oEPA
United States
Environmental Protection
Agency
Office of Water
4304T
EPA 822-R-21-006
August 2021
2021 Revision* to:
Aquatic Life Ambient Water
Quality Criterion for
Selenium - Freshwater
2016
* This 2021 revision entails errata regarding footnotes on pages xv and 99, as
described on page vii.
U.S. Environmental Protection Agency
Office of Water
Office of Science and Technology
Washington, D.C.
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Table of Contents
Table of Contents ii
List of Tables v
List of Figures vi
Notice vii
Foreword viii
Acknowledgements ix
Acronyms xi
Executive Summary xii
1 Introduction and Background 1
1.1 History of the EPA Recommended Selenium AWQC for Aquatic Life 1
2 Problem Formulation 4
2.1 Overview of Selenium Sources and Occurrence 4
2.2 Environmental Fate and Transport of Selenium in the Aquatic Environment 8
2.2.1 Selenium Species in Aquatic Systems 8
2.2.2 Bioaccumulation of Selenium in Aquatic Systems 10
2.3 Mode of Action and Toxicity of Selenium 12
2.4 Narrow Margin between Sufficiency and Toxicity of Selenium 14
2.5 Interactions with Mercury 15
2.6 Assessment Endpoints 16
2.7 Measures of Effect 19
2.7.1 Fish Tissue 20
2.7.2 Water 23
2.7.3 Summary of Assessment Endpoints and Measures of Effect 24
2.7.4 Conceptual Model of Selenium Effects on Aquatic Life 25
2.7.5 Analysis Plan for Derivation of the Chronic Fish Tissue-Based Criterion
Elements 26
2.7.6 Analysis Plan for Derivation of the Fish Tissue Criterion Elements Duration 27
2.7.7 Analysis Plan for Derivation of the Fish Tissue Criterion Elements Return
Frequency 28
2.7.8 Analysis Plan for Derivation of Chronic Water-based Criterion Element 29
2.7.9 Analysis Plan for Derivation of the Water Criterion Elements Duration 31
2.7.10 Analysis Plan for Intermittent-Exposure Water-based Criterion Element
Derivation 32
3 Effects Analysis for Freshwater Aquatic Organisms 34
3.1 Chronic Tissue-Based Selenium Criterion Element Concentration 34
3.1.1 Acceptable Studies of Fish Reproductive Effects for the Four Most Sensitive
Genera 35
3.1.2 Summary of Acceptable Studies of Fish Reproductive Effects 44
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3.1.3 Derivation of Tissue Criterion Element Concentrations 47
3.1.4 Invertebrate Chronic Effects 54
3.1.5 Summary of Relevant Invertebrate Tests 57
3.1.6 Selenium Fish Tissue Toxicity Data Fulfilling Minimum Data Needs 58
3.2 Chronic Water Column-based Selenium Criterion Element 60
3.2.1 Translation from Fish Tissue Concentration to Water Column Concentration 60
3.2.2 Equation Parameters 69
3.2.3 Food-Web Models 81
3.2.4 Classifying Categories of Aquatic Systems 82
3.2.5 Deriving Protective Water Column Concentrations for Lentic and Lotic System
Categories 87
3.2.6 Derivation of Averaging Period for Chronic Water Criterion Element 93
3.3 Intermittent-Exposure Water Criterion Element: Derivation from the Chronic Water
Criterion Element 94
4 National Criterion for Selenium in Fresh Waters 98
4.1 Protection of Downstream Waters 102
5 Site-specific Criteria 103
6 Effects Characterization 104
6.1 Fish and Amphibians 104
6.1.1 Principles for Using Studies for which ECios Cannot Be Calculated 104
6.1.2 Acceptable Studies of Fish Reproductive Effects of Genera that were not among
the Four Most Sensitive Genera 105
6.1.3 Reproductive Effects in Catfish (Ictaluridae) Ill
6.1.4 Reproductive Effects in Amphibians (Xenopus laevis) 116
6.1.5 Reproductive Studies Not Used in the Numeric Criterion Derivation 116
6.1.6 Salmo GMCV: EPA Re-analysis of a Key Study Used in Criterion Derivation 119
6.1.7 Impact of Number of Tested Species on Criterion Derivation 120
6.1.8 Comparisons between Concentrations in Different Tissues 120
6.1.9 Studies of Non-Reproductive Effects 121
6.1.10 Special conditions for consideration of primacy of water column criterion
elements over fish tissue criterion elements 126
6.2 Water 127
6.2.1 Validation of Translation Equation for Developing Water Column
Concentrations 127
6.2.2 Sulfate-Selenium Interactions 130
6.3 Uncertainty 131
6.3.1 Tissue Criterion Element 131
6.3.2 Trophic Transfer Factors 136
6.3.3 Enrichment Factors 138
6.3.4 Water Values 140
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6.4 Protection of Threatened or Endangered Species 140
6.4.1 Special Consideration for Pacific Salmonid Juveniles 142
6.5 Aquatic-Dependent Wildlife is Beyond the Scope of this Aquatic Criteria
Derivation 145
6.6 Summary 146
7 References 149
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List of Tables
Table 1. Summary of the Recommended Freshwater Selenium Ambient Chronic Water Quality
Criterion for Protection of Aquatic Life xv
Table 2.1. Predominant Chemical Forms of Selenium in Discharges Associated with Different
Activities and Industries 8
Table 2.2. Summary of Assessment Endpoints and Measures of Effect Used in Criteria
Derivation for Selenium 24
Table 3.1. Maternal Transfer Reproductive Toxicity Studies 45
Table 3.2. Ranked Genus Mean Chronic Values for Fish Reproductive Effects Measured as
Egg or Ovary Concentrations 47
Table 3.3. Four Lowest Genus Mean Chronic Values for Fish Reproductive Effects 48
Table 3.4. Tested Reproductive-Effect Whole Body (WB) Concentrations Measured Directly
or Converted to WB Concentrations from Egg-Ovary (EO) Concentrations 50
Table 3.5. The Lowest Four Reproductive-Effect Whole-Body GMCVs 51
Table 3.6. Tested Reproductive-Effect Muscle (M) Concentrations Measured Directly or
Converted to M Concentrations from Egg-Ovary (EO) Concentrations 52
Table 3.7. The Lowest Four Reproductive-Effect Fish Muscle GMCVs 53
Table 3.8. Ranked Invertebrate Whole-Body Chronic Values with Translation to Expected
Accompanying Fish Whole-Body Concentrations 58
Table 3.9. Minimum Data Requirements Summary Table Reflecting the Number of Species and
Genus Level Mean Values Represented in the Chronic Toxicity Dataset for Selenium in
Freshwater 58
Table 3.10. EPA-Derived Trophic Transfer Factor (TIT) Values for Freshwater Aquatic
Invertebrates 75
Table 3.11. EPA-Derived Trophic Transfer Factor (TTF) Values for Freshwater Fish 76
Table 3.12. EPA-Derived Egg-Ovary to Whole-Body Conversion Factor (CF) Values 79
Table 3.13. Data for the 65 Site Minimum Translations of the Egg-Ovary Criterion
Concentration Element to a Water Column Concentration 89
Table 3.14. Water Column Criterion Element Concentration Values Translated from the Egg-
Ovary Criterion Element 92
Table 3.15. Representative Values of the Intermittent Water Criterion Concentration
Element 97
Table 4.1. Summary of the Recommended Freshwater Selenium Ambient Chronic Water
Quality Criterion for Protection of Aquatic Life 99
Table 6.1. Correlation Matrix (Values of r) for Ictaluridae and Centrarchidae Abundance and
for Selenium Food Chain Contamination for the Hyco Reservoir 112
Table 6.2. Freshwater Chronic Values from Acceptable Tests - Non-Reproductive
Endpoints 122
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List of Figures
Figure 2.1. Selenium in Surficial Soils and Aquatic Sediments in counties of the Conterminous
United States 6
Figure 2.2. Diagram of Selenium Partitioning, Bioaccumulation, and Effects in the Aquatic
Environment 25
Figure 2.3. Conceptual Model for Translating the Selenium Egg-Ovary Concentration to a
Water Column Concentration 32
Figure 3.1. Distribution of Reproductive-Effect GMCVs for Fish Measured as Egg-Ovary
Concentrations 49
Figure 3.2. Distribution of Reproductive-Effect GMCVs for Fish, either Measured as Whole-
Body Concentrations in the Original Tests, or Measured as Egg-Ovary Concentrations
but Converted to Whole-Body 51
Figure 3.3. Distribution of Reproductive-Effect GMCVs for Fish, either Measured as Muscle in
the Original tests, or Measured as Egg-Ovary Concentrations but Converted to Muscle
Concentrations 54
Figure 3.4. Example Aquatic System Scenarios and the Derivation of the Equation Parameter
TTp gy
Figure 3.5. Effect of Relative Sample Collection Time on Correlation Coefficients of Selenium
Measurements in Particulate Material, and Invertebrate and Fish Tissue 72
Figure 3.6. Enrichment Factors (EF) for 96 Aquatic Sites Derived from Published Studies and
Organized by Waterbody Type 84
Figure 3.7. The Relationship between Cwater and Cparticuiate, and Cwater and EF for the 39 Lentic
and 57 Lotic Aquatic Systems 86
Figure 3.8. Distribution of EF Values for the Same 96 Aquatic Systems 87
Figure 3.9. Probability Distribution of the Water Column Concentrations Translated from the
Egg-Ovary Criterion Element at 26 Lentic and 39 Lotic Aquatic Sites 92
Figure 3.10. Illustration of Intermittent Spike Exposure Occurring for a Certain Percentage of
Time (e.g., 10%) Over a 30-Day Period, and Background Exposure Occurring for the
Remaining Percentage of Time (e.g., 90%) 95
Figure 6.1. Crutchfield (2000) Observations of Channel Catfish (CCF) and Largemouth Bass
(LMB) in Hyco Reservoir Beginning a Few Years after Populations of Largemouth
Bass had been Reduced by Se Contamination 115
Figure 6.2. Distribution of Fish Reproductive Effect GMCVs from Figure 3.2 and
Distribution of Fish Nonreproductive Effect GMCVs and Invertebrate GMCVs 125
Figure 6.3. Scatter Plot of Predicted Versus Measured Concentrations of Selenium in Fish 129
VI
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ERRATA
In 2021, EPA identified that the following text was missing from the second sentence in
footnote 4 in the criterion table: "When selenium inputs are increasing," Corrected footnote 4
now states: "4. Water column values are based on dissolved total selenium in water and are
derived from fish tissue values via bioaccumulation modeling. When selenium inputs are
increasing, water column values are the applicable criterion element in the absence of steady-
state condition fish tissue data." Footnotes 2 and 3 also reflect that footnote 4 was corrected.
Notice
This document has undergone a contractor-led external expert peer-review, as well as an
EPA review process following publication and public comments received on the May 14, 2014,
and July 28, 2015 criteria drafts. Final review by the Health and Ecological Criteria Division,
Office of Science and Technology, U.S. Environmental Protection Agency, has been completed,
and the document has been approved for publication.
This document provides guidance to States and Tribes authorized to adopt water quality
standards under the Clean Water Act (CWA), to protect aquatic life from toxic effects of
selenium. Under the CWA, States and Tribes are to adopt water quality criteria to protect
designated uses. State and tribal decision makers retain the discretion to adopt approaches on a
case-by-case basis that differ from this guidance when appropriate. While this document contains
EPA's scientific recommendations regarding ambient concentrations of selenium that protect
aquatic life, it does not substitute for the CWA or EPA's regulations; nor is it a regulation itself.
Thus, it cannot impose legally-binding requirements on EPA, States, Tribes, or the regulated
community, and might not apply to a particular situation based upon the circumstances. EPA
may change this document in the future. This document has been approved for publication by the
Office of Science and Technology, Office of Water, U.S. Environmental Protection Agency.
Mention of trade names or commercial products does not constitute endorsement or
recommendation for use. This document can be downloaded from:
http://www.epa.gov/waterscience/criteria/aqlife.html
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Foreword
Section 304(a)(1) of the Clean Water Act requires the Administrator of the Environmental
Protection Agency to publish water quality criteria that accurately reflect the latest scientific
knowledge on the kind and extent of all identifiable effects on health and welfare that might be
expected from the presence of pollutants in any body of water, including ground water. This
document presents EPA's updated chronic ambient water quality criterion (AWQC) for the
protection of aquatic life based upon consideration of all available information relating to effects
of selenium on aquatic organisms. EPA has incorporated revisions into this final document based
on comments from the general public and an external expert peer review panel on an earlier draft
published in the Federal Register in May 14, 2014, and comments from the general public on a
second draft published in the Federal Register in July 28, 2015.
The term "water quality criteria" is used in two sections of the Clean Water Act, section
304(a)(1) and section 303(c)(2). The term has a different program impact in each section. In
section 304, the term represents a non-regulatory, scientific assessment of ecological effects. The
criterion presented in this document is such a scientific assessment. If water quality criteria
associated with specific designated uses are adopted by a state or authorized tribe as water
quality standards under section 303, and approved by EPA, they become applicable Clean Water
Act water quality standards in ambient waters within that state or tribe. Water quality criteria
adopted in state or tribal water quality standards could have the same numerical values as criteria
developed under section 304. However, states and authorized tribes may adopt water quality
criteria that reflect adjustments to EPA's recommended section 304 criteria to reflect local
environmental conditions and human exposure patterns. Alternatively, states and authorized
tribes may derive numeric criteria based on other scientifically defensible methods but the
criteria must be protective of designated uses. It is not until their adoption as part of state or
tribal water quality standards, and subsequent approval by EPA, that criteria become Clean
Water Act applicable water quality standards. Guidelines to assist the states and authorized tribes
in modifying the criteria presented in this document are contained in the Water Quality Standards
Handbook (U.S. EPA 1994, as updated), which along with additional guidance on the
development of water quality standards and other water-related programs of this Agency have
been developed by the Office of Water.
This document provides guidance only. It does not establish or affect legal rights or
obligations. It does not establish a binding norm and cannot be finally determinative of the issues
addressed. Agency decisions in any particular situation will be made by applying the Clean
Water Act and EPA regulations on the basis of specific facts presented and scientific information
then available.
Elizabeth Southerland
Director
Office of Science and Technology
viii
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Acknowledgements
Technical Analysis Leads
Joseph Beaman, U.S. EPA, Office of Water, Office of Science and Technology, Health and
Ecological Criteria Division, Washington, DC
beaman. i oe@epa. gov (primary contact person)
Gary Russo, U.S. EPA, Office of Water, Office of Science and Technology, Standards and
Health Protection Division, Washington, DC
russo.gary@epa.gov
Charles Delos (Retired) U.S. EPA, Office of Water, Office of Science and Technology, Health
and Ecological Criteria Division, Washington, DC
U.S. EPA Office of Water Reviewers
Elizabeth Behl
Kathryn Gallagher
Lisa Huff
Michael Elias
Intra-Agency Panel Peer Reviewers (2014-2016)
Russell Erickson, Dale Hoff and Charles Stephan, U.S. EPA, Office of Research and
Development, Mid-Continent Ecology Division, Duluth, MN
Cindy Roberts, U.S. EPA, Office of Research and Development, Office of Science Policy,
Washington, DC
Jim Lazorchak, U.S. EPA, Office of Research and Development, National Exposure Research
Laboratory, Cincinnati, OH
Jeff Gallagher, U.S. EPA, Office of Chemical Safety and Pollution Prevention, Office of
Pollution Prevention and Toxics, Washington, DC
Catherine Aubee and Geoff Sinclair, Office of Chemical Safety and Pollution Prevention, Office
of Pesticide Programs, Arlington, VA
David Hair, Laura Phillips, and Scott Wilson, U.S. EPA, Office of Water, Office of Wastewater
Management, Washington, DC
Rosaura Conde, Ruth Chemerys, and Eric Monschein, U.S. EPA, Office of Water, Office of
Wetlands, Oceans, and Watersheds, Washington, DC
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Jim Keating. Julianne McLaughlin, and Lars Wilcut and, U.S. EPA, Office of Water, Office of
Science and Technology, Washington, DC
Cheryl Atkinson and Frank Borsuk, U.S. EPA Region 3, Philadelphia, PA, and Wheeling, WV
Joel Hansel, U.S. EPA Region 4, Atlanta, GA
Dean (Robie) Anson, Candice Bauer, Katharine Marko, and Angela Vincent, U.S. EPA Region
5, Chicago, IL
Jason Gildea and Lareina Guenzel, U.S. EPA Region 8, Denver, CO
Diane Fleck, Eugenia McNaughton, and Daniel Oros, U.S. EPA Region 9, San Francisco, CA
Lisa Macchio, and Burt Shepard, U.S. EPA Region 10, Seattle, WA
Technical support was provided by Great Lakes Environmental Center
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Acronyms
AE Assimilation Efficiency
AWQC Ambient Water Quality Criteria
BAF Bioaccumulation Factor
CF Conversion Factor
CV Chronic Value (expressed in this document as an EC 10)
CWA Clean Water Act
dw Dry Weight
ECx Effect Concentration at X Percent Effect Level
EF Enrichment Factor
EPA Environmental Protection Agency
EO Egg Ovary
FCV Final Chronic Value
GMCV Genus Mean Chronic Value
HNOEC Highest No Observed Effect Concentration
IR Ingestion Rate
ke Rate of selenium loss
ku Rate of selenium uptake
LOEC Lowest Observed Effect Concentration
M Muscle
MATC Maximum Acceptable Toxicant Concentration (expressed mathematically as the
geometric mean of the NOEC and LOEC)
MDR Minimum Data Recommendations or Requirements
NPDES National Pollutant Discharge Elimination System
NOEC No Observed Effect Concentration
SMCV Species Mean Chronic Value
SSD Species Sensitivity Distribution
TMDL Total Maximum Daily Load
TRAP EPA's Statistical Program: Toxicity Relationship Analysis Program
TTF Trophic Transfer Factor
WB Whole body
WQBELS Water Quality-based Effluent Limitations
WQC Water Quality Criteria
WQS Water Quality Standards
ww Wet Weight
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Executive Summary
This document sets forth the basis for and derivation of the Clean Water Act, Section
304(a) water quality criterion for protecting freshwater aquatic life from harmful effects of
selenium, a naturally occurring chemical element that is nutritionally essential in small amounts,
but toxic at higher concentrations. This assessment provides a critical review of all data
identified in EPA's literature search quantifying the toxicity of selenium to freshwater aquatic
organisms, and provides a basis for a criterion that will assure protection of populations of fish,
amphibians, aquatic invertebrates, and plants, based on available data.
Although selenium may cause acute toxicity at high concentrations, the most deleterious
effect on aquatic organisms is due to its bioaccumulative properties; these chronic effects are
found at lower concentrations than acute effects. Organisms in aquatic environments exposed to
selenium accumulate it primarily through their diets, and not directly through water (Chapman et
al. 2010). The best science also indicates that selenium toxicity occurs primarily through transfer
to the eggs and subsequent reproductive effects. Consequently, in harmony with the
recommendations of expert panels (U.S. EPA 1998; Chapman et al. 2010) and with peer review
and public comments on previous U.S. EPA (2004, 2014, 2015) drafts, the Agency developed a
chronic criterion reflective of the reproductive effects of selenium concentrations on fish species.
The 2016 "Aquatic Life Ambient Water Quality Criterion for Selenium - Freshwater,
2016," is a chronic criterion that is composed of four elements. All elements are protective
against chronic selenium effects. Two elements are based on the concentration of selenium in
fish tissue and two elements are based on the concentration of selenium in the water column. The
recommended elements are: (1) a fish egg-ovary element; (2) a fish whole-body and/or muscle
element; (3) a water column element (one value for lentic and one value for lotic aquatic
systems); and (4) a water column intermittent element to account for potential chronic effects
from short-term exposures (one value for lentic and one value for lotic aquatic systems). The
assessment of the available data for fish, invertebrates, and amphibians indicates that a criterion
value derived from fish will protect the aquatic community. All four criterion elements applied
together should protect aquatic life from the chronic effects of exposure to total selenium in
waters inhabited by fish, as well as "fishless waters."
Xll
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Because the factors that determine selenium bioaccumulation vary among aquatic
systems, site-specific water column criterion element values may be necessary at aquatic sites
with high selenium bioaccumulation to ensure adequate protection of aquatic life (Appendix K).
Finally, this freshwater chronic selenium criterion applies only to aquatic life, and is not intended
to address selenium toxicity to aquatic-dependent wildlife such as aquatic-dependent birds.
The toxicity studies relevant to the derivation of the fish tissue selenium criterion
elements involve (a) extended duration dietary exposure, and (b) measurement of total selenium
in the tissue of the target organism. Selenium either in fish whole-body or in muscle is usually
measured in non-reproductive studies, and selenium in eggs or ovaries is typically measured in
reproductive studies. Selenium accumulation in the eggs of the exposed adult female prior to
spawning has been shown to yield the most robust relationship (statistically significant) with
occurrence of deformities and reduced survival of the offspring.
The outcome of assessing both reproductive and non-reproductive studies under
laboratory and field conditions led EPA to the conclusion, consistent with expert consensus
(Chapman et al. 2009, 2010), that reproductive effects, linked to egg-ovary selenium
concentrations, provide the most sound basis for the criterion compared to non-reproductive
(e.g., survivorship, growth) endpoints. Reproductive effects have been linked to observed
reductions in the populations of sensitive fish species in waterbodies having elevated
concentrations of selenium (Young et al. 2010). EPA applied the sensitivity distribution concepts
from the U.S. EPA Guidelines for Deriving Numerical National Water Quality Criteria for the
Protection of Aquatic Organisms and their Uses (Stephan et al. 1985) to derive the national
selenium criterion. Based on the available data, expressed as ECio values, the egg-ovary criterion
element concentration is 15.1 milligrams selenium per kilogram dry weight (mg Se/kg dw),
based primarily on 17 reproductive studies representing 10 fish genera.
EPA recommends states and tribes adopt all four elements of the criterion into their water
quality standards. Two elements are based on the concentration of selenium in fish tissue (eggs
or ovaries, and whole-body or muscle) and two elements are based on the concentration of
selenium in the water column (a 30-day chronic element and an intermittent exposure element).
Both water column elements are further refined into values for lentic waters (e.g., lakes and
impoundments) and lotic waters (e.g., rivers and streams). The difference between lentic and
lotic water column values reflect the observed difference in selenium bioaccumulation in these
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two categories of aquatic systems (ATSDR 2003; Luoma and Rainbow 2005; Orr et al. 2006;
Simmons and Wallschlagel 2005). EPA derived the intermittent exposure element based on the
chronic 30-day water column element and the fraction of any 30-day period during which
elevated selenium concentrations occur. EPA recommends the intermittent element to address
short-term exposures that contribute to chronic effects through selenium bioaccumulation (e.g.,
releases from storage ponds or other intermittent releases). EPA derived the values for the water-
column criterion elements from the egg-ovary element by assessing food-chain bioaccumulation
based on available data collected at lentic and lotic systems in the continental United States.
Thus, all four criterion elements are based on reproductive effects in freshwater fish.
EPA primarily used field studies in freshwater systems to provide quantitative estimates
of selenium bioaccumulation in particulate material (algae, detritus, and sediment) from water,
and used field observations and laboratory data to quantify and model the trophic transfer of
selenium from particulate material into invertebrates, and from invertebrates into fish. EPA
additionally used field and laboratory observations to assess species-specific selenium
partitioning between different tissues within a fish (whole-body, eggs and/or ovaries, and
muscle). EPA developed food web models of fish in aquatic systems with a range of
bioaccumulation potentials and used the food web models with the species-specific estimates of
trophic transfer (or the most proximate taxonomic surrogate when species-specific data was not
available) to develop water column criterion elements from the egg-ovary criterion element for
lotic and lentic aquatic systems. EPA validated this approach using selenium measurements from
aquatic systems with a range of bioaccumulation potentials. Similar approaches could be used in
the derivation of selenium criteria in saltwater or estuarine systems with selenium data and food
webs relevant to those systems.
While more than half the available chronic studies were fish studies, available field data
and laboratory toxicity studies suggest that a criterion based on fish will protect amphibians,
aquatic invertebrates, and plants since these taxa appear to be less sensitive to selenium than fish
(see Sections 3.1.4 and 6.1.4),
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Table 1. Summary of the Recommended Freshwater Selenium Ambient Chronic Water
Quality Criterion for Protection of Aquatic Life.
Media
Type
I' isli Tissue1
\Yater Column4
Criterion
Klcmcnt
Kgg/Ovary 2
I'isli W hole
liody or
Muscle'
Monthly
Average
Kxposurc
Intermittent KxposuiV
Magnitude
1 5 I mg/kg dw
8.5 mg/kg dw
whole body
or
11.3 mg/kg
dw muscle
(skinless,
boneless filet)
1.5 |ig/L in
lentic aquatic
systems
3.1 |ig/L in lotic
aquatic systems
WQClnt =
WQCso-day ~ Cbkgrnd(.l ~ f int)
f int
Duration
Instantaneous
measurement6
Instantaneous
measurement6
30 days
Number of days/month with an
elevated concentration
frequency
Not to be
exceeded
Not to be
exceeded
Not more than
once in three
years on
average
Not more than once in three years on
average
1. Fish tissue elements are expressed as steady-state.
2. Egg/Ovary supersedes any whole-body, muscle, or water column element when fish egg/ovary concentrations are
measured, except as noted in footnote 4 below.
3. Fish whole-body or muscle tissue supersedes water column element when both fish tissue and water concentrations are
measured, except as noted in footnote 4 below.
4. Water column values are based on dissolved total selenium in water and are derived from fish tissue values via
bioaccumulation modeling. When selenium inputs are increasing, water column values are the applicable criterion element
in the absence of steady-state condition fish tissue data.
5. Where WQC30-day is the water column monthly element, for either a lentic or lotic waters; Cbkgrnd is the average
background selenium concentration, and fint is the fraction of any 30-day period during which elevated selenium
concentrations occur, with fmt assigned a value >0.033 (corresponding to 1 day).
6. Fish tissue data provide instantaneous point measurements that reflect integrative accumulation of selenium over time and
space in fish population(s) at a given site.
The recommended chronic selenium criterion is expected to protect the entire aquatic
community, including fish, amphibians, and invertebrates, based on available data. Because fish
are the most sensitive to selenium effects, EPA recommends that selenium water quality criterion
elements based on fish tissue (egg-ovary, whole body, and/or muscle) data take precedence over
the criterion elements based on water column selenium data due to the fact, noted above, that fish
tissue concentrations provide a more robust and direct indication of potential selenium effects in
fish. However, because selenium concentrations in fish tissue are a result of selenium
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bioaccumulation via dietary exposure, there are two specific circumstances where the fish tissue
concentrations do not fully represent potential effects on fish and the aquatic ecosystem: 1)
"Ashless" waters, and 2) areas with new selenium inputs.
For purposes of this document, EPA defines "Ashless waters" as waters with insufficient
instream habitat and/or flow to support a population of any fish species on a continuing basis, or
waters that once supported populations of one or more fish species but no longer support fish
(e.g., extirpation) due to temporary or permanent changes in water quality (e.g., selenium
pollution), flow or instream habitat. Because of the inability to collect sufficient fish tissue to
measure selenium concentrations in fish in such waters, water column concentrations will best
represent selenium levels required to protect aquatic communities and downstream waters in
such areas. Appendix K of this criterion document discusses approaches to develop a site-
specific water column criterion element in such situations.
For purposes of this document EPA defines "new inputs" as new activities resulting in
the release of selenium into a lentic or lotic aquatic system. New inputs will likely result in a
greater concentrations of selenium in the food web and a relatively slow increase in the selenium
concentration in fish until the new selenium release achieves a quasi-"steady-state" balance in
the aquatic system. EPA estimates that the concentration of selenium in fish tissue will not reach
steady state for several months in lotic systems and longer time periods (e.g., 2 to 3 years) in
lentic systems. Achievement of steady state in an aquatic system also depends on the
hydrodynamics of the aquatic system, (particularly reservoirs with multiple riverine inputs), the
location of the selenium input and the particular food web. EPA expects the time needed to
achieve steady state with new or increased selenium inputs to be site specific. Thus, EPA
recommends that fish tissue criterion elements not take precedence over the water column
criterion elements until the aquatic system achieves steady state. In the interim, EPA
recommends sampling and using site-specific data to determine steady state in the receiving
water to gain a better understanding of the selenium bioaccumulation dynamics in a given
system.
EPA recommends states and tribes adopt into their water quality standards a selenium
criterion that expresses the four elements as a single criterion composed of multiple parts in a
manner that explicitly affirms the primacy of the whole-body or muscle element over the water
column elements, and the egg-ovary element over any other element. Adopting the fish whole-
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body or muscle tissue element into water quality standards ensures the protection of aquatic life
when measurements from fish eggs or ovary are not available, and adopting the water column
element ensures protection when fish tissue measurements are not available.
EPA recommends that when states adopt a four-part criterion for selenium reflecting
EPA's recommended criterion, states use the default monthly average exposure water column
elements of the criterion, adopted as part of the state's water quality criterion when implementing
the criterion under the National Pollutant Discharge Elimination System (NPDES) permits
program and to assist with implementation of other Clean Water Act programs. Alternatively,
states may want to develop adopt, and submit for EPA approval, either a site-specific water
column criterion element (or set of lentic/lotic criterion element values), or a set of procedures to
facilitate the translation of the fish tissue criterion concentration elements into site-specific water
concentration values. A site-specific water column criterion element or set of lentic/lotic
criterion element values can be developed using a mechanistic modeling approach (Presser and
Luoma 2010) or using the empirical bioaccumulation factor approach, both described in
Appendix K, for the specific waterbody or waterbodies. Any translation procedure must be
scientifically defensible, produce repeatable, predictable outcomes, and result in criterion
element values that protect the applicable designated use. Examples of such procedures include
the mechanistic modeling approach and the empirical BAF approach described in Appendix K.
This recommended selenium criterion applies to freshwater lentic and lotic systems, as it
is based on the toxicity of selenium to freshwater organisms. A similar approach may be
appropriate for deriving criteria for selenium in estuarine and marine waters if appropriate data
are available.
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1 Introduction and Background
The objective of the Clean Water Act (CWA) is to "restore and maintain the chemical,
biological and physical integrity of the Nation's waters." One of the tools that EPA uses to meet
this objective is the development of recommended ambient water quality criteria (AWQC) under
section 304(a)(1) of the Act. As provided for by the Clean Water Act, EPA reviews and from
time to time revises 304(a)(1) AWQC to ensure the criteria are consistent with the latest
scientific knowledge. Section 304(a) aquatic life criteria serve as recommendations to states and
authorized tribes for defining ambient water concentrations that will protect against adverse
ecological effects to aquatic life resulting from exposure to a pollutant found in water from direct
contact or, ingestion of contaminated water and/or food. Aquatic life criteria address the Clean
Water Act goals of providing for the protection and propagation of fish and shellfish. When
adopted into state or tribal water quality standards (WQS), these criteria can become a basis for
establishing National Pollutant Discharge Elimination System (NPDES) program permit limits
and, the basis for listing impaired waters under Section 303(d) and establishing Total Maximum
Daily Loads (TMDLs).
1.1 History of the EPA Recommended Selenium AWQC for Aquatic Life
In 1980 EPA first published numeric aquatic life criteria for selenium in freshwater.
These criteria were based on water-only exposure (no dietary exposure). In order to address the
lack of consideration of bioaccumulation in the 1980 selenium criteria, in 1987 EPA published
updated selenium criteria to address field-based toxicity observed in aquatic ecosystems at levels
below the existing criteria values. The 1987 criteria were field-based and accounted for both the
water column and dietary uptake pathways manifested at Belews Lake, North Carolina (USA), a
cooling water reservoir where water quality and fish communities had been affected by selenium
loads from a coal-fired power plant. At that time EPA also provided an acute criterion of 20 |ig/L
derived from a reverse application of an acute-chronic ratio obtained from conventional water-
only exposure toxicity tests applied to the 5 |ig/L chronic value based on dietary and water
column exposure in Belews Lake.
In 1998-1999 EPA published a revised acute criterion, a formula that recognized that the
two oxidation states, selenate and selenite, appeared to have substantially different acute
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toxicities. This acute criterion assumed toxicity was based on water-only exposure. Subsequent
research has demonstrated that sulfate levels influence selenate toxicity in water-only exposures.
In 1998 EPA held a peer consultation workshop (EPA-822-R-98-007) to evaluate new
science available for selenium relevant to the selenium aquatic life criterion. EPA concluded, and
the peer reviewers agreed, that fish-tissue values more directly represent chronic adverse effects
of selenium than the conventional water concentration approach used by EPA to protect aquatic
life, because chronic selenium toxicity is primarily based on the food-chain bioaccumulation
route, not on a water column route of exposure.
In 2004 EPA published a draft chronic whole-body fish-tissue criterion with a water-
based monitoring trigger in the summer and fall. The critical effect considered at that time was
the impact on survivorship based on overwintering stress to bluegill sunfish. An acute criterion
was estimated at that time that addressed concerns with the species of selenium present and
adjusted for sulfate levels; however, it did not address the dietary uptake pathway.
Further refinement of the fish tissue approach occurred in 2009 based on the findings of a
Pellston scientific workshop on the ecological risk assessment of selenium (Chapman et al. 2009,
2010). As presented by Chapman et al. (2009), some key findings resulting from that workshop
are:
• Diet is the primary pathway of selenium exposure for both invertebrates and vertebrates.
• Traditional methods for predicting toxicity on the basis of exposure to dissolved [water
column] concentrations do not work for selenium because the behavior and toxicity of
selenium in aquatic systems are highly dependent upon site-specific factors, including
food web structure and hydrology.
• Selenium toxicity is primarily manifested as reproductive impairment due to maternal
transfer, resulting in embryotoxicity and teratogenicity in egg-laying vertebrates.
In this 2016 final recommended freshwater chronic criterion for selenium, EPA includes
revisions based on the public and external expert peer reviews of the 2014 draft, public
comments on the 2015 draft, data and information from additional studies provided by the public
and peer reviewers, and additional scientific analyses. EPA also conducted a new literature
review and reanalyzed data considered in the 2004 and 2009 draft criteria documents. This final
criterion reflects the latest scientific consensus (e.g., Chapman et al. 2010) on the reproductive
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effects of selenium on aquatic life and their measurement in aquatic systems and supersedes all
previous national aquatic life water quality criteria for selenium.
EPA is recommending a national selenium criterion expressed as four elements. All
elements are protective against chronic selenium effects, and account for both short term and
longer term exposure to selenium. Two elements are based on the concentration of selenium in
fish tissue (eggs and ovaries, and whole-body or muscle) and two elements are based on the
concentration of selenium in the water-column (two 30-day chronic values and an intermittent
value). EPA derived the 30-day chronic water column element from the egg-ovary element by
modeling selenium bioaccumulation in food webs of lotic and lentic aquatic systems. EPA is
recommending the intermittent value to address short-term exposures that could contribute to
chronic effects through selenium bioaccumulation in either lotic or lentic systems. EPA derived
the intermittent element based on the chronic 30-day water column element and the fraction of
any 30-day period during which elevated selenium concentrations occur. These water column
criterion elements apply to the total of all oxidation states (selenite, selenate, organic selenium,
and any other forms) (See Appendix L for Analytical Methods for Measuring Selenium). Aquatic
communities are expected to be protected by this chronic criterion from any potential acute
effects of selenium.
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2 Problem Formulation
Problem formulation provides a strategic framework for water quality criteria
development by focusing the effects assessment on the most relevant chemical properties and
endpoints. The structure of this effects assessment is consistent with EPA's Guidelines for
Ecological Risk Assessment (U.S. EPA 1998).
This ecological effects assessment defines a scientifically-defensible water quality
criterion for selenium under section 304(a)(1) of the Clean Water Act. Clean Water Act Section
304(a)(1) requires EPA to develop criteria for water quality that accurately reflect the latest
scientific knowledge. These criteria are based solely on high quality data and best professional
scientific judgments on toxicological effects. Criteria are developed following overarching
guidance outlined in the Agency's Guidelines for Deriving Numerical National Water Quality
Criteria for the Protection of Aquatic Organisms and Their Uses (Stephan et al. 1985), hereafter
referred to as "EPA Ambient Water Quality Criteria Guidelines." States and authorized tribes
may adopt EPA's recommended criteria into their water quality standards to protect designated
uses of water bodies, they may modify EPA's criteria to reflect site-specific conditions, or they
may derive criteria using other scientifically-defensible methods, all subject to EPA review and
approval.
2.1 Overview of Selenium Sources and Occurrence
Selenium is a naturally occurring element present in sedimentary rocks and soils. It is
also present in the aquatic environment as methyl derivatives of selenium, naturally occurring in
freshwaters through methylation by bacteria (Ranjard et.al. 2003). Selenium's occurrence in
surficial soils and aquatic sediments in the United States is illustrated in Figure 2.1. There are
around 40 known selenium-containing minerals, some of which can have as much as 30%
selenium, but all are rare and generally occur together with sulfides of metals such as copper,
zinc and lead (Emsley 2011). Sedimentary rocks, particularly shales, have the highest naturally
occurring selenium content (Burau 1985). The distribution of organic-enriched, sedimentary
shales, petroleum source rocks, ore deposits, phosphorites, and coals, in which selenium
typically co-occurs, is well characterized in the United States (Presser et al. 2004). Natural
weathering of selenium-bearing geologic strata containing selenium can lead to selenium
leaching into groundwater and surface water. Two major anthropogenic activities are known to
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cause increased selenium mobilization and introduction into aquatic systems. The first is the
mining of metals, minerals and refinement and use of fossil fuels; the second is irrigation of
selenium-rich soils.
Mining activities bring selenium-enriched deposits to the surface, where they are exposed
to physical weathering processes. The release of selenium related to resource extraction activities
is most common in the phosphate deposits of southeast Idaho and adjacent areas of Wyoming,
Montana, and Utah, and in coal mining areas in portions of West Virginia, Kentucky, Virginia,
and Tennessee (Presser et al. 2004). Where selenium-containing minerals, rocks, and coal are
mined, selenium can be mobilized when rock overburden and waste materials are crushed,
increasing the surface area and exposure of material to weathering processes. Selenium
contamination of surface waters can also occur when sulfide deposits of iron, uranium, copper,
lead, mercury, silver, and zinc are released during the mining and smelting of these metal ores.
Where coal is burned for power production, selenium can enter surface waters as drainage from
fly-ash ponds and fly-ash deposits on land (Gillespie and Baumann 1986). Fly ash deposits have
a high surface area to volume ratio, resulting in rates of selenium in leachate several times higher
than from the parent feed coal (Fernandez-Turiel et al. 1994). The refining of crude oil
containing high levels of selenium can also be a major source of loading in certain water bodies
(Maher et al. 2010).
Irrigation of selenium-rich soils for crop production in arid and semi-arid regions of the
country can mobilize selenium and move it off-site in surface water runoff or via leaching into
ground water. Where deposits of Cretaceous marine shales occur, they can weather to produce
high selenium soils; such soils are present in many areas of the western U.S. (Lemly 1993c).
Selenium is abundant in the alkaline soils of the Great Plains, and some ground waters in
California, Colorado, Kansas, Oklahoma, South Dakota and Wyoming contain elevated
concentrations of selenium due to weathering of and leaching from rocks and soils. In semi-arid
areas of the West, irrigation water applied to soils containing soluble selenium can leach
selenium. The excess water (in tile drains or irrigation return flow) containing selenium can be
discharged into basins, ponds, or streams. For example, elevated selenium levels at the Kesterson
Reservoir in California originated from agricultural irrigation return flow collected in tile drains
that discharged into the reservoir (Ohlendorf et al. 1986).
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Se (ppm)
No data
0.01-0.12
0.13-0.14
0.14- 0.15
0.15-0.17
0.17-0.19
0.19-0.20
0.20-0.22
0.22-0.24
0.24-0.25
0.25- 0.27
0.27-0.29
0.29-0.32
0.32-0.35
0.35-0.38
0.38-0.41
0.41 - 0.45
0.45-0.51
0.51 - 0.59
0.59-0.75
0.75-5.32
Figure 2.1. Selenium in Surficial Soils and Aquatic Sediments in counties of the
Conterminous United States.
U.S. Geological Survey Open-File Report 2004-1001. URL:
http://mrdata.usgs.gov/geochem/doc/averages/countvdata.htm. Data are available from:
http://mrdata.usgs.gov/geochem/doc/groups-cats.htm.
Atmospheric emissions of selenium can originate from several sources including power
plants and other facilities that burn coal or oil, selenium refineries that provide selenium to
industrial users, base metal smelters and refineries, resource extraction industries, milling
operations, and end-product manufacturers (e.g., semiconductor manufacturers) (ATSDR 2003).
Airborne selenium particles can settle either on surface waters or on soils from which selenium
can be further transported and deposited into water bodies through ground or surface water
conveyances or runoff.
The chemical form of selenium that dominates a location is usually dependent on its
sources, effluent treatments, and biogeochemical processes in the receiving waters. Irrigation
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activities in areas with seleniferous soils typically mobilize selenate (SeC>4 , or Se[VI]) (Seiler et
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al. 2003). Combustion of coal for power generation creates predominantly selenite (SeCb , or
Se[IV|) in the fly ash waste due to the temperatures, pFI, and redox conditions involved with the
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process (Huggins et al. 2007). Similar conditions during refinement of crude oil can also result in
high concentrations of selenite relative to selenate, as was observed in the San Francisco Bay
estuary in the 1980s (Cutter 1989). Although selenite is the dominant species in the discharges
resulting from crude oil refining and coal burning using conventional technologies, the
implementation of alternative treatment technologies can alter the relative concentrations of
selenate and selenite. For example, in scrubbers with forced oxidation systems that produce
strong oxidizing conditions and high temperatures, the majority of discharged selenium is in the
form of selenate (Maher et al. 2010). However for flue gas desulfurization systems that are the
inhibited oxidation type, the selenium chemistry is more complex, and selenite may not be the
primary form emitted (Petrov et al. 2012). Table 2.1 shows the predominant form of selenium
that is associated with different activities and industries.
EPA's Office of Water and Office of Research and Development conducted the first
statistically based survey of contaminants in fish fillets from U.S. rivers from 2008 through
2009. This national fish survey was conducted under the framework of EPA's National Rivers
and Streams Assessment (NRSA), a probability-based survey designed to assess the condition of
the Nation's streams and rivers (Lazorchak et al. 2014). During June through October of 2008
and 2009, field teams applied consistent methods nationwide to collect samples of fish species
commonly consumed by humans at 541 randomly selected river locations (> 5th order based on
l:100,000-scale Strahler order) in the lower 48 states. They collected one composite fish sample
at every sampling location, with each composite consisting of five similarly sized adult fish of
the same species from a list of target species. Largemouth and smallmouth bass were the primary
species collected for the study, accounting for 34% and 24% of all fish composites, respectively.
Samples were collected from both non-urban (379 sites) and urban locations (162 sites). Each
fillet composite sample was homogenized and analyzed using an ICP-MS (Inductively Coupled
Plasma- Mass Spectrometry) method for total selenium, and results were reported as wet weight.
Three of the 541 samples (approximately 0.6%) exceeded the 2016 criterion for muscle tissue,
11.3 mg/kg dw. The maximum value detected was 17.75 mg Se/kg dw muscle, the median was
1.90 mg Se/kg dw, and the minimum 0.41 mg Se/kg dw.
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Table 2.1. Predominant Chemical Forms of Selenium in Discharges Associated with
Different Activities and Industries.
Selenium l-orm
Sources
Selenate
Agricultural irrigation drainage
Treated oil refinery effluent
Mountaintop coal mining/ valley fill leachate
Copper mining discharge
Selenite
Oil refinery effluent
Fly ash disposal effluent
Phosphate mining overburden leachate
Organoselenium
Treated agricultural drainage (in ponds or lagoons)
Source: Presser and Ohlendorf 1987; Zhang and Moore 1996; Cutter and Diego-McGlone 1990.
2.2 Environmental Fate and Transport of Selenium in the Aquatic
Environment
The fate and transport of selenium in aquatic systems is affected by the distribution of
selenium species and their transformations in water, sediment, and biota. These transformations
include the assimilation and conversion of inorganic selenium to organic selenium species in
plants and microbes that are transferred to higher trophic level consumer species throughout the
aquatic food web.
2.2.1 Selenium Species in Aquatic Systems
Aquatic organisms are exposed to a combination of predominantly organic selenium
species present in the food web throughout their life history; reproductive effects integrate these
exposures to transformed inorganic and organic species of selenium. The bioavailability and
toxicity of selenium depend on both its concentration and speciation (Cutter and Cutter 2004;
Meseck and Cutter 2006; Reidel et al. 1996). Selenium exists in four oxidation states (VI, IV, 0, -
II) and in a wide range of chemical and physical species across these oxidation states (Doblin et
al. 2006; Maher et al. 2010; Meseck and Cutter 2006). Therefore, in the effects assessment that
follows, we have correlated the adverse effects on aquatic life with total dissolved selenium.
In oxygenated surface waters, the primary dissolved selenium species are selenate
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(SeC>4 , or Se[VI]) and selenite (SeC>3 , or Se[IV]), as well as dissolved organic selenides (-II)
formed from fine particulate organic matter (e.g., Doblin et al. 2006; Meseck and Cutter 2006).
The relative abundance of selenate and selenite depends on relative contributions from the
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geologic and anthropogenic sources of selenium to the receiving waters, as there is negligible
inter-conversion between the two species (e.g., Maher et al. 2010). Aqueous selenite is more
abundant than selenate when the majority of selenium originates from discharges from coal fly
ash tailings or oil refineries (e.g., Cutter 1989; Huggins et al. 2007). Particulate species in the
water column include selenate, selenite, and elemental selenium (Se(0)) bound to resuspended
sediments and organic particles, as well as particulate organic selenium species incorporated into
suspended detritus (e.g., Cutter and Bruland 1984; Meseck and Cutter 2006).
In sediments, selenate and selenite can be reduced to iron selenides or elemental selenium
under abiotic or biotic processes; elemental selenium and selenides can be converted to selenate
under oxidizing conditions (Maher et al. 2010). For example, selenate can be reduced to
elemental selenium in sediments (e.g., Oremland 1990) in the presence of iron oxides (Chen et
al. 2008) and iron sulfides (Breynaert et al. 2008). Elemental selenium and organic selenides are
produced by selenate-reducing microbes in sediments. Overall, the reduction of selenate and
particularly selenite in sediments increases with increasing sediment organic matter (Tokunaga et
al. 1997). Selenite in particular is readily bound to iron and manganese oxy-hydroxides (Maher
et al. 2010), and is readily adsorbed to inorganic and organic particles, particularly at a lower pH
range (e.g., McLean and Bledsoe 1992; Tokungawa et al. 1997). Microbial reduction of selenite
to organic forms (via methylation) increases the solubility and bioavailability of selenium
(Simmons and Wallschlagel 2005). Plants and algae produce volatile selenium species by
biomethylation of excess selenium, which upon reaching the sediment can be transformed to a
more bioavailable species, or deposited in the sediments and effectively removed from the
system (Diaz et al. 2009). Depending on environmental conditions, the reduction processes
described above are largely reversible, as elemental selenium and selenides in sediments can be
oxidized to selenate through microbial or abiotic transformations (e.g., Maher et al. 2010;
Tokunaga et al. 1997).
The most important transformation of selenium, with respect to its toxicity to aquatic
organisms, is in the uptake of dissolved inorganic selenium into the tissues of primary producers
at the base of the food web. The main route of entry of selenium into aquatic foodwebs is from
the consumption of particulate selenium of primary producers, and to a lesser degree, from the
consumption of sediments (Doblin et al. 2006; Luoma and Presser 2009). For algae, selenite and
organic selenides are similarly bioavailable, and both dissolved species are more bioavailable
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than selenate (e.g., Baines et al. 2001; Luoma et al. 1992). In vascular plants, selenate uptake is
greater than for the other dissolved species, as the majority of selenium uptake occurs in the
roots, and selenate is more easily transported to the shoots and leaves than selenite or organic
selenides (Dumont 2006). Following uptake, selenium is metabolized into a variety of organic
species that are assimilated into plant tissues. Selenium metabolism in plants is analogous to
sulfur metabolism (e.g., Dumont et al. 2006; Ouerdane et al. 2013). Selenate is reduced to
selenite, which is then reduced to selenide in a process involving reduced glutathione (Dumont et
al. 2006). Selenide is converted to selenocysteine (SeCys), which is then converted to
selenomethionine (SeMet) (Dumont et al. 2006). In addition to SeCys and SeMet, a variety of
other organic selenium species can be formed; however, SeCys, and particularly SeMet are
toxicologically important because these amino acids nonspecifically replace cysteine and
methionine in proteins, and are more bioavailable to higher trophic level consumers (Fan et al.
2002; Freeman et al. 2006).
2.2.2 Bioaccumulation of Selenium in Aquatic Systems
Dissolved selenium uptake by animals is slow, whatever the form, such that under
environmentally relevant conditions, dissolved selenium in the water column makes little or no
direct contribution to bioaccumulation in animals (Lemly 1985a; Ogle and Knight 1996), but
does influence the concentration of selenium in particulate matter. Selenium bioaccumulation in
aquatic organisms occurs primarily through the ingestion of food (Fan et al. 2002; Luoma et al.
1992; Maher et al. 2010; Ohlendorf et al. 1986; Presser and Ohlendorf 1987; Presser et al. 1994;
Saiki and Lowe 1987). However, unlike other bioaccumulative contaminants such as mercury,
the single largest step in selenium accumulation in aquatic environments occurs at the base of the
food web where algae and other microorganisms accumulate selenium from water by factors
ranging from several hundred to tens of thousands (Luoma and Presser 2009; Orr et al. 2012;
Stewart et al. 2010). Bioaccumulation and transfer through aquatic food webs are the major
biogeochemical pathways of selenium in aquatic ecosystems. Dissolved selenium oxyanions
(selenate, selenite) and organic selenides are assimilated into the tissues of aquatic primary
producers (trophic level 1 organisms), such as periphyton, phytoplankton, and vascular
macrophytes; and subsequently biotransformed into organoselenium. These organisms, together
with other particle-bound selenium sources, constitute the particulate selenium fraction in the
water column. Selenium from this particulate fraction is then transferred to aquatic primary
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consumers such as zooplankton, insect larvae, larval fish, and bivalves (trophic level 2), and then
to predators such as fish and birds (trophic level 3 and above). In addition to the water
concentration of selenium, the process of selenium bioaccumulation in aquatic life residing in
freshwater systems depends on several factors specific to each aquatic system. These factors
include:
Water residence time. Residence time is a measure of the average time a water molecule
will spend in a specified region of space. Residence time influences both the proportion of
selenium found in particulate and dissolved forms and the predominant form of selenium.
Organisms in waters with long residence times such as lakes, ponds, reservoirs, wetlands or
estuaries will tend to bioaccumulate more selenium than those living in waters with shorter
residence times such as rivers and streams (ATSDR 2003; EPRI2006; Luoma and Rainbow
2005; Orr et al. 2006; Simmons and Wallschlagel 2005). Several interrelated factors underlie
selenium's greater bioaccumulation potential in slow moving systems, such as food web
complexity and the organic content and reduction/oxidation potential of sediments. Finally,
selenium toxicity in flowing waters with shorter residence times may only be apparent
downstream of their selenium sources, whereas waters with longer residence times are more
likely to exhibit selenium toxicity near their sources (Presser and Luoma 2006).
Distribution of selenium between particulate and dissolvedforms. Selenium is found in
both particulate and dissolved forms in water, but direct transfer of selenium from water to
animals is only a small proportion of the total exposure. The proportion of selenium found in
particulate matter (algae, detritus, and sediment) is important because it is the primary avenue for
selenium entering into the aquatic food web (Luoma et al. 1992; Luoma and Rainbow 2005;
Ohlendorf et al. 1986; Presser and Ohlendorf 1987; Presser et al. 1994; Presser and Luoma 2006;
Saiki and Lowe 1987).
Bioaccumulation in prey. Trophic level 1 organisms such as periphyton and
phytoplankton, as well as other forms of particulate material containing selenium, such as
detritus and sediment, are ingested by trophic level 2 organisms such as mollusks, planktonic
crustaceans, and many insects, increasing the concentration of selenium in the tissues of these
higher-level organisms. Differences in the physiological characteristics of these organisms result
in different levels of bioaccumulation. Also, selenium effects on invertebrates typically occur at
concentrations higher than those that elicit effects on the vertebrates (e.g., fish and birds) that
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prey upon them. Additionally, certain molluscan taxa such as mussels and clams can accumulate
selenium to a much greater extent than planktonic crustaceans and insects (although the levels do
not seem to be toxic to the mussels) due to higher ingestion rates of both particulate-bound
(algae) and dissolved selenium from the water column through filter feeding, as well as the lower
rate at which they eliminate selenium (Luoma and Rainbow 2005; Stewart et al. 2013). Because
egg-laying (oviparous) vertebrates such as fish and birds are most sensitive to selenium effects,
(Janz et al. 2010), these vertebrate consumers are also the most vulnerable groups to selenium
poisoning and the focal point of most selenium environmental assessments (Ogle and Knight
1996; Stewart et al. 2010).
Trophic transfer to predators. Bioaccumulation of selenium by higher trophic level
organisms, such as trophic level 3 and 4 fish, is highly influenced by the food web of the aquatic
environment. For example, fish that primarily consume freshwater mollusks (e.g., redear sunfish)
will exhibit greater selenium bioaccumulation than fish that consume primarily insects or
crustaceans from waters with the same concentration of dissolved selenium because mollusks
tend to accumulate selenium at higher concentrations than other trophic level 2 organisms, as
noted above (Luoma and Presser 2009; Stewart et al. 2004).
2.3 Mode of Action and Toxicity of Selenium
Selenium is a naturally occurring chemical element that is also an essential micronutrient.
Trace amounts of selenium are required for normal cellular function in almost all animals.
However, excessive amounts of selenium can also have toxic effects, with selenium being one of
the most toxic of the biologically essential elements (Chapman et al. 2010). Egg-laying
vertebrates have a lower tolerance than do mammals, and the transition from levels of selenium
that are biologically essential to those that are toxic occurs across a relatively narrow range of
exposure concentrations (Luckey and Venugopal 1977; U.S. EPA 1987, 1998; Haygarth 1994;
Chapman et al. 2009, 2010). Selenium consumed in the diet of adult female fish is deposited in
the eggs, when selenium replaces sulfur in vitellogenin, which is transported to the ovary and
incorporated into the developing ovarian follicle (Janz et al. 2010), the primary yolk precursor.
Selenium is a member of the sulfur group of nonmetallic elements, and consequently, the
two chemicals share similar characteristics. Selenium can replace sulfur in two amino acids, the
seleno-forms being selenomethionine and selenocysteine. It has been a long-standing hypothesis
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that the cause of malformations in egg-laying vertebrates is due to the substitution of selenium
for sulfur in these amino acids and their subsequent incorporation into proteins, which causes
disruption of the structure and function of the protein. When present in excessive amounts,
selenium is erroneously substituted for sulfur, resulting in the formation of a triselenium linkage
(Se-Se-Se) or a selenotrisulfide linkage (S-Se-S), either of which was thought to prevent the
formation of the normal disulfide chemical bonds (S-S). The end result was thought to be
distorted, dysfunctional enzymes and protein molecules that impaired normal cellular
biochemistry (Diplock and Hoekstra 1976; Reddy and Massaro 1983; Sunde 1984).
Recent research, however, suggests that selenium's role in oxidative stress plays a role in
embryo toxicity, whereas selenium substitution for sulfur does not. The substitution of
selenomethionine for methionine does not appear to affect either the structure or function of
proteins (Yuan et al. 1998; Mechaly et al. 2000; Egerer-Sieber et al. 2006). The reason is
apparently due to selenium not being distally located in selenomethionine, which insulates the
protein from an effect on its tertiary structure. Although the incorporation of selenomethionine
into proteins is concentration-dependent (Schrauzer 2000), selenocysteine's incorporation into
proteins is not (Stadtman 1996). This suggests that neither selenomethionine nor selenocysteine
affect protein structure or function. In fact, Se as an essential micronutrient is incorporated into
functional and structural proteins as selenocysteine.
The role of selenium-induced oxidative stress in embryo toxicity and teratogenesis
appears to be related to glutathione homeostasis. A review of bird studies by Hoffman (2002)
showed exposure to selenium altered concentrations and ratios of reduced to oxidized glutathione
thereby increasing measurements of oxidative cell damage. Palace et al. (2004) suggested
oxidative stress due to elevated selenium levels results in pericardial and yolk sac edema in
rainbow trout embryos. Evidence for the role of oxidative stress in selenium toxicity is growing,
but mechanistic studies are needed to better understand its effects on egg-laying vertebrates. For
a more in depth discussion on the mechanism of toxicity at the cellular level including the
evidence against sulfur substitution as a cause and the role of oxidative stress, see Janz et al.
(2010).
The most well-documented, overt and severe toxic symptoms in fish are reproductive
teratogenesis and larval mortality. Egg-laying vertebrates appear to be the most sensitive taxa,
with toxicity resulting from maternal transfer to eggs. In studies involving young organisms
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exposed through transfer of selenium from adult female fish into their eggs, the most sensitive
diagnostic indicators of selenium toxicity in vertebrates occur when developing embryos
metabolize organic selenium that is present in egg albumen or yolk. It is then further metabolized
by larval fish after hatching.
A variety of lethal and sublethal deformities can occur in the developing fish exposed to
selenium, affecting both hard and soft tissues (Lemly 1993b). Developmental malformations are
among the most conspicuous and diagnostic symptoms of chronic selenium poisoning in fish.
Terata are permanent biomarkers of toxicity, and have been used to identify impacts of selenium
on fish populations (Maier and Knightl994; Lemly 1997b). Deformities in fish that affect
feeding or respiration can be lethal shortly after hatching. Terata that are not directly lethal, but
distort the spine and fins, can reduce swimming ability, and overall fitness. Because the rate of
survival of deformed young would be less than that for normal young, the percentage of
deformed adults observed during biosurveys will likely understate the underlying percentage of
deformed young, although quantitation of the difference is ordinarily not possible.
In summary, the most sensitive indicators of selenium toxicity in fish larvae are effects
modulated through the reproductive process and exhibited in fish larvae as teratogenic
deformities such as skeletal, craniofacial, and fin deformities, and various forms of edema that
result in mortality (Lemly 2002). The toxic effect generally evaluated is the reduction in the
number of normal healthy offspring compared to the starting number of eggs. In studies of young
organisms exposed to selenium solely through their own diet (rather than via maternal transfer),
reductions in survival and/or growth are the effects that are generally evaluated.
2.4 Narrow Margin between Sufficiency and Toxicity of Selenium
Selenium has a narrow range encompassing what is beneficial for biota and what is
detrimental. Selenium is an essential nutrient that is incorporated into functional and structural
proteins as selenocysteine and selenomethionine. Several of these proteins are enzymes that
provide cellular antioxidant protection. Selenomethionine is readily oxidized, and its antioxidant
activity arises from its ability to deplete reactive oxygen species. Selenomethionine is required as
a mineral cofactor in the biosynthesis of glutathione peroxidases. All of the classic glutathione
peroxidases contain selenium and are found to be involved in the catalytic reaction of these many
enzymes (Allan 1999). The major function of the glutathione peroxidases involves the reduction
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of hydrogen peroxide to water at the expense of the oxidation of glutathione, the enzyme's
cofactor, an important antioxidant process at normal dietary levels.
Aquatic and terrestrial organisms require low levels of selenium in their diet to sustain
metabolic processes, whereas excess concentrations of selenium that are only an order of
magnitude greater than the required level have been shown to be toxic to fish, apparently due to
generation of reactive oxidized species, resulting in oxidative stress (Palace et.al. 2004). Dietary
requirements in fish have been reported to range from 0.05 to 1.0 mg Se/kg dw (Watanabe et al.
1997). Selenium requirements for optimum growth and liver glutathione peroxidase activity in
channel catfish were reported as 0.25 mg Se/kg dw (Gatlin and Wilson 1984). Estimated
selenium dietary requirements in hybrids of striped bass, based on selenium retention, were
reported as 0.1 mg Se/kg dw (Jaramillo 2006). Selenium deficiency has been found to affect
humans (U.S. EPA 1987), sheep and cattle (U.S. EPA 1987), deer (Oliver et al. 1990), fish
(Thorarinsson et al. 1994; Wang and Lovell 1997; Wilson et al. 1997; U.S. EPA 1987), aquatic
invertebrates (Audas et al. 1995; Caffrey 1989; Cooney et al. 1992; Cowgill 1987; Cowgill and
Milazzo 1989; Elendt 1990; Elendt and Bais 1990; Harrison et al. 1988; Hyne et al. 1993;
Keating and Caffrey 1989; Larsen and Bjerregaard 1995; Lim and Akiyama 1995; Lindstrom
1991; U.S. EPA 1987; Winner 1989; Winner and Whitford 1987), and algae (Doucette et al.
1987; Keller et al. 1987; Price 1987; Price et al. 1987; Thompson and Hosja 1996; U.S. EPA
1987; Wehr and Brown 1985). The predominance of research on selenium deficiency in
invertebrates and algae is related to optimizing the health of test organisms cultured in the
laboratory. A summary of several studies that evaluated the deficiency and/or the sufficiency of
selenium in the diet of fish is provided in Appendix E.
2.5 Interactions with Mercury
The most well-known interactions with selenium occur with both inorganic and organic
mercury, and are generally antagonistic (Micallef and Tyler 1987; Cuvin and Furness 1988;
Paulsson and Lundbergh 1991; Siegel et al. 1991; Southworth et al. 1994; Ralston et al. 2006),
with the most likely mechanism being the formation of metabolically inert mercury selenides
(Ralston et al. 2006; Peterson et al. 2009). However, other studies have found interactions
between mercury and selenium to be additive (Heinz and Hoffman 1998) or synergistic
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(Huckabee and Griffith 1974; Birge et al. 1979). The underlying mechanism for these additive
and synergistic interactions between mercury and selenium are unknown.
2.6 Assessment Endpoints
Assessment endpoints are defined as "explicit expressions of the actual environmental
value that is to be protected" and are defined by an ecological entity (species, community, or
other entity) and its attribute or characteristics (U.S. EPA 1998). Assessment endpoints may be
identified at any level of organization (e.g., individual, population, community). In the context of
the Clean Water Act, aquatic life criteria for toxic pollutants are typically determined based on
the results of toxicity tests with aquatic organisms in which unacceptable effects on growth,
reproduction, or survival occurred. The goal of criteria is to protect the diversity, productivity,
and stability of aquatic communities. To achieve this goal, the endpoint of criteria assessment is
the survival, growth, and reproduction of a high percentage of species of a diverse assemblage of
freshwater aquatic animals (fish, amphibians, and invertebrates) and plants. Toxicity data are
aggregated into a sensitivity distribution that indicates the impact of the toxicant under study to a
variety of genera representing the broader aquatic community. Criteria are designed to be
protective of the vast majority of aquatic animal species in an aquatic community (i.e.,
approximately 95th percentile of tested aquatic animals representing the aquatic community). As
a result, health of the aquatic community may be considered as an assessment endpoint indicated
by survival, growth, and reproduction. Assessment endpoints are the ultimate focus in risk
characterization and link the measurement endpoints to the risk management process (e.g., policy
goals). When an assessment endpoint can be directly measured, the measurement and assessment
endpoints are the same. In most cases, however, the assessment endpoint cannot be directly
measured, so a measurement endpoint (or a suite of measurement endpoints) is selected that can
be related, either qualitatively or quantitatively, to the assessment endpoint. For example, a
decline in a sport fish population (the assessment endpoint) may be evaluated using laboratory
studies on the mortality of surrogate species, such as the fathead minnow (the measurement
endpoint) (EPA/630/R-92/001 February 1992). The assessment endpoint for selenium is the
protection of freshwater aquatic life; because we know that fish are the most sensitive aquatic
taxon to the toxicological effect of selenium, the criterion is expressed in terms of fish tissue
using eggs and ovarian tissue as the most representative element related to selenium toxicity.
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To assess potential effects on the aquatic ecosystem by a particular stressor, and develop
304(a) aquatic life criteria under the CWA, EPA typically requires the following, as outlined in
the EPA Ambient Water Quality Criteria Guidelines: acute toxicity test data (mortality,
immobility, loss of equilibrium) for aquatic animals from a minimum of eight diverse taxonomic
groups; as well as chronic toxicity data (e.g., survival, growth and reproduction) for aquatic
animals from 8 eight taxonomic groups (described in more detail below). The diversity of tested
species is intended to ensure protection of various components of an aquatic ecosystem. In the
case of bioaccumulative compounds like selenium, these acute toxicity studies do not address
risks that result from exposure to chemicals via the diet (through the food web). They also do not
account for the slow accumulation kinetics of many bioaccumulative compounds such as
selenium and may underestimate effects from long-term accumulation in different types of
aquatic systems (SAB 2005).
Because the most sensitive adverse effects of selenium are reproductive effects (larval
deformities and mortality) on the offspring of exposed fish, chronic effects from long term
exposure are the focus of this selenium assessment. In addition to continuous discharges, shorter-
term intermittent or pulsed exposures to elevated levels of selenium may also result in
bioaccumulation through the aquatic food web and may subsequently adversely affect fish
reproduction, and such measures of effect are therefore also estimated from chronic assessment
endpoints. Selenium toxicity in the water body could potentially threaten fecundity and
recruitment in fishes, resulting in extirpation of sensitive species in a waterbody, and potentially
shifting the trophic dynamics of the system. Therefore, the assessment endpoint for selenium is
the protection of fish populations. In some waters where ESA-listed fish species occur, a
protection goal oriented to protection of individuals may be more appropriate. This should be
reflected using site-specific data to derive an SSC for the site.
Chronic toxicity test data (longer-term survival, growth, or reproduction) for aquatic
animals are needed from a minimum of eight diverse taxonomic groups (or less generically,
[minimum of three taxa] if the derivation is based on an acute to chronic ratio). The diversity of
tested species is intended to ensure protection of various components of an aquatic ecosystem.
Specific minimum data recommendations or requirements (MDRs) identified for development of
criteria in the EPA Ambient Water Quality Criteria Guidelines require aquatic animal toxicity
data from:
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1. the family Salmonidae in the class Osteichthyes,
2. a second family in the class Osteichthyes, preferably a commercially or
recreationally important warmwater species (e.g., bluegill, channel catfish, etc.),
3. a third family in the phylum Chordata (may be in the class Osteichthyes or may
be an amphibian, etc.),
4. a planktonic crustacean (e.g., cladoceran, copepod, etc.),
5. a benthic crustacean (e.g., ostracod, isopod, amphipod, crayfish, etc.),
6. an insect (e.g., mayfly, dragonfly, damselfly, stonefly, caddisfly, mosquito,
midge, etc.),
7. a family in a phylum other than Arthropoda or Chordata (e.g., Rotifera,
Annelida, Mollusca, etc.), and
8. a family in any order of insect or any phylum not already represented.
Acceptable quantitative chronic values for selenium are available for six of the eight
MDRs (requirements 1, 2, 3, 6, 7, and 8). Acceptable chronic values for selenium are not
available for two of the MDRs (requirements 4 and 5: planktonic and benthic crustaceans,
respectively). Following the approach of U.S. EPA (2008b), which was reviewed by the Science
Advisory Board, if information is available to demonstrate that an MDR is not sensitive, then a
surrogate value can be used in place of actual toxicity data to represent the missing MDR. Based
on the data estimating the sensitivity of insects (Centroptilum triangulifer), rotifers (Brachionus
calyciflorus), and oligochaetes (Lumbriculus variegatus), EPA determined that invertebrates
(e.g., insects and crustaceans) are generally less sensitive to selenium than fish, based on the
characteristics of selenium toxicity to aquatic life. Therefore, the available fish data were used in
the genus-level sensitivity distribution to derive the chronic selenium criterion (Note:
invertebrate data were included in the sensitivity distribution for the whole body criterion
element to demonstrate that the derivation of the criterion element based on the fish egg-ovary to
whole body translated values protected invertebrates given the sensitivity range of the available
species).
The EPA Ambient Water Quality Criteria Guidelines also require at least one acceptable
test with a freshwater alga or vascular plant. If plants are among the aquatic organisms most
sensitive to the stressor, results of a plant in another phylum should also be available. A
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relatively large number of tests from acceptable studies of aquatic plants were available for
possible derivation of a Final Plant Value. However, the relative sensitivity of freshwater plants
to selenium (Appendix F) is less than fish, so plant criterion elements were not developed.
The available scientific evidence indicates that for selenium, critical assessment
endpoints for aquatic species are offspring mortality and severe development abnormalities that
affect the ability of fish to swim, feed and successfully avoid predation, resulting in impaired
recruitment of individuals into fish populations. Selenium enrichment of reservoir environments
(e.g., Belews Lake, NC (Lemly 1985), Hyco Reservoir (DeForest 1999), and Kesterson
Reservoir, CA (Ohlendorf 1986)) are well documented and demonstrate that adverse effects
resulted from bioaccumulative processes at different levels of biological organization, resulting
in population-level reductions of resident species.
2.7 Measures of Effect
Each assessment endpoint requires one or more "measures of ecological effect", which
are defined as changes in the attributes of an assessment endpoint itself or changes in a surrogate
entity or attribute in response to chemical exposure. Ecological effects data are used as measures
of direct and indirect effects to growth, reproduction, and survival of aquatic organisms.
The toxicity testing data available for any given pollutant vary significantly, depending
primarily on whether any major environmental issues are raised. An in-depth evaluation of
available data for selenium has been performed by EPA to determine data acceptability and
quality, based on criteria established in the EPA Ambient Water Quality Criteria Guidelines.
In traditional chronic tests used in many EPA aquatic life criteria documents, organisms
are exposed to contaminated water but fed a diet grown in uncontaminated media not spiked with
the toxicant prior to introduction into the exposure chambers. Such tests are not suitable for
deriving a criterion for a bioaccumulative pollutant unless (1) effects are linked to concentrations
measured in appropriate tissues, and (2) the route of exposure does not affect the potency of
residues in tissue. For selenium, the first condition might be met, but the second condition is not,
because the route of selenium exposure appears to influence the potency of a given tissue residue
(Cleveland et al. 1993; Gissel-Nielsen and Gissel-Nielsen 1978). Consequently, toxicity tests
with water-only exposures (and any tests not relying on dietary exposure) are not included in this
assessment.
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Selenium toxicity is primarily manifested as reproductive impairment due to maternal
transfer, resulting in embryo mortality and teratogenicity. Measurements of selenium in fish
tissue are most closely linked to the chronic adverse effects of selenium (Chapman et al. 2010),
since chronic selenium toxicity is based on the food-chain bioaccumulation route, not a direct
waterborne route. In this selenium criterion document, water column criterion element
concentrations for selenium were derived from fish tissue concentrations by modeling selenium
transfer through the food web. The next sections describe approaches used to establish selenium
effects concentrations in fish tissue and to relate the concentrations in fish tissue to
concentrations in water.
2.7.1 Fish Tissue
Chronic measures of effect concentrations are the ECio, EC20. No Observed Effect
Concentration (NOEC), Lowest Observed Effect Concentration (LOEC), and Maximum
Acceptable Toxicant Concentration (MATC). The EC10 is the concentration of a chemical that is
estimated to result in a 10 percent effect in a measured chronic endpoint (e.g., growth,
reproduction, or survival); the EC20 corresponds to 20 percent effect. The NOEC is the highest
chemical concentration at which none of the observed effects are statistically different from the
control, as determined by hypothesis testing. The LOEC is the lowest test concentration at which
observed effects are found to be statistically different from the control. For selenium, in all cases
the effect endpoint used in the estimation of chronic values (e.g., ECios) is an effect on offspring
(with exposure via maternal transfer) from parents exposed to selenium via diet.
Selenomethionine was used exclusively in dietary exposures in the lab, whereas field-exposed
females would be exposed to a combination of forms of selenium as a function of the selenium in
their prey items.
Whenever possible, estimates of selenium concentrations associated with a low level of
effect (i.e., EC10) were calculated for each study using the computer program TRAP (version
1.30a), Toxicity Relationship Analysis Program (U.S. EPA 2013). The program is based on a
regression approach that models the level of adverse effects as a function of increasing
concentrations of the toxic substance. With the fitted model it is possible to estimate the
contaminant concentration associated with a small effect. TRAP was used when there are
sufficient data for EC10 estimation. For studies with binary data, the analysis proceeded by
tolerance distribution analyses using the log-triangular distribution, unless there was substantial
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extrabinomial variability, in which case regression analysis was used. For regression analysis,
the threshold sigmoidal model was used, exposure variables were log-transformed, and effects
variables were weighted appropriately to address their relative uncertainties.
When there were insufficient data for TRAP to fit an effects/exposure curve (no
treatments with clear effects near the ECio and/or significant background variability), the ECio
was based on interpolation. To ensure that the interpolations were comparable to the TRAP
analyses, threshold sigmoidal equation was used. This equation is fitted to two points, and
constrained so that 3 equation parameters can be set. The first set-point was treated as the ECo
with a second associated set-point being the threshold for background effects values, based on
the highest NOEC (HNOEC) datum and other NOEC data. The final set-point was the LOEC. If
the LOEC is a partial effect, then this point was used to estimate the equation slope. If the LOEC
was a 100% effect, it was specified as the ECioo; with the ECo specified, then this relationship
dictated the equation slope. It should be noted that despite the superficial resemblance of these
analyses to TRAP they are also subject to the uncertainties associated with the interpolation
method.
It should be noted that TRAP involves the assumption that (a) there is a single underlying
relationship of the effects variable to the exposure variable which follows the specified equation
and (b) the exposure variable is known with negligible error, with uncertainty being
predominantly in the effects variable. Some of the reproductive data for selenium involved
multiple sources of variability that led to both multiple relationships across different cohorts of
offspring and uncertainty in the exposure variable, so that the resulting TRAP curves were more
approximate, and TRAP error estimates were generally not useful. These issues can also affect
the interpolation protocol. It should also be noted that estimating a concentration associated with
a low effects level, such as an ECio, is especially uncertain when treatments yielding partial
effects values are lacking in the concentration response data produced by a study. These two
issues prevented the use of TRAP in some datasets. When the data are insufficient to provide any
meaningful ECio by the first two approaches, the study should either not be used for criteria
development or a chronic value should be set by other means than an estimated ECio if possible.
Only studies with a reference site (field surveys) or control treatment(s) (experimental
studies) were included in the analysis, because response levels at these low selenium
concentrations were the most influential points for calculating the estimated response level at a
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selenium concentration of zero (yo). When considering the use of the ECio versus the EC20, an
EC10 was determined to be a more appropriate endpoint for tissue-based criteria given the nature
of exposure and effects for this bioaccumulative chemical. EC20s have historically been used in
the derivation of EPA criteria applicable to the water medium. While water concentrations may
vary rapidly over time, tissue concentrations of bioaccumulative chemicals are expected to vary
gradually over time. Thus, where concentrations of selenium in fish tissue are used as an effect
threshold, there is potential for sustained impacts on aquatic systems, relative to chemicals that
are not as bioaccumulative. Furthermore, it was found that the dose-response curves for selenium
across a broad range of fish genera are very steep, such that a small change in selenium tissue
concentration yielded a large increase in observed adverse effect. In many cases, the selenium
data indicated a change from control effect levels to effects in excess of 50% for larval mortality
or deformity over a few mg/kg dry weight increase in selenium detected in fish tissue. These
issues call for use of a lower level of effect to attain sufficient protection. The EC10 was also
preferred over the NOEC or LOEC as these measures of effect are influenced by study design,
specifically the concentrations tested, the number of concentrations tested, the number of
replicates for each concentration, and the number of organisms in each replicate. As noted by
Campbell (2011), EC10S and NOECs are generally of similar magnitude, but EC10S have the
advantage of being more reproducible than NOECs (Van der Hoeven et al. 1997; Warne and van
Dam 2008). NOECs and MATCs are generally presented if calculated by the original
investigators, but were not used where an EC10 could be calculated. The four lowest egg-ovary
Genus Mean Chronic Values (GMCVs), whose exact values influence the calculation of the egg-
ovary criterion element, are all based solely on EC10S. NOECs contribute to some of the GMCVs
for less sensitive species.
In this document, chronic values are presented as tissue concentrations of total selenium
in units of mg/kg dry weight (dw). Studies of chronic toxicity of selenium to aquatic organisms
measure concentrations in distinct tissues (e.g., whole body, ovaries, eggs, muscle, and liver) and
report these values as either wet weight (ww) or dw. Studies reporting tissue concentrations only
based on wet weight were converted to dry weight using tissue-specific and species-specific
conversion factors. When wet to dry weight conversion factors were not available for a given
species, conversion factors for a closely related taxon were used. In deriving the egg or ovary
tissue criterion element, chronic values are for those tissues directly measured in the study.
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Tissue-to-tissue conversions (e.g., to estimate concentrations in an unmeasured tissue from a
study's measured tissue) involve some uncertainty because of variability in tissue concentration
ratios (deBruyn et al. 2008; Osmudson et al. 2007). Tissue-to-tissue conversions were needed for
calculating the reproductive toxicity-based whole-body and muscle chronic criterion element and
water criterion concentration elements.
The overall assessment evaluates both reproductive and non-reproductive studies.
Selenium concentrations measured directly in eggs or ovaries from reproductive (maternal
transfer) studies are used to derive the egg/ovary criterion element, and corresponding selenium
concentrations in whole body or muscle tissue resulting in reproductive effects are estimated
using conversion factors. Direct measurements of selenium concentrations in whole-body or
muscle from non-reproductive studies are used to examine non-reproductive, chronic effects,
such as impairments to growth.
2.7.2 Water
While state monitoring programs may sample ambient waters for selenium, widespread
measurements of selenium in fish tissue are relatively rare. Therefore, EPA is providing
estimated chronic measures of effect for water column data. The chronic criterion element for the
water column is the 30-day average concentration that corresponds to the concentration of
selenium in fish tissue estimated to result in a 10 percent effect in fish for a specific water body
type (lotic or lentic water bodies as described below in Section 3.2.4), The chronic criterion
element for the water column is derived by modeling trophic transfer of selenium through the
food web resulting in the fish tissue concentration that yields the chronic reproductive effects of
concern.
EPA collaborated with the United States Geological Survey (USGS) to develop a model
(later published in Presser and Luoma 2010) that relates the concentration of selenium in fish
tissue to the water column. The approach is based on bioaccumulation and trophic transfer
through aquatic system food-webs. Model parameters are calculated using both field and
laboratory measurements of selenium in water, particulate material (algae, detritus and
sediment), invertebrates, fish whole-body, and fish egg-ovary. Although EPA and USGS use the
same model to relate the concentration of selenium in fish tissue to water, EPA starts with
selenium in the egg/ovary (reproductive criterion) whereas USGS starts with selenium in the
fish's whole body. The EPA approach therefore has the additional step of converting the
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concentration of selenium in the egg/ovary to whole body. This model (which is a set of
equations) is described in more detail in Section 3.2.1,
2.7.3 Summary of Assessment Endpoints and Measures of Effect
The typical assessment endpoints for aquatic life criteria are based on effects on growth,
reproduction, or survival of the assessed taxa. These measures of effect on toxicological
endpoints of consequence to populations are provided by results from toxicity tests with aquatic
plants and animals. The toxicity values (i.e., measures of effect expressed as genus means) are
used in the genus sensitivity distribution of the aquatic community to derive the aquatic life
criteria. Endpoints used in this assessment are listed in Table 2.2.
Table 2.2. Summary of Assessment Endpoints and Measures of Effect Used in Criterion
Derivation for Selenium.
Assessment Kndpoinls for (lie Aquatic
(ommunilY
Measures of KITecl
Survival, growth, and reproduction of
freshwater fish, other freshwater vertebrates,
and invertebrates
For effects from chronic exposure:
1. ECio concentrations in egg and ovary, for
offspring mortality and deformity.
2. Measured or estimated reproductive ECio
in whole body and muscle.
3. Estimated concentrations (|ig/L) in water
linked to egg-ovary ECios by food web-
modeling.
4. Intermittent water concentrations yielding
exposure equivalent to the above.
For acutely lethal effects:
Acute toxicity effects based on standard
water column-only toxicity testing are not
provided here for selenium, due to the
dominant significance of chronic effects.
Note: Chronic criterion is expected to be
protective of acute effects.
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2.7.4 Conceptual Model of Selenium Effects on Aquatic Life
Reproductive Impairment.
Larval skeletal deformities.
Larval mortality.
Tertiary Trophic Transfer from
lower trophic level fish
To higher trophic level fish
Secondary Trophic Transfer from
macroinvertebrates/
icthyoplankton/ other zooplankton
Initial Trophic Transfer
from phytoplankton, periphyton, macrophytes, detritus, & sediment
Selenium in Water Column
Selenium Sources
Naturally elevated selenium in soils - agricultural irrigation practices (Western US only)
Mining activities - coal, metals and sulfide minerals, phosphate
Algal/Plant Transformation and Enrichment:
¦ As function of sorption to particulates (sediment, algae, detritus)
As function of system hydrodynamics, lotic & lentic systems, residence time
¦
¦
I
Population decline
Figure 2.2. Diagram of Selenium Partitioning, Bioaccumulation, and Effects in the Aquatic
Environment.
The conceptual model links sources, transformation and uptake through media phases,
and consumer transfer and dynamics reflective of the movement of selenium through ecosystems
(Figure 2.2). Diet is the dominant pathway of selenium exposure for both invertebrates and
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vertebrates. Selenium moves from water to particulates, a collection of biotic and abiotic
compartments that includes primary producers, detritus, and sediments, which form the base of
aquatic food webs. Transfer from particulates to primary consumers (e.g., macroinvertebrates) to
fish is species specific. Knowledge of the food web is one of the keys to determining which
biological species or other ecological characteristics will be affected.
During the development of CWA section 304(a) criteria, EPA assembles all available test
data and considers all the relevant data that meet acceptable data quality and test acceptability
standards. This criterion update document is specific to selenium in fresh water. Chronic
criterion elements for selenium are protective concentrations measured in fish tissue and related
to protective water concentrations generated using food-web modeling. Further modeling is used
to estimate short-term concentrations in water from intermittent or pulsed exposures that are
protective against the chronic effect.
2.7.5 Analysis Plan for Derivation of the Chronic Fish Tissue-Based Criterion Elements
Data for possible inclusion in the selenium dataset were obtained primarily by search of
published literature using EPA's public ECOTOX database (up to July 2013). These studies were
screened for data quality as described in the EPA Ambient Water Quality Criteria Guidelines,
and adjusted for factors related to dietary lab or field exposure, which were not considered at the
time the Guidelines were written. Additional data were considered and reviewed for inclusion in
this criterion based on the public and peer review comments on the 2014 "External Peer Review
Draft" criterion document, and public comments on the 2015 draft.
Chronic toxicity studies (both laboratory and field studies) were further screened to
ensure they contained the relevant chronic exposure conditions of selenium to aquatic organisms
(i.e., dietary, or dietary and waterborne selenium exposure), measurement of chronic effects, and
measurement of selenium in tissue(s). The criterion derivation uses only those studies in which
test organisms were exposed to selenium in their diet, because such studies most closely replicate
real-world exposures (diet and/or diet plus water). This approach accords with findings and
recommendations of the 2009 SETAC Pellston Workshop (Chapman et al. 2009, 2010).
EPA grouped studies based on whether the effects were chronic reproductive (e.g.,
effects on offspring survival or morphology) or chronic non-reproductive (e.g., juvenile growth
and survival). At the 2009 Pellston workshop (Chapman et al. 2009, 2010), a group of 46 experts
in the area of ecological assessment of selenium in the aquatic environment agreed that the most
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important toxicological effects of selenium in fish arise following maternal transfer of selenium
to eggs during vitellogenesis, resulting in selenium exposure when hatched larvae undergo yolk
absorption. Such effects include larval mortality or permanent developmental malformations,
such as skeletal and craniofacial deformities. Therefore, the chronic fish-tissue-based criterion
elements are based on reproductive effects only.
The egg-ovary Species Mean Chronic Values (SMCVs) were calculated from the chronic
values (ECios and occasionally NOECs) obtained from the relevant toxicity tests. Genus Mean
Chronic Values (GMCVs) were calculated from the SMCVs and then rank-ordered from least to
most sensitive. The four lowest egg-ovary Genus Mean Chronic Values (GMCVs), whose exact
values influence the calculation of the egg-ovary criterion element, are all based solely on ECios.
The egg-ovary Final Chronic Value (FCV) was calculated from regression analysis of the four
most sensitive GMCVs, in this case extrapolating to the 5th percentile of the distribution
represented by the tested genera. The FCV directly serves as the fish tissue egg-ovary criterion
concentration element without further adjustment because the underlying ECios represent a low
level of effect (per the EPA Ambient Water Quality Criteria Guidelines).
For the whole-body and muscle criterion element concentrations, CVs were either
measured directly using the relevant tissue or the egg-ovary CVs were converted to estimated
equivalent whole-body or muscle CVs. The criterion concentration element expressed as whole-
body or as muscle concentration was calculated in a manner similar to the egg-ovary criterion
element using a combination of directly calculated CVs or CVs that used conversion factors
described below.
2.7.6 Analysis Plan for Derivation of the Fish Tissue Criterion Elements Duration
Duration of the averaging periods in national criteria restrict allowable fluctuations in the
concentration of the pollutant in the receiving water and restrict the length of time that the
concentration in the receiving water can be continuously above a criterion concentration, in order
to protect aquatic life. A numerical value for the fish tissue criterion elements averaging period,
or duration, is specified as instantaneous, because fish tissue data provide point, or instantaneous,
measurements that reflect integrative accumulation of selenium over time and space in the fish
population(s) at a given site. Selenium concentrations in fish tissue are generally expected to
change only gradually over time (Section 3.2.6 and Appendix J) in response to environmental
fluctuations; thus, there would be relatively little difference in tissue concentrations with
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different averaging period durations if the average selenium concentrations in water are
relatively stable over time. Generally fish collected to calculate average tissue concentrations for
a site are collected in one sampling event, or over a short time interval due to logistical
constraints and costs for obtaining samples incurred by state monitoring programs.
2.7.7 Analysis Plan for Derivation of the Fish Tissue Criterion Elements Return Frequency
Frequency is the number of times an excursion can occur over time without impairing the
aquatic community or other use. The current recommendation (1985 Guidelines - EPA PB85-
227049) for return frequency of once in 3 years on average is based on the ability of an aquatic
ecosystem to recover from a toxic insult when pollutant impacts are associated exclusively with a
water column exposure. This recommendation is based on the variability of water concentrations
that aquatic life will be exposed to, and is set at a low level such that the water concentrations
would mostly be below the criteria concentration. Selenium, however, is a bioaccumulative
pollutant, and elevated levels in various ecological compartments (e.g., biota, surficial
sediments) require a long period to decrease and the associated aquatic community requires a
long time to recover following reduction or removal of an elevated selenium exposure to a given
system (e.g., Belews Lake, NC, and Hyco Lake, NC).
Cumbie and Van Horn (1978) first reported young of the year losses in Belews Lake
quickly followed by dramatic decreases in standing stocks of many species, and particularly
game species like bluegill and largemouth bass. Fish communities were reduced to selenium-
tolerant species including cyprinids (e.g., fathead minnow) and green sunfish in both lakes.
Selenium reduction in Belews Lake (1985) and Hyco Lake (1990), resulted in rapid decreases in
[Se] in the water column, but reductions in fish tissue took much longer. Finley and Garrett
(2007) show that concentrations in bluegill and largemouth decreased from 19 and 17 mg/kg dw,
respectively in 1992-1994 to -8.0 mg/kg dw in both species sampled between 2003-2005. In
Belews Lake, where Se contamination was higher, [Se] in crappie and redear sunfish averaged
18 and 17 mg/kg dw respectively in 1994-1996, and decreased to -9-10 mg/kg dw in both
species based on sampling in 2004-2006, twenty years later.
Chapman et al. (2010) also reported a similar scenario for Hyco Lake where "fish
recruitment failure and the a massive fish kill in 1980 led to a decimated fishery. Selenium
concentrations in the reservoir were reduced beginning in 1990 and gradual reductions in Se
exposure via the food web led to the reestablishment of a diverse Hyco Lake fish community
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similar to the period prior to Se impact." The Belews and Hyco Lake examples indicate that a
protracted period of time (in excess of 10 years) would be necessary for fish communities to
recover once a selenium in fish tissue reached concentrations associated with reproductive
impacts. Thus, the typical "once-in-three years on average" criteria return frequency is not
appropriate for selenium, as this could lead to sustained ecological impacts.
2.7.8 Analysis Plan for Derivation of Chronic Water-based Criterion Element
The relationship between the ambient concentration of selenium in water and the
concentration of selenium in the eggs or ovaries of fish is primarily through trophic transfer of
selenium, which is greatly affected by site-specific conditions. EPA used a peer-reviewed model
to derive water concentrations from the egg-ovary criterion element that explicitly recognizes
partitioning of selenium in water and particulate material (algae, detritus, and sediment), and
trophic transfer from particulate material to aquatic invertebrates, from invertebrates to fish, and
partitioning in fish whole-body and fish eggs and ovaries. The method is composed of five main
steps:
1. Formulate a mathematical equation relating the concentration of selenium in the eggs and
ovaries of fish to the ambient concentration of selenium in the water column.
2. Develop parameters needed to use the mathematical equation formulated in step 1 from
available empirical or laboratory data related to selenium bioaccumulation in aquatic systems
and aquatic organisms.
3. Classify categories of aquatic systems where a single water column concentration would be
adequately protective by evaluating the bioaccumulation potential at the base of the aquatic
food web.
4. Translate the egg-ovary criterion element to an equivalent water column concentration at
each aquatic site.
5. Apply a statistical threshold to the distribution of translated water column concentrations for
each aquatic system category to yield a water column concentration value that would be
protective of each aquatic system category.
EPA worked with USGS to derive a translation equation to estimate the site-specific
concentration of selenium in the water column corresponding to the egg-ovary criterion element
concentration. This equation utilizes a mechanistic model of bioaccumulation previously
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published in peer-reviewed scientific literature (Luoma et. al. 1992; Wang et. al. 1996; Luoma
and Fisher 1997; Wang 2001; Schlekat et al. 2002b; Luoma and Rainbow 2005; Presser and
Luoma 2006, 2010; Presser 2013). The equation uses site-specific food web models, species-
specific Trophic Transfer Factor (TTF) values, egg-ovary to whole-body conversion factor (CF)
values, and a site-specific enrichment factor (EF) values to calculate a site-specific water column
concentration element from the egg-ovary criterion element.
Empirical or laboratory data related to selenium bioaccumulation in aquatic organisms
are needed to calculate species-specific TTF and CF parameters and a site-specific EF parameter.
EPA obtained these data by reviewing its extensive selenium library of published papers and
reports, by searching published literature using EPA's public ECOTOX database and other
publically available data received through solicitation of public comments on the 2014 "External
Peer Review" draft, through the external peer reviewers of the 2014 draft, and through public
comments on the 2015 draft criterion document. Studies were screened using the same data
quality guidelines described above. Relevant studies contained selenium measurements from
field studies (water, particulate material, and aquatic organisms) or contained laboratory data on
physiological parameters of selenium bioaccumulation in aquatic organisms. Literature searches
for information on selenium associated with particulate matter included searches for data on all
forms of algae, detritus, inorganic suspended material, and sediment.
EPA compiled a collection of selenium concentration measurements from acceptable
field studies. Measurements were accepted if the study indicated the samples were collected in
the field, and the study identified the unit of measure, the media from which the measurement
was made, the location from where the sample was taken, and the date the sample was collected.
EPA only used data from studies with adequately described field collection protocols and where
concentrations were within the bounds of concentrations found using modern, rigorous protocols
in similar systems (Sanudo-Wilhelmy et al. 2004). The spatial precision of field data sample
collection locations were generally at the site level, although aggregate measurements were also
included if exposure conditions were considered similar (e.g., averages of single or composite
measurements from several locations in the same aquatic system). The temporal precision of
sample collection times were usually at the level of the day they were collected, although some
studies only provided enough information to determine the week, month, or year. If the day a
series of samples were collected was not reported but the study provided information that
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indicated the samples were taken concurrently, EPA noted sample precision, but assigned a
single effective collection date to all the samples.
EPA also compiled a collection of physiological coefficients for food ingestion rate (IR),
selenium assimilation efficiency (A A'), and rate of selenium loss (ke) from published literature.
Coefficients were accepted if the studies provided either the actual measurements or sufficient
information to derive them, and were reported in standard units (ke: /d; AE: %; IR: g/g-d) or
could be converted to standard units. Even though IR can be highly variable (Whitledge and
Hayward 2000), IR values of surrogate species were occasionally used.
EPA accounted for bioaccumulation variability across aquatic sites by evaluating the
parameter EF (representing the partitioning of selenium between the dissolved and particulate
state) from representative aquatic systems. The parameter EF is a measure of bioaccumulation
potential because it quantifies the transfer of selenium from the water column to particulate
material, which is the single most influential step in selenium bioaccumulation (Chapman et al.
2010). EPA calculated EF values for a set of aquatic systems using data from published literature
and applied statistical methods to distinguish categories with similar bioaccumulation
characteristics. On this basis, a single water column concentration is deemed adequately
protective when it is derived using data from aquatic sites in the same category. EPA translated
the egg-ovary criterion element into a set of water concentration values and derived a water
column criterion element for each aquatic system category using a percentile of the water column
concentrations for each category. To ensure adequate protection, EPA selected the 20th percentile
of the distribution of median water column values as the statistical cut-off (see Section 3.2.5),
Figure 2.3 diagrams the conceptual framework EPA used to derive water column criterion
element values from the egg-ovary criterion element.
2.7.9 Analysis Plan for Derivation of the Water Criterion Elements Duration
A numerical value for the lentic and lotic water criterion elements averaging period, or
duration, is specified as a 30-day average, because the presence of selenium in water is the initial
step in the process of bioaccumulation from the water column to fish tissue. The
bioaccumulation process for selenium takes place over a longer term than typically observed for
acute and chronic effects on aquatic life based on water concentrations. The derivation of a
protective water averaging period from kinetic modeling considerations is described in Section
3.2.6 and in Appendix J. Because the intermittent criterion element values are based on the water
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criteria chronic magnitudes and duration, the kinetic analysis of Appendix J also controls the
intermittent criterion element values.
Egg-ovary criterion element
Representative aquatic systems
Egg/ovary - whole body Conversion Factors (CP)
Concentrations in whole-body of fish
Trophic Transfer Functions (TIF)
O
Concentrations in prey
Trophic Transfer Functions (277)
O
Concentrations in particulate material
Site-specific Enrichment Factors (EF)
O
Distribution of water concentrations
Statistical threshold
O
Water criterion element
Figure 2.3. Conceptual Model for Translating the Selenium Egg-Ovary Concentration to a
Water Column Concentration.
2.7.10 Analysis Plan for Intermittent-Exposure Water-based Criterion Element Derivation
Like the chronic water criterion element, the intermittent-exposure criterion element
protects against cumulative exposure of selenium from multiple short-term discharges that may
cause an excursion of the fish tissue criterion element. EPA derived the intermittent exposure
criterion element directly from the chronic water criterion element by algebraically rearranging
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the chronic water criterion element to establish a limit on an intermittent elevated concentration
occurring over a specified percentage of time, while simultaneously accounting for background
concentrations (see Section 3.3).
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3 Effects Analysis for Freshwater Aquatic Organisms
3.1 Chronic Tissue-Based Selenium Criterion Element Concentration
Data were obtained primarily by search of published literature using EPA's public
ECOTOX database. The most recent ECOTOX database search extended to July 2013; this
document also reflects data either gathered or received by EPA based on information from the
2014 public comment period and 2014 external expert peer review of the "External Peer Review
Draft" published in May 2014, as well as information gathered based on public comments on the
2015 draft criterion. All available, relevant, and reliable chronic toxicity values were
incorporated into the appropriate selenium AWQC tables and used to recalculate the FCV, as
outlined in detail in the EPA Ambient Water Quality Criteria Guidelines.
The chronic values determined from acceptable chronic toxicity studies were separated
into reproductive endpoint and non-reproductive endpoint categories. Although both sets of
endpoints assess effects due to selenium on embryo/larval or juvenile development and survival
and growth, the fundamental difference is exposure route (inherent in test design). That is, the
fundamental difference is whether the aquatic organisms (e.g., fish) were directly exposed to
selenium in the diet and water column or exposed via maternal transfer of selenium to the
eggs/ovaries prior to reproduction. In studies with reproductive endpoints, parental females are
exposed to selenium and the contaminant is transferred from the female to her eggs. In the
selenium-exposed females, selenium replaces sulfur in vitellogenin, the primary yolk precursor,
which is transported to the ovary and incorporated into the developing ovarian follicle (Janz et al.
2010). In most but not all of these studies, progeny from these females were not additionally
exposed to aqueous selenium. The chronic values derived for the reproductive effects (survival,
deformities, and edema) are based on the concentration of selenium in the eggs or ovary, the
tissues most directly associated with the observed effects. In contrast, in studies grouped under
non-reproductive effects (usually larval and/or juvenile survival or growth), the tested fish had
no maternal pre-exposure to selenium. Chronic values for non-reproductive effects are based on
the concentration of selenium in tissues measured in the study: muscle, liver and/or whole body.
The reproductive endpoint studies applied to the derivation of the chronic criterion
elements are described below. Less definitive reproductive studies that are not directly applied to
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the criterion derivation are described in Section 6.1.2 and in Appendix C. Nonreproductive
studies are described in Section 6.1.9,
3.1.1 Acceptable Studies of Fish Reproductive Effects for the Four Most Sensitive Genera
Below is a brief synopsis of the experimental design, test duration, relevant test
endpoints, and other critical information regarding the four sensitive genera that drive the
calculation of each specific chronic value. The studies in this section involve effects on the
offspring of exposed female fish. Data are summarized in Table 3.1. Details of these studies and
other chronic studies considered for criterion derivation are contained in Appendix C.
3.1.1.1 Acipenseridae
Acipenser transmontanus (white sturgeon)
Linville (2006) evaluated the effect of elevated dietary selenium on the health and
reproduction of white sturgeon. Adult female white sturgeon (approximately 5 years old) were
fed either a control diet (no added selenium, 1.4 mg/kg Se) or a diet spiked with selenized yeast
(34 mg/kg Se) for six months in a freshwater flow through system. At the end of the dietary
exposure, females were induced to spawn and fertilized with non-exposed male milt. Large
cohorts of fertilized eggs from individual females (two from control and three from the
treatment) were collected and separately hatched. After hatching (stage 36), n=500 sets of larvae
were randomly distributed into each of six flowthrough chambers, three for stage 40 assessment
and three for stage 45 assessment. Length, weight, mortality, abnormalities (edema, skeletal
deformities) and selenium were measured at stages 36, 40 and 45. The mortality and abnormality
observations from oldest stage (45) were used for effects analysis because these measurements
showed the greatest response.
No selenium effects were observed for length or weight of larvae but effects were
observed for both abnormalities (edema and skeletal deformities) and survival. Selenium
concentrations in eggs from the control fish were 1.61 and 2.68 mg/kg dry weight (dw), and were
7.61, 11 and 20.5 mg/kg dw in eggs from the treatment fish. As stated above larval survival and
abnormality frequency was evaluated at stage 45. Because the mortalities for each cohort were
recorded up to the sample collection time for abnormalities, a combined effects variable was
derived based on the total proportion of hatched larvae which were both alive and without any
abnormalities at stage 45. This can be calculated as PS*(1-PA), where PS is the proportion
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survival in the test chambers and PA is the proportion of the sample of surviving larvae with
abnormalities. The larvae hatched from the batches of eggs with selenium concentrations of 1.61,
2.68,7.61, 11 and 20.5 mg Se/kg dw had 0.3, 0.3, 13.6,0.3 and 33.8% combined survival and
abnormal (edema and deformities) effects, respectively.
Estimation of the ECio was conducted using weighted nonlinear regression analysis with
the threshold sigmoid model equation (TRAP version 1.30a). The binary data (i.e., survival and
abnormalities) available in this study would normally be analyzed using the tolerance
distribution analysis in TRAP; however, the combined survival/abnormalities effects variable in
this study precludes its use because of the different sample sizes for survival and abnormality
evaluation. When there are insufficient data for TRAP to fit an effects/exposure curve, an
interpolation is conducted with the same TRAP equation, but constrained to provide
interpolation between two points.
Since the study yielded only one definite partial effect, TRAP cannot be used to estimate
a concentration-response curve. Instead, TRAP was used to interpolate between the last two
points to estimate the ECio (see Linville summary in Appendix C for detail). The resultant TRAP
slope is 2.96 and the interpolated ECio is 15.6 mg/kg.
The white sturgeon ECio of 15.6 mg/kg egg dw is important to include in the criterion
analyses because this species a commercially and recreationally important fish species in the
Pacific Northwest, and also serves as a surrogate for other sturgeon species in the United States
(see Section 6.4, Protection of Threatened or Endangered Species), and has a population listed as
endangered in the Kootenai River in Idaho and Montana.
3.1.1.2 Salmonidae
Acceptable studies were available for three salmonid genera, Oncorhynchus, Salvelinus
and Salmo. All of these studies evaluated the effects of selenium on salmonid embryo/larval
survival and deformity and used wild-caught adults taken from selenium contaminated streams
and spawned for effects determination. Exposure for all studies was therefore through the
parents. Summaries of the studies with Salvelinus are discussed in Section 6.1.2.3;
Oncorhynchus and brown trout {Salmo trutta) are discussed below.
Oncorhynchus mykiss (rainbow trout) Holm (2002) and Holm et al. (2005) obtained eggs
and milt from ripe rainbow trout collected from reference streams and streams containing
elevated selenium from an active coal mine in Alberta, Canada. In 2000, 2001 and 2002 eggs
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were fertilized and monitored in the laboratory until swim-up stage, for percent fertilization,
deformities (craniofacial, finfold, and spinal malformations), edema, and mortality. No
significant differences among sites were observed for percent fertilization and mortality.
Percentages of embryonic deformities and edema were significantly different among streams, but
rates of deformities at Wampus Creek, one of the reference streams, were often similar to or
higher than deformities at streams with elevated concentrations of selenium (see Holm summary
in Appendix C). The measurement of selenium in the otolith layers of rainbow trout collected in
this watershed showed low selenium exposure in the fish's early life and a higher exposure to
selenium during the fish's adult years (Palace et al. 2007), suggesting that individuals that reach
adulthood tend not to start their lives in streams with elevated selenium concentrations, even
though they may reside there later.
Craniofacial deformities, skeletal deformities and edema in rainbow trout embryo, as a
function of selenium in egg wet weight (ww), were fitted to a curve using a weighted regression
and a threshold sigmoidal equation (TRAP) from which ECio values were calculated (see
Appendix C for tables and figures). EC estimates for finfold deformities, length and weight of
rainbow trout embryos could not be made because of inadequate dose-response data. The most
sensitive endpoint was edema with an ECio value of 9.5 mg Se/kg egg ww or 24.5 mg Se/kg egg
dw. The conversion of ww to dw used the average percent moisture of 61.2% for rainbow trout
eggs reported by Seilor and Skorupa (2001).
Oncorhynchus clarkii lewisi (Westslope cutthroat trout)
In a field study similar to those conducted by Holm et al. (2005), Rudolph et al. (2008)
collected eggs from Westslope cutthroat trout from Clode Pond (exposed site) and O'Rourke
Lake (reference site). Clode Pond is on the property of Fording River Coal Operations in
Southeast British Columbia with reported selenium concentrations of 93 |ig/L. O'Rourke Lake is
an isolated water body into which Westslope cutthroat trout were stocked in 1985, 1989 and
1992 and has selenium levels reported as <1 |ig/L. Eggs with the four highest Se concentrations
(86.3 to 140 mg/kg dw) collected from Clode Pond fish died before reaching the laboratory. Of
those eggs from both ponds that survived, there was no correlation between egg selenium
concentration and frequency of deformity or edema in the fry. The percent of alevins (post hatch
to swim-up stage) that died was related to the selenium concentration in the eggs; the ECio
estimate for alevin survival based on the concentration of selenium in the eggs is 24.7 mg Se/kg
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dw. See Appendix C for details on the statistical analysis and how it differed from the previous
draft(s).
As a follow-up to the study by Rudolph et al. (2008), Nautilus Environmental (2011)
conducted a more extensive study with Westslope cutthroat trout at the same site. Adult
Westslope cutthroat trout were collected from lentic and lotic environments from locations near
the mining operations. The lentic fish were primarily captured in Clode Pond, a settling area used
to improve water quality of the mining discharge. Lotic fish were collected from the Fording
River and its tributaries near the mining operation. Reference females were obtained from
Connor Lake which is located within the watershed but not exposed to mining discharges. The
researchers reared fertilized eggs from the caught females in the laboratory until they reached
swim-up fry stage. A subset of fry surviving at swim-up were reared for an additional 28 days.
The most sensitive endpoint was larval survival at swim-up with an ECio of 27.7 mg/kg egg dw
determined by interpolation between the one partial effect (20.8% survival at 34.2 mg Se/kg and
average NOEC of 87.2% survival at 24.8 mg Se/kg; see Appendix C for detail and how this
statistical analysis differed from the previous draft(s)). This result is very similar to the ECio of
24.7 mg/kg egg dw determined for the data generated by Rudolph et al. (2008). See Appendix C
for more details on the Nautilus Environmental (2011) study.
The GMCV for Oncorhynchus reproductive endpoints is 25.3 mg Se/kg EO. This GMCV
is the geometric mean of the O. mykiss ECio of 24.5 mg (Holm 2002 and Holm et al. 2005) and
the SMCV of 26.2 mg Se/kg EO dw for 0. clarkii. The 0. clarkii SMCV was based on the ECio
values of 24.7 mg Se/kg EO from Rudolph et al (2008) and 27.7 mg Se/kg EO dw from Nautilus
Environmental (2011).
Salmo trutta (brown trout)
Formation Environmental (2011) collected adult female and male brown trout from sites
with low and high selenium exposure in the vicinity of a phosphate mine located in Southeastern
Idaho in November 2007. Eggs were collected from 26 gravid females across three sampling
locations, fertilized with milt collected from several males from the same site and taken to the
laboratory for hatching and observation of larval malformations and survival. In addition to the
field collected fish, fertilized eggs of 14 females from two separate hatcheries were used in the
study.
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The study had two phases, hatch-to-swim up, and swim up-to-15 days post swim-up.
There are two experimental complications that affect the interpretation of these data: (a) elevated
deformity rates among the offspring that were to serve as hatchery-originated method controls
(very low selenium exposure) and among some of the low exposure field-collected organisms,
and (b) the accidental loss of a number of individuals from several treatments during the 15-day
post swim up portion of the test due to overflow of the tank water. The current criterion
document's analysis is still based on the revised count data from AECOM (2012), which built
upon and superseded EPA's 2012 analysis (Taulbee et al. 2012), peer reviewed by ERG (2012).
Approximately 600 eggs/female were obtained from the majority of the field and
hatchery-collected females; however, the numbers of eggs per female ranged from 20 to 609.
Selenium concentrations were measured for a subsample of eggs taken from each field and
hatchery-collected female. EPA's primary evaluation in this document is of the survival of larvae
from hatch to swim-up. Hatching success and larval survival were monitored to swim-up, at
which time the fry were thinned to a maximum of 100 individuals for monitoring survival for 15
days post swim-up. Larvae from 24 field collected and 14 hatchery collected females were
assessed for survival, as no larvae hatched from the eggs of two of the 26 field collected females.
Because of uncertainties regarding how best to address the loss of fish during the
overflow event during the second phase of the test, and also because of the preferential selection
of healthy fish during the thinning process prior to the post-swim-up portion of the test, where
only those individuals presumed to be healthy were retained for assessment of deformities, EPA
used survival during only the first portion of the test (hatch to swim-up), as it provides a more
reliable chronic value.
The dataset of percent survival from hatch to swim-up versus the selenium concentration
in eggs is an excellent dataset and provides a good foundation for setting numeric effect
concentrations for selenium. There is a narrow range between the NOEC (20.5 mg/kg) and a
LOEC with severe effects (26.8 mg/kg, 61% mortality) that leaves little uncertainty in what an
appropriately protective effects concentration should be. There are sufficient data for TRAP to
estimate a curve, using weighted least-squares nonlinear regression with the threshold sigmoidal
model. The weighting factor for the 33 no-effect points is their standard deviation, and the
weighting factor for the 5 effect points is their residual standard deviation. The TRAP parameter
values are 96.2% for background survival, 1.45 for the logECso (ECso=28.2 mg/kg), and 4.28 for
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the slope. The ECio is estimated to be 21.0 mg/kg, slightly higher than the NOEC of 20.5 mg/kg.
The weighted TRAP model curve fits the 5 higher effects data well, which forces the ECo
estimate down to 16.4 mg/kg, below two of the points in the background range. In particular, the
fitted curve goes through the NOEC data point at 20.5 mg/kg, so that this point is considered to
be an ECg. This is reasonable because the response is so steep at concentrations above this point
that some effect at this point is plausible, and also provides further support of an ECio at 21.0
mg/kg. Section 6.1.6 provides a summary of the analysis that led to the final selection of the
ECio for larval survival during the first portion of the test. Appendix C presents details of the
study and analysis.
3.1.1.3 C entrarchi dae
Lepomis macrochirus (bluegill sunfish)
In a laboratory study, Doroshov et al. (1992a) exposed adult bluegill for 140 days to three
dietary treatments of seleno-L-methionine (nominal dietary concentrations of 8, 18 and 28 mg
Se/kg) added to trout chow. Near the end of the exposure, ripe females were induced to ovulate
and ova were fertilized in vitro with milt stripped from males. Fertilized eggs were sampled for
fertilization success and selenium content. They were also used in two tests, (a) a larval
development study during the first 5 days after hatching, and (b) a 30-day embryo-larval test. In
the 30-day larval survival test, statistical difference from the control was only found in the
highest test treatment for survival and growth (length and weight) measurements. In the 5-day
larval test, the average proportion of larvae with edema was 0% at an egg concentration of 8.33
mg Se/kg (8 mg/kg dietary treatment), 5% at an egg concentration of 19.46 mg Se/kg dw (18
mg/kg dietary treatment), and 95% at an egg concentration of 38.39 mg Se/kg dw (28 mg/kg
dietary treatment). The latter two were statistically different from the control (0% edema). All
edematous larvae died in the high treatment.
This analysis focuses on the available data for the individual replicates for the 4-day data
(5-day were not used because of almost complete mortality at the highest treatment). Of the 33
edema measurements, only 15 could be used because not all the replicate egg concentrations
were reported. Table 4 in the Doroshov et al. (1992a) summary in Appendix C shows both
individual replicates and the treatment averages, which are only slightly different than the 5-day
data (averages) previously used in the selenium document. Individual replicates rather than
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treatment means were used because the exposure concentrations vary substantially and effects
are correlated with exposure within the treatment (illustrated by nominal dietary treatments of 18
mg/kg (with corresponding Se concentrations in eggs at that nominal treatment level ranging
from 8.55 to 30.20 mg/kg) and 28 mg/kg (with corresponding Se concentrations in eggs ranging
from 25.21 to 52.18 mg/kg; see Appendix C for details).
TRAP was fitted to the available data based on the individual replicates and the treatment
means using the tolerance distribution option with the log-triangular distribution. In both cases,
the TRAP program indicates that the dataset contains inadequate partial responses because the
partial responses are less than 10% or greater than 90%, and there are no data (responses)
between 10 and 90%. However, for this dataset, these partial responses at both ends of the
concentration response curve are sufficiently informative based on multiple lines of evidence
(e.g., same response on both days 4 and 5, other endpoints that show effects at dietary treatment
of 18 mg/kg, and several instances of edema at dietary treatment 18 mg/kg in contrast to
absolutely none for many observations at any lower concentration). Also, because dietary
treatment 18 mg/kg does have an effect of several percent or so, estimating the ECio near these
points is defensible. Therefore, the ECio estimated using separate replicates is 22.6 mg/kg dw.
A similar study with similar results was done by Coyle et al. (1993) in which two year
old pond-reared bluegill sunfish were exposed in the laboratory and fed (twice daily ad libitum)
Oregon moist™ pellets containing increasing concentrations of seleno-L-methionine. Water
concentrations were nominal 10 |ig Se/L. The fish were grown under these test conditions for
140 days. Spawning frequency, fecundity, and percentage hatch were monitored for 60 days
from the initiation of spawning. There was no effect from the highest dietary selenium
concentration (33.3 mg Se/kg dw) on adult growth, condition factor, gonadal somatic index, or
other endpoints (Appendix C). The effect of interest in this study was 30-d larval survival after
hatch (deformities weren't examined and other reproductive endpoints showed no effect at the
highest exposure). For this survival endpoint, there was complete mortality after one week at the
highest exposure and no significant differences in survival at lower concentrations.
Previously, the day 5 data were used in the analysis described in Appendix C because this
was the only day in which control survival was greater than 90%, with the control and all the
treatments showing substantial and increasing toxicity over the next 4 days. However, upon
closer analysis, EPA asserts that this is not sufficient cause to base the assessment, because from
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day 6 through day 30, survival at the fifth treatment was greater than survival in the first and
third treatments, indicating this is not an effect level. These later data (day 6-30) establish that
the highest treatment is best considered an ECioo and the fifth treatment an ECo. Therefore, the
TRAP interpolation was redone using 42 mg/kg as an ECioo rather than an EC93, resulting in a
slope of 7.6 and an EC10 of 26.3 mg Se/kg dw in eggs.
Hermanutz et al. (1992), and Hermanutz et al. (1996) exposed bluegill sunfish to sodium
selenite spiked into artificial streams (nominal test concentrations: 0, 2.5, 10, and 30 |ig Se/L)
which entered the food web, thus providing a simulated field exposure (waterborne and dietary
selenium exposure). In an effort originally intended to improve the rigor of the statistical analysis
of the Hermanutz et al. (1996) data, Tao et al. (1999) re-examined the raw data records and made
corrections to the counts. This criterion document considers the Hermanutz et al. (1992) data and
the Tao et al. (1999) re-examination of Hermanutz et al. (1996).
These data come from a series of three studies lasting from 8 to 11 months, conducted
over a 3-year period. All three studies began with exposure of adult bluegill sunfish in the fall,
and with respective studies ending in the summer of the following year. Temperatures averaged
4.6, 4.1 and 4.5°C during the winter months, and averaged 26.4, 23.9 and 22.4°C during the
spawning months (June-July) for Studies I, II and III, respectively. Spawning activity was
monitored in the stream, and embryo and larval observations were made in situ and from
fertilized eggs taken from the streams and incubated within egg cups in the laboratory. None of
the adult bluegill exposed to the highest concentration of selenium in the water (Study I, mean
measured concentration equal to 29.4 |ig/L) survived the entire exposure period (although a few
did survive to spawn). Reduced survival and increased deformities on offspring were observed in
the selenium-dosed streams in both Study I and Study II, but were not found during Study III
(recovering from contamination, no active selenium input/treatment). The incidence of edema,
lordosis, hemorrhage and larval survival in the one stream concentration common to both Study I
and II, 10 |ig/L, ranged from 80 to 100 percent, 5 to 18 percent, 27 to 56 percent, and 29 to 58
percent, respectively over the three years (combined egg cup and nest observations). Edema,
lordosis, and hemorrhage in the lowest stream concentration in Study II, 2.5 |ig/L, ranged from 0
to 4 percent, 0 to 25 percent, and 3.6 to 75 percent, respectively (combined egg cup and nest
observations); larval survival was 71.6 percent (72 and 75 percent in the control streams). (See
Hermanutz 1996 and 1992 in Appendix C for more detail). The effects were not observed in
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larvae from fish that were not exposed to elevated concentrations of selenium (control
treatment). The mean concentrations of selenium in bluegill ovaries, measured at the end of each
study, ranged from 2.2 to 5.0 mg/kg dw in controls, 7.6 to 14 mg/kg dw in the 2.5 |ig/L
treatments, 34 to 52 mg/kg dw in the 10 |ig Se/L treatments, and 16 to 55 mg/kg dw in
recovering 30 |ig/L treatments. Muscle and whole-body measurements were also available. For
all three tissue types, concentrations measured during the spring of each exposure period were
not used because they were not sufficiently co-occurrent with the observation of effects. It
should also be noted that in contrast to more recent field studies, the tissue concentrations cannot
be linked from particular adult females to effects on her offspring, but only from an aliquot of
females in the treatment to all offspring observed in the treatment.
The egg-cup data for all streams of Studies I, II, and III of this experiment were
combined and analyzed in response to measured selenium concentration in the maternal ovaries
(mg/kg dw) using TRAP. That is, data for streams receiving water-borne selenium were
combined with data for streams recovering from the previous year's contamination. The absence
of effects at high tissue levels (55 mg Se/kg ovary dw) in the recovering stream of Study II did
not affect the ECio estimate because it was outweighed by three other points showing severe
effects at concentrations as low as 16.7 mg Se/kg ovary dw. However, this one observation is
suggestive but not definitive corroboration for the field observations of biological recovery in
Belews Lake and Hyco Reservoir after selenium loads were reduced, but while tissue
concentrations remained relatively high (Lemly 1997a; Crutchfield 2000; Finley and Garrett
2007).
Several egg-cup endpoints were analyzed by TRAP independently (% edema, % lordosis,
and % hemorrhage) and in combination (% normal and surviving). The best fit and most
sensitive was the combined percent normal and surviving larvae. Due to inadequate partial
effects for the ovary analysis, a threshold sigmoidal model was used to interpolate an ECio
estimate between the first interpolation point set to the highest no observed effect concentration
(HNOEC) of 14.0 mg/kg and the average background survival/normal of 69.1% and the second
point set to the LOEC of 16.7 mg/kg and a survival/normal of 5.76%. The resulting ECio is 14.7
mg/kg ovary dw. Chronic values for muscle and whole body based on percentage surviving and
free of deformities are 13.4 mg Se/kg muscle dw and 10.6 mg Se/kg whole body dw. (See
Appendix C for more discussion of this study).
43
-------
The SMCV for bluegill reproductive endpoints based on ECio values is 20.6 mg Se/kg
dw in egg/ovary, based on the ECio values of 22.6 mg/kg dw in the Doroshov et al. (1992a)
study, 26.3 mg/kg dw in the Coyle et al. (1993) study, and 14.7 mg/kg dw for Hermanutz et al.
(1992, and 1996 as corrected by Tao et al. 1999).
3.1.2 Summary of Acceptable Studies of Fish Reproductive Effects
Table 3.1 summarizes the effect concentrations obtained from all acceptable reproductive
studies with fish. Summaries of the remainder of the reproductive studies (beyond the four most
sensitive genera described above) can be found in Section 6.1.2 below.
44
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Table 3.1. Maternal Transfer Reproductive Toxicity Studies.
Species
Reference
Kxposurc Koule
Toxicological
Kndpoinl
Chronic Value
m«/k« d\v"
S.MCV
nig/k« d\v
(i.MCV
nig/k« d\v
Salvelinus malma
Dolly Varden
Golder 2009
dietary and
waterborne
(field: Kemess Mine
NW British Columbia)
EC io for total
deformities
56.2 E
56.2 E
56.2 E
Esox lucius
northern pike
Muscatello et
al. 2006
dietary and waterborne
(field: Saskatoon,
Sask.)
EC24 larval
deformities
34.0 E
34.0 E
34.0 E
Cyprinodon macularius
desert pupfish
Besser et al.
2012
dietary and waterborne
(lab)
Estimated EC 10 for
offspring survival
27 E
27 E
27 E
Micropterus salmoides
largemouth bass
Carolina Power
& Light 1997
dietary (lab)
EC10 for larval
mortality &
deformity
26.3 O
26.3 O
26.3 O
Pimephales promelas
fathead minnow
Schultz and
Hermanutz
1990
dietary and waterborne
(mesocosm:
Monticello)
LOEC for larval
edema and lordosis
<25.6 Eb
NA°
NA
Oncorhynchus mykiss
rainbow trout
Holm 2002;
Holm et al.
2003, 2005
dietary and
waterborne
(field: Luscar River,
Alberta)
EC10 for skeletal
deformities
24.5 Eb
24.5 E
25.3 E
Oncorhynchus clarkii
lewisi
Westslope cutthroat trout
Rudolph et al.
2008
dietary and waterborne
(field: Clode Pond,
BC)
EC10 for alevin
mortality
24.7 E
26.2 E
Oncorhynchus clarkii
lewisi
Westslope cutthroat trout
Nautilus
Environmental
2011
dietary and waterborne
(field: Clode Pond &
Fording River, BC)
EC 10 for survival
at swim-up
27.7 E
Salmo trutta
brown trout
Formation
Environmental
2011; AECOM
2012
dietary and waterborne
(field: Lower Sage
Creek & Crow Creek,
ID)
EC10 for larval
survival
21.0 E
21.0 E
21.0 E
45
-------
Species
Reference
Kxposnre Uoulc
Toxicologicsil
Kml point
Chronic Value
m«/k« dw"
SMCV
nig/kg dw
CMCV
nij»/k« dw
Lepomis macrochirus
bluegill
Doroshov et al.
1992a
dietary (lab)
ECio larval edema
22.6 E
20.6 E
20.6 E
Lepomis macrochirus
bluegill
Coyle et al.
1993
dietary and waterborne
(lab)
ECio for larval
survival
26.3 E
Lepomis macrochirus
bluegill
Hermanutz et
al. 1992, 1996
dietary and waterborne
(mesocosm:
Monticello)
EC io for larval
edema
14.7 Ob
Acipenser transmontanus
white sturgeon
Linville 2006
dietary (lab)
ECio for combined
edema and
deformities
15.6 E
15.6E
15.6 E
E-Concentration reported in egg; O- concentration reported in ovary
a All chronic values reported in this table are based on the measured concentration of selenium in egg/ovary tissues.
b Tissue value converted from ww to dw. See Appendix C for conversion factors.
0 SMCV not calculated due to variability in the observations among replicates in Schultz and Hermanutz (1990). The chronic
value is presented in this table to show it is in the range of selenium effect concentrations. See Appendix C for detail. Also, see
Appendix E for an additional study with fathead minnow.
46
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In order of their sensitivity to selenium, Table 3.2 presents the Genus Mean Chronic
Values from acceptable fish reproductive-effect studies that have been measured in terms of egg-
ovary concentrations.
Table 3.2. Ranked Genus Mean Chronic Values for Fish Reproductive Effects Measured as
Egg or C
~vary Concentrations.
Knnk
(;m( \-
(mg Se/kg dw r.O)
Species
SMCV
(mg Se/kg dw KO)
8
56.2
Dolly Varden,
Salvelinus malma
56.2
7
24**
Northern pike,
Esox lucius
34
6
27
Desert pupfish,
Cyprinodon macularius
27
5
26.3
Largemouth bass,
Micropterus salmoides
26.3
4
25.3
Cutthroat trout,
Oncorhynchus clarkii
26.2
Rainbow trout,
Oncorhynchus mykiss
24.5
3
21.0
Brown trout,
Salmo trutta
21.0
2
20.6
Bluegill sunfish,
Lepomis macrochirus
20.6
1
15.6
White sturgeon,
Acipenser transmontanus
15.6
* This table excludes Gambusia, which has a reproductive chronic value expressed as adult
whole-body rather than egg-ovary, because it is a live bearer.
** The Northern Pike SMCV is an EC24 based on larval deformities (Table 3.1). The EC10 is less
than 34 mg/kg.
This table excludes GMCV for Pimephales due to uncertainty in the chronic value for the
Schultz and Hermanutz (1990) study; the estimate of <25.6 mg/kg egg dw in Table 3.1 shows it
is in the range of reproductive effect levels for selenium (See Appendix C for study details).
3.1.3 Derivation of Tissue Criterion Element Concentrations
Data used to derive the final chronic value were differentiated based on the effect
(reproductive and non-reproductive effects). Acceptable chronic toxicity data on fish
reproductive effects are available for 10 fish genera. Acceptable chronic toxicity data on non-
reproductive effects are available for 7 fish genera and 3 invertebrate genera. The fish non-
47
-------
reproductive effects data were not used to calculate tissue criterion elements because they were
more variable and less reproducible than the data on reproductive effects. The genus sensitivity
distribution is predominantly populated with data on fish species because field evidence
demonstrated that fish communities were affected in situations having no observable change in
the accompanying diverse array of invertebrate communities. As a result, decades of aquatic
toxicity research have focused primarily on fish. The studies that have been done with
invertebrates (Table 3.8, Section 3.1.4) have shown them to be more tolerant than most of the
tested fish species.
Also, while amphibians are potentially sensitive due to physiologic similarities to fish,
effects clearly attributable to selenium are largely unknown (Unrine et al. 2007; Hopkins et al.
2000; Janz et al. 2010). Hopkins et al. (2000) reported that amphibian larvae at sites receiving
coal combustion wastes appear to efficiently accumulate selenium in their tissues and possibly
due to selenium have exhibited axial malformations. In a recent laboratory exposure, Masse et al.
(2015) determined an ECio of 44.9 mg/kg Se for the African clawed frog (Xenopus laevis)
suggesting that amphibians are similar to the less sensitive fish species (see Section 6.1.4),
3.1.3.1 Fish Egg-Ovary Concentration
The lowest four GMCVs from Table 3.2 are shown below in Table 3.3.
Table 3.3. Four Lowest Genus Mean Chronic Values for Fish Reproductive Effects
Relative Sensitivity
Knnk
(ienus
cm (v
(m« Se/kg dw e««-ovarv)
4
Oncorhynchus
25.3
3
Salmo
21.0
2
Lepomis
20.6
1
Acipenser
15.6
With N=15 GMCVs (see Section 3.1.6), the 5th percentile projection yields an egg/ovary
criterion element concentration of 15.1 mg Se/kg dw egg/ovary, lower than the most sensitive
fish species tested, white sturgeon (A. transmontanus). The egg/ovary criterion element
concentration is compared to the distribution of egg/ovary chronic values in Figure 3.1.
48
-------
64
T3
two
32
E
o
u
>
O
i
two
two
~
~
X
Salvelinus
Esox
X
X
Cyprinodon
+ - *
-
Micropterus
~ -
+
Oncorhynchus
Salmo
~
¦
Lepomis
Acipenser
EO FCV
o ; n (>
8
10
Rank
Figure 3.1. Distribution of Reproductive-Effect GMCVs for Fish Measured as Egg-Ovary
Concentrations.
3.1.3.2 Fish Whole-Body Criterion Element Concentration
Whole body reproductive chronic values were calculated directly from whole body tissue
concentrations measured in the study or by applying an egg-ovary (EO) to whole-body (WB)
conversion factor (CF) presented subsequently in Section 3.2.2.2, Direct calculations were done
when whole body measurements were available in the study and the data were amenable to an
effect level determination. Table 3.4 provides the chronic values for each fish genus and whether
it was calculated directly or converted from the reproductive-effect egg-ovary concentrations to
whole-body concentrations using a CF. The final EO/WB CF applied to each taxon was
determined using a hierarchical approach based on taxonomic relatedness, and is described in
Section 3.2.2, and in greater detail in Appendix B. The four most sensitive reproductive-effect
fish whole-body GMCVs are shown in Table 3.5.
49
-------
Table 3.4. Tested Reproductive-Effect Whole Body (WB) Concentrations Measured
Directlv or Converted to WB Concentrations from Egg-Ovarv (EO) Concentrations.
Taxon-
r.o
Chronic
Value
KO/W'H
CI
Direct or
Calculated
W li Ucpro
Chronic
Value
Direct Calculation or
liasis for KOAYIi CI
(from Appendix 1$)
Salvelinus
56.2
1.61
34.9
Dolly Varden EO/M (1.26) x all fish
M/WB (1.27)
Esox
34.0
2.39
14.2
Northern pike EO/M (1.88) x all fish
M/WB (1.27)
Cyprinodon
27.0
1.20
22.6
Desert pupfish EO/WB
0. mykiss
24.5
2.44
10.0
Rainbow trout EO/M (1.92) x all
fish M/WB (1.27)
Rudolph et al.
2008
24.7
1.96
12.6
Oncorhynchus EO/WB
Nautilus 2011
27.7
1.96
14.1
Oncorhynchus EO/WB
O. clarkii
26.2
NA
13.3
Geometric mean of two studies
Oncorhynchus
25.3
NA
11.6
Geometric mean of O. mykiss and O.
clarkii WB SMCVs
Micropterus
26.3
1.42
18.5
Micropterus EO/WB
Salmo
21.0
NA
13.2
Directly calculated ECio
Coyleetal. 1993
26.3
NA
8.6
Directly calculated ECio
Doroshov et al.
1992a
22.6
2.13
10.6
Bluegill sunfish EO/WB
Hermanutz et al.
1992, 1996
14.7
NA
10.6
Directly calculated ECio
Lepomis
20.6
NA
9.9
Geometric mean of three studies
Acipenser
15.6
1.69
9.2
White sturgeon EO/M (1.33) x all
fish M/WB (1.27)
* The GMCV for Gambusia, a live bearer, not included in the conversion table, was originally
measured as adult WB, not EO, and is >13.38 mg Se/kg dw WB. The "greater than" sign
signifies that no effects were found at the highest observed concentrations. This table also
excludes Pimephales due to uncertainty in the chronic value for the Schultz and Hermanutz
(1990) study (See Appendix C for details).
50
-------
Table 3.5. The Lowest Four Reproductive-Effect Whole-Body GMCVs.
Relative
Sensitivity
Rank
Genus
GMCV
(mg Se/kg dw whole-body)
4
Salmo
13.2
3
Oncorhynchus
11.6
2
Lepomis
9.9
1
Acipenser
9.2
Because the factors used to convert egg-ovary to whole-body concentrations vary across
species, the whole-body rankings differ from the egg-ovary rankings. With N=15 GMCVs, the
5th percentile projection yields a whole body criterion element concentration of 8.5 mg Se/kg dw
whole-body, slightly lower than the most sensitive fish species tested, white sturgeon (Acipenser
transmontanus). The fish whole body criterion element is compared to the distribution of fish
whole-body reproductive chronic values in Figure 3.2.
~ Salvelinus
X Cyprinodon
• Micropterus
X Gambusia
+ Esox
Salmo
~ Oncorhynchus
A Lepomis
¦ Acipenser
... WBFCV
Rank
Figure 3.2. Distribution of Reproductive-Effect GMCVs for Fish, either Measured as
Whole-Body Concentrations in the Original Tests, or Measured as Egg-Ovary
Concentrations but Converted to Whole-Body.
(As shown in Table 3.4).
TS
32
-------
3.1.3.3 Fish Muscle Criterion Element Concentration
Reproductive chronic values for muscle tissue were calculated directly from muscle
tissue concentrations measured in the study or from the egg-ovary to muscle conversion factors
of the bioaccumulation modeling approach (presented in Section 3.2). Direct calculations were
made when muscle measurements were available in the study and the data were amenable to an
effect level determination. The final EO/M CF applied to each taxon was determined using a
hierarchical approach based on taxonomic relatedness, consistent with the approach used to
calculate EO/WB CFs described in Section 3.2.2,
Table 3.6 provides the chronic values for each fish taxa and whether it was calculated
directly or converted from reproductive-effect egg-ovary concentrations to muscle
concentrations. The four most sensitive reproductive-effect fish muscle GMCVs are shown in
Table 3.7
Table 3.6. Tested Reproductive-Effect Muscle (M) Concentrations Measured Directly or
Converted to M Concentrations from Egg-Ovary (EO) Concentrations.
Taxon
i:o
Chronic
Value
EO/M
CI
Direct or
Calculated
Muscle Uepro
Chronic Value
Direct Calculation or
Basis for EO/M CI
(from Appendix 1$)
Salvelinus
56.2
1.26
44.5
Dolly Varden EO/M
Esox
34.0
NA
21.7
Directly determined EC24
Cyprinodon
27.0
0.94
28.7
Desert pupfish EO/WB (1.20)
/all fishM/WB (1.27)
0. mykiss
24.5
1.92
12.8
Rainbow trout EO/M
Rudolph et al.
2008
24.7
NA
16.6
Directly calculated EC10
Nautilus 2011
27.7
1.81
15.3
Cutthroat trout EO/M
0. clarkii
26.2
NA
16.0
Geometric mean of two studies
Oncorhynchus
25.3
NA
14.3
Geometric mean of two SMCVs
Micropterus
26.3
1.19
22.2
Micropterus EO/M
Salmo
21.0
1.14
18.5
Brown trout EO/WB (1.45)
/all fish M/WB (1.27)
52
-------
Taxon
i:o
Chronic
Value
KO/.M
(1
Direct or
Calculated
Muscle Uepro
Chronic Value
Direct Calculation or
Basis lor KO/.M CI
(from Appendix 1$)
Coyle et al.
1993
26.3
1.38
19.1
Bluegill sunfish EO/M
Doroshov et al.
1992a
22.6
NA
15.7
Directly calculated ECio
Hermanutz et
al. 1992, 1996
14.7
NA
13.4
Directly calculated ECio
Lepomis
20.6
NA
15.9
Geometric mean of three studies
Acipenser
15.6
NA
11.9
Directly calculated ECio
Table 3.7. The Lowest Four Rcproductivc-F-nect Fish Aluscle GAICVs.
Relative Sensitivity
Knnk
(ienus
GM( V
(nig Se/kg dw muscle)
4
Salmo
18.5
3
Lepomis
15.9
2
Oncorhynchus
14.3
1
Acipenser
11.9
Because the factors used to convert egg-ovary to muscle concentrations vary across
species based on empirical data, the whole-body rankings differ from both from the egg-ovary
rankings and the muscle rankings. With N=15 GMCVs, the 5th percentile projection yields a
muscle criterion element concentration of 11.3 mg Se/kg dw muscle, lower than the muscle value
for the most sensitive fish genus tested, Acipenser. Figure 3.3 compares the fish muscle criterion
element concentration to the distribution of fish muscle reproductive chronic values in Table 3.6.
53
-------
- X
+
—I
10
Rank
A
Salvelinus
X
Cyprinodon
+
Micropterus
•
Esox
X
Gambusia
-
Salmo
~
Lepomis
~
Oncorhynchus
¦
Acipenser
M FCV
Figure 3.3. Distribution of Reproductive-Effect GMCVs for Fish, either Measured as
Muscle in the Original tests, or Measured as Egg-Ovary Concentrations but Converted to
Muscle Concentrations.
(As shown in Table 3.6). (Live-bearer Gambusia was converted from WB to muscle).
3.1.4 Invertebrate Chronic Effects
Below is a brief synopsis of the experimental design of the available invertebrate chronic
toxicity tests, and the resulting chronic values.
Brachiomts calyciflorus (rotifer)
Dobbs et al. (1996) exposed Brachiomts calyciflorus to selenate in natural creek water for
25 days in a three-trophic level food chain test system. This is one of two laboratory-based
experiments (also see Bennett et al. 1986) that involved exposing algae to selenium (in this case
as sodium selenate) in water, and subsequently feeding the algae to rotifers which were in turn
fed to fish (fathead minnows). In the Dobbs et al. (1996) study, the rotifers and fish were
exposed to the same concentrations of sodium selenate in the water as the algae, but consumed
selenium bioaccumulated in the next lower trophic level. Rotifers did not grow well at
concentrations exceeding 108.1 |ig Se/L in water, and the population survived only 6 days at
selenium concentrations equal to or greater than 202.4 |ig Se/L in the water (40 |ig Se/g dw in
the algae). Regression analysis of untransformed growth data (dry weight), determined 4 day
post-test initiation, resulted in a calculated ECio of 37.84 |ig Se/g dw tissue.
54
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Lumbriculus variegatus (oligochaete, blackworm)
Although not intended to be a definitive toxicity study for blackworms, Besser et al.
(2006) evaluated the bioaccumulation and toxicity of selenized yeast to the oligochaete,
Lumbriculus variegatus, which was intended to be used for dietary exposure in subsequent
studies with the endangered desert pupfish, Cyprinidon macularius. Oligochaetes fed selenized-
yeast diets diluted with nutritional yeast (54 to 210 mg Se/kg) had stable or increasing biomass
and accumulated Se concentrations as high as 140 mg/kg dw. The oligochaetes fed the undiluted
selenized-yeast (826 jag/g Se dry wt.) showed reduced biomass. The effect level is considered
>140 mg Se/kg dw.
Centroptilum triangulifer (mayfly)
Mayfly larvae (Centroptilum triangulifer) were exposed to dietary selenium contained in
natural periphyton biofilms to eclosion (emergence) (Conley et al. 2009; Conley et al. 2011;
Conley et al. 2013). In Conley et al. (2009), the periphyton fed to the mayfly larvae were
75
exposed to dissolved selenite (radiolabeled Se) in November 2008 (12.6 and 13.9 |ig/L) and in
January 2009 ( 2.4, 2.4, 4.9, 10.3, and 10.7 |ig/L). Periphyton bioconcentrated selenium an
average of 1113-fold over the different aqueous selenium concentrations (see Table E-22 in
Appendix E). Twenty 4 to 6-day old mayfly larvae were exposed for 4.5 to 6 weeks to each of
the periphyton diets until the larvae eclosed to subimagos (final pre-adult winged stage). The
subimagos were allowed to emerge to the adult imago stage which deposited their egg masses in
Petri dishes. Selenium concentrations were measured in postpartum adults along with their dry
weights and clutch size. Selenium increased in concentration from periphyton to the adult
mayflies (trophic transfer factor) an average of 2.2-fold. The authors observed a reduction in
fecundity with diets containing more than 11 mg Se/kg dw, which is considered the dietary
threshold for this study. Using the trophic transfer factor of 2.2, the periphyton selenium
concentration of 11 mg/kg dw translates to an adult mayfly selenium concentration of 24.2
mg/kg dw.
Conley et al. (2011) exposed larval C. triangulifer larvae similar to Conley et al. (2009)
to two different rations of periphyton (lx and 2x) containing low, medium and high selenium
levels to evaluate the effect of feeding ration on the bioaccumulation of selenium and life cycle
performance of the mayfly. Mayfly larvae were fed either a lx or 2x ration of periphyton loaded
with the three different selenium levels until the larvae eclosed to subimagos after 25-29 days.
55
-------
Average periphyton Se concentrations for the three treatments in the lx ration study were 4.2,
11.9, and 27.2 mg/kg dw, respectively. In the 2x ration study, average periphyton concentrations
for the three treatments were 9.5, 19.9, and 40.9 mg/kg dw, respectively (Conley et al. 2011).
Subimagos were induced to emerge to adults in petri dishes and their clutch size measured
through digital imaging. Mayflies fed the lx ration had 54% and 72% reductions in survival
relative to controls in the medium and high Se treatment levels, respectively, both of which were
significant (p<0.05). The mayflies fed the lx ration also had significant reductions in fecundity
in the low (44% reduction), medium (63% reduction) and high (77% reduction) Se treatment
levels. However, for the mayflies that were fed the 2x ration, there were no significant
differences between the controls and any of the three Se treatment levels for any of the endpoints
measured including survival and fecundity. The 2x ration mayflies had 60% more biomass than
the lx ration mayflies. This growth difference explains why the lx ration mayflies had higher
concentrations of Se in their tissues (see Table E-23 in Appendix E). The two different rations
resulted in vastly different effect levels for Se, <12.8 mg/kg dw in the lx ration test and >37.3
mg/kg dw in the 2x ration. It is apparent from this study that if the mayflies do not obtain
sufficient nutrition, they are more sensitive to selenium. Although reduced feeding levels occur
in nature, it is a confounding variable in this study that cannot be used to set a chronic effect
level for selenium.
Conley et al. (2013) evaluated the accumulation of selenite and selenate into periphyton
with a subsequent feeding exposure to mayfly larvae. As in the previous studies, C. triangulifer
larvae were fed periphyton previously exposed to different concentrations of selenium. In this
study, periphyton plates were first exposed to low (10 |ig/L) and high (30 |ig/L) concentrations
of either selenite or selenate and then fed to mayfly larvae to eclosion and to subimagos. The
mean concentrations of selenium in the periphyton fed to the mayflies were 2.2, 12.8 and 37
mg/kg Se dw in the control, low and high treatments, respectively. Mayfly tissue (subimago)
concentrations (extrapolated from Figure 4a in Conley et al. 2013) were approximately 4-7, 20-
35, and 45-75 mg/kg Se dw, in the control, low and high treatments, respectively. The authors
reported significant reductions in survival from the control in the high Se treatment (both pooled
data and individual selenite and selenate treatments), but no significant differences were
observed in the low Se treatments. Secondary production (mayfly biomass) was significantly
reduced relative to the control in the high Se treatment for both selenium species. For the low Se
56
-------
exposure treatments, secondary production was not significantly different than the control for the
selenite treated periphyton exposure, but was for the selenate and pooled data suggesting an
effect level between 20 and 35 mg/kg Se dw. These results as well as those observed in 2x ration
exposures in Conley et al. (2011) where no effects were observed at 37.3 mg/kg Se dw generally
support the chronic value determined for Conley et al. (2009) of 24.2 mg/kg Se dw. This
information included tabulated data from these studies presented in Appendix E.
3.1.5 Summary of Relevant Invertebrate Tests
The available measured invertebrate whole-body effect concentrations are shown in
Table 3.8. Because the intent of this assessment is to derive a concentration expressed in terms
of fish tissue, Table 3.8 also provides information on how concentrations in invertebrate tissue
are translated (in Section 3.2) across media to predicted WB fish tissue concentrations (Trophic
Level 3, TL3) in a system having invertebrates and fish. That is, consistent with the
bioaccumulation modeling approach of Section 3.2, the second column of Table 3.8 uses the
median trophic transfer factor of 1.21 from Table 3.11 to yield expected WB fish tissue
concentrations in a system having invertebrates and fish. Whether comparing TL2 (invertebrate)
whole-body GMCVs directly to Table 3.4 TL3 (fish) whole-body GMCVs, or via the trophic
transfer adjustment in the second column of Table 3.8, it is apparent that invertebrates are not
among the most sensitive species.
The relative insensitivity of invertebrates overall when compared with the fish whole-
body concentrations demonstrates that invertebrates are expected to be generally protected by
selenium criterion values derived from fish. It should be noted that mayflies appear to be the
most sensitive invertebrate group tested; their whole-body effects levels just below the least
sensitive fish genus (Salvelinus, Dolly Varden) on whole-body basis. However these mayfly
results have some uncertainty due to the indicated effect of feeding ration on selenium toxicity to
mayflies that has not been fully defined. The rotifer and lumbricuius tests indicate that these
organisms are less sensitive than any tested fish genus on a whole-body basis. Therefore, the
invertebrates are considered implicitly in the species sensitivity distribution, and are counted
toward the number of values available to calculate the fish tissue criterion elements (as egg-
ovary, whole-body, and muscle), and the missing invertebrate MDRs (4 and 5) are considered
satisfied by the available invertebrate data.
57
-------
Table 3.8. Ranked Invertebrate Whole-Body Chronic Values with Translation to Expected
Accompanying Fish Whole-Body Concentrations
SMCV & (i.MCY
as measured
( Trophic Level 2)
(mg Se/kg d\v WIS)
Accompanying Trophic Level 3
Median Whole-Body Concentration
Predicted by liioacciimiilalion
Model (Section 3.2)
(mg Se/kg d\v WIS I I.3)
Species
> 140
> 169.4
Oligochaete, black,
Lumbriculus variegatus
37.84
45.8
Rotifer,
Brachionus calyciflorus
24.2
29.3
Mayfly,
Centroptilum triangulifer
3.1.6 Selenium Fish Tissue Toxicity Data Fulfilling Minimum Data Needs
The toxicity data currently available for genera and species fulfilling the EPA Ambient
Water Quality Criteria Guidelines recommendations for calculation of the freshwater chronic
criterion are described in Sections 3.1.1, 3.1.4, 6.1.2 and Appendix C, and are summarized in
Table 3.9
Table 3.9. Minimum Data Requirements Summary Table Reflecting the Number of Species
and Genus Level Mean Values Represented in the Chronic Toxicity Dataset for Selenium
in Freshwater.
(ienus Mean Chronic
Species Mean Chronic
Kreshwater .Minimum Data Requirement
Value (G.MCV)
Value (SMCV)
1. Family Salmonidae in the class Osteichthyes
3
4
2. Second family in the class Osteichthyes,
preferably a commercially or recreationally
2
2
important warmwater species
3. Third family in the phylum Chordata (may be
in the class Osteichthyes or may be an
amphibian, etc.)
5
5
4. Planktonic Crustacean
See text
See text
5. Benthic Crustacean
See text
See text
6. Insect
1
1
7. Family in a phylum other than Arthropoda or
Chordata (e.g., Rotifera, Annelida, or
1
1
Mollusca)
8. Family in any order of insect or any phylum
not already represented
1
1
Total
15
16
58
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The first three of these MDRs in Table 3.9 are easily fulfilled by the fish species
represented in Sections 3.1.1, 6.1.2 and Appendix C. Because the field observations of
contaminated sites have found effects on fish and birds in the absence of changes in invertebrate
assemblages, scientific studies on the chronic toxicity of dietary selenium for invertebrates has
been very limited. The few dietary chronic toxicity studies that are available for invertebrate
species (arthropods , rotifers, and worms) indicate that they are generally less sensitive than fish,
with available data indicating invertebrate whole body mean chronic values ranging from
approximately 3 to 12 times higher than the fish whole body criterion element value
recommended in this document (Section 3.1.4), The above invertebrate data address MDRs 6-8,
leaving only MDRs 4 and 5, for the planktonic and benthic crustaceans, to be addressed. Because
the 5th percentile calculation methods for the FCV use actual numeric values for the GMCVs of
the four most sensitive (fish) genera in the selenium dataset, it is only necessary to know that the
more tolerant genera have GMCVs that are greater than those of the lowest four. A
recommendation in the draft white paper on Aquatic Life Criteria for Contaminants of Emerging
Concern Part I (U.S. EPA 2008b), which was supported by the Science Advisory Board, states
"because only the four most sensitive genus mean chronic values (GMCVs) are used in the
criterion calculations, chronic testing requirements for a taxon needed to meet an MDR should
be waived if there is sufficient information to conclude that this taxon is more tolerant than the
four most sensitive genera."
Currently, there are no available data on the chronic toxicity to crustaceans via dietary
exposure to selenium. Since there are data available for insects (Centroptilum spp. mayfly), EPA
used the taxonomic association at the level of phylum (Arthropoda) to allow insects to be a
surrogate for crustaceans. There is also associative evidence that macroinvertebrates in general
are less sensitive than fish. At sites where there have been documented effects to fish and
aquatic-dependent birds from selenium exposure (e.g., Kesterson Reservoir, Belews Lake, Hyco
Reservoir), field observations and data indicate that there has been no evidence of effects to
macroinvertebrates including crustaceans (Janz et al. 2010). In addition, Janz et al. (2010) notes
that the key vector for selenium toxicity via maternal transfer is selenium loading in the egg via
vitellogenesis. Crustaceans, and other arthropods are not known to deposit a significant amount
of vitellogenin in the egg compared with oviparous vertebrates like fish, therefore, less selenium
is likely transferred to the egg via deposition of vitellogenin. These mechanistic considerations
59
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are thus consistent with the absence of observed field effects on aquatic macroinvertebrates,
including crustaceans and other arthropods, and with the Chapman et al. (2009, 2010) expert
consensus that it is the egg-laying vertebrates that are most at risk.
Applying this concept to the selenium criterion 5th percentile calculations, GMCVs for
MDRs 4 and 5 (the two crustacean MDRs) should be waived and counted in the total number of
GMCVs in the dataset, based on (a) the difference in the measured effect values discussed above,
and (b) the lack of observed invertebrate field effects linked to selenium (for example, as
concluded by Lemly 2002, pages 21-23, and Janz et al. 2010). Thus data are adequate to fulfill
the data needs for developing a chronic selenium criterion.
The total number of GMCVs available to derive the chronic criterion is 15. These include
ten fish genera from Sections 3.1.1 and 6.1.2 (Acipenser, Salmo, Lepomis, Micropterus,
Oncorhynchus, Pimephales, Gambusia, Esox, Cyprinodon, and Salvelinus) [Added to these are
the tested invertebrate genera Centroptilum, Brachionus, and Lumbriculus from Section 3.1.4,
and lastly the two waived genera for MDRs 4 and 5 (crustaceans).
3.2 Chronic Water Column-based Selenium Criterion Element
3.2.1 Translation from Fish Tissue Concentration to Water Column Concentration
EPA derived the chronic water column selenium criterion element by translating the egg-
ovary concentration to an equivalent water concentration. EPA worked with USGS to derive a
translation equation that utilizes a mechanistic model of bioaccumulation previously published in
peer-reviewed scientific literature (Luoma et. al. 1992; Wang et. al. 1996; Luoma and Fisher
1997; Wang 2001; Schlekat et al. 2002b; Luoma and Rainbow 2005; Presser and Luoma 2006,
2010; Presser 2013). This model quantifies bioaccumulation in animal tissues by assuming that
net bioaccumulation is a balance between assimilation efficiency from diet, ingestion rate, rate of
direct uptake in dissolved forms, loss rate, and growth rate. The basic model is given as:
60
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c,
tissue
\(K'C^)+(AEyIRyClx,,l
(k,+g)
(Equation 1)
Where:
IR
water
•tissue
g
AE
Concentration of chemical in water (|ig/L)
Average concentration of chemical in all tissues at steady-state (|ig/g)
Efflux rate (/d)
Growth rate (/d)
Uptake rate (L/g-d)
Assimilation efficiency (%)
Ingestion rate (g/g-d)
Concentration in food (|ig/g)
3.2.1.1 Simplifying the Bioaccumulation Model
Specific application to selenium bioaccumulation permits the simplification of Equation 1
in two ways. One simplification is removing the parameter representing growth rate (g), and the
other simplification is removing the parameter representing direct aqueous uptake (ku).
Growth Rate
The growth rate constant g is included in Equation 1 because the addition of body tissue
has the potential to dilute the concentration of bioaccumulative chemicals when expressed as
chemical mass per tissue mass. For very hydrophobic chemicals with low excretion rates such as
polychlorinated biphenyls, growth can be an important factor in bioaccumulation estimates
(Connolly and Pedersen 1988). However, Luoma and Rainbow (2005) suggest that for selenium,
growth rate is a relatively inconsequential parameter under most circumstances. Food
consumption is typically high during periods of high growth rate. Because food consumption is
the primary route of selenium uptake in aquatic organisms (Ohlendorf et al. 1986a, b; Saiki and
Lowe 1987; Presser and Ohlendorf 1987; Lemly 1985a; Luoma et al. 1992; Presser et al. 1994;
Chapman et al. 2010), high consumption rates of selenium-contaminated food may counteract
the selenium dilution that occurs with the addition of body tissue during periods of fast growth.
EPA evaluated the effect of removing the parameter g in the Equation 1 by performing a
sensitivity analysis. EPA analyzed a series of hypothetical tissue concentration estimates using
Equation 1 with g ranging between 0 (no growth) and 0.2/day (a relatively high rate of growth).
61
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In one analysis, tissue concentrations of selenium were estimated using static values of IR. In a
second analysis, tissue concentrations of selenium were estimated using values of IR that were
adjusted for growth rate using a method similar to the approach used in a model of organic
chemical accumulation in aquatic food webs (Thomann et al. 1992). As expected, estimates of
selenium tissue concentrations were significantly reduced at progressively higher growth rates
when IR remained constant. However, selenium concentrations remained fairly steady or slightly
increased with progressively higher growth rates when IR was adjusted for the bioenergetics of
growth. This analysis supports the hypothesis that a higher IR (and consequently greater rate of
selenium ingestion) associated with the higher bioenergetic requirements of rapidly growing
young fish tends to oppose the dilution of selenium in their tissues due to growth, whereas a
lower IR (and consequently lower rate of selenium ingestion) associated with the lower
bioenergetic requirements of slower growing older fish tends to oppose the bioconcentration of
selenium in their tissues. EPA concludes from this analysis that omitting the growth rate
parameter g is an appropriate simplification of Equation 1. A more detailed description of this
sensitivity analysis is provided in Appendix J.
Uptake Rate
The uptake rate constant ku is included in Equation 1 to account for direct absorption of
bioaccumulative chemicals in the dissolved phase. However, dietary intake of selenium is the
dominant source of exposure, suggesting that ku may also be relatively inconsequential for
selenium accumulation (Luoma and Rainbow 2005). Because aqueous uptake of selenium makes
up a small percentage of bioaccumulated selenium (Fowler and Benayoun 1976; Luoma et. al.
1992; Roditi and Fisher 1999; Wang and Fisher 1999; Wang 2002; Schlekat et. al. 2004; Lee et.
al. 2006), Presser and Luoma (2010a, b, 2013) deemed removal of ku from Equation 1 as an
acceptable simplification.
EPA evaluated the effect of removing the parameter ku in the Equation 1 by performing a
sensitivity analysis. EPA analyzed a series of tissue concentration estimates using Equation 1 and
a realistic range of ku values for trophic level 2 and trophic level 3 organisms. The analysis
suggests that approximately 75% of selenium exposure in trophic level 2 organisms
(invertebrates) and over 90% of selenium exposure in trophic level 3 organisms occurs through
consumption of selenium-contaminated food. EPA concluded that omitting the aqueous uptake
62
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rate constant ku is an appropriate simplification of Equation 1. A more detailed description of this
sensitivity analysis is provided in Appendix J.
Derivation of the Translation Equation
Disregarding growth (g) and uptake of selenium dissolved in water (ku x Cwater), Equation
1 becomes Equation 2 (Reinfelder et al. 1998):
c _ AExIRxCfood
or:
_ AExIR
tissue i food
e (Equation 2)
Because application of the bioaccumulation model applies to a single species, the
AExIR
combination of species-specific physiological parameters expressed as —; remains
ke
AExIR
constant for the species. Thus the EPA defines the expression —; as a single species-
ke
specific Trophic Transfer Factor (TTF) given as Equation 3 (Reinfelder et al. 1998):
AExIR
TTF
^e (Equation 3)
AExIR
Substituting TTF for —: in Equation 2 yields:
Ctusue = TTF x Cfood (Equation 4)
The trophic level of the organisms considered can be denoted by superscripts given as:
s~iTL2 TTJi ^^ x
ussm food (Equation 5)
63
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CTt^ue as defined here represents the steady-state proportional concentration of selenium in the
tissue of trophic level 2 organisms relative to the concentration of selenium in their food source.
Using the same rationale, the average concentration of selenium in the tissues of trophic
level 3 organisms can be expressed as the concentration of selenium in its food multiplied by a
TTF which is given as:
rTL3 = ttftl3 x rTL3
name food (Equation 6)
TZ/3 TL 2
For trophic level 3 organisms that consume trophic level 2 organisms, CJood = Ctissue.
Thus:
cIifsue= TTFTL3 X Cjtfsue (Equation 7)
Substituting c£"ue in Equation 7 with TIT'112 x C food in Equation 5 yields:
^TL3 rjirrij^TL3 rjirjij^TLl S~lTL2
tissue ~ Jood (Equation 8)
Defining the term C™ue as the concentration of selenium in fish tissue, defining the term
ctifsue as the concentration of selenium in living and nonliving particulate material ingested by
invertebrates, and expressing the product of all TTF values as a single term results in the
equation:
^whole-body = TTFcomposite X Cparticulate (Equation 9)
where:
Cparticulate = the concentration of selenium in particulate material
Cwhoie-body = the concentration of selenium in the whole body of fish
TTpcompo^te = product of all trophic transfer factor values
Equation 9 quantitatively expresses selenium bioaccumulation in fish (Cwhoie-body) as the
product of the concentration of selenium at the base of the food web (CparfiCH/ate) and a parameter
representing the trophic transfer of selenium through all dietary pathways This
model of bioaccumulation is conceptually similar to the model of bioaccumulation utilizing a
bioaccumulation factor (BAF). A BAF is the ratio of the concentration of a chemical in the tissue
64
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of an aquatic organism to the concentration of the chemical dissolved in ambient water at the site
of sampling (U.S. EPA 2001c). Similar to the term /"///x""/x',v"':', a BAF quantitatively represents
the relationship between the chemical concentrations in multiple environmental compartments.
However, a BAF is empirically derived from site-specific measurements, whereas jjp°omP°slte js
derived from knowledge of the ecological system. Because each TTF is associated with a
particular taxon, jjp°omP°slte can be inferred for an aquatic system using existing knowledge and
reasonable assumptions, without the considerable time and cost of collecting and analyzing
tissue and water samples.
Equation 9 characterizes the bioaccumulation of selenium as a combination of TTF
parameters from all steps in the dietary pathway of the predator species of interest. Thus it is
possible to differentiate bioaccumulative potential for different predator species and food webs
by modeling different exposure scenarios. For example, where the fish species of interest is a
trophic level 4 predator that primarily consumes trophic level 3 fish, the term can be
represented as the product of all TTF parameters that includes the additional trophic level given
as:
TTFcompoS1te = TTFTL4 ^ ^ y.yj/TLZ (EqUatiOIl 10)
where:
J"II''112 = the trophic transfer factor of trophic level 2 species
l'1'l'"3 = the trophic transfer factor of the trophic level 3 species
TTFTL4 = trophic transfer factor of the trophic level 4 species
j•'!•],composite = procjuct 0f all trophic transfer factors
Similarly, the consumption of more than one species of organism at the same trophic
level can also be modeled by expressing the TTF at a particular trophic level as the weighted
average of the T'/T's of all species consumed given as:
TTFTLx = £ (TTFtTLx X w,) (Equation 11)
where:
TTFi = the trophic transfer factor of the ith species at a particular trophic level
w; = the proportion of the ith species consumed
65
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These concepts can be used to formulate an expression of to model selenium
bioaccumulation in ecosystems with different consumer species and food webs. Figure 3.4
describes four example food web scenarios and the formulation of to model selenium
bioaccumulation in each of them.
The parameter jjp°omP°slte quantitatively represents all dietary pathways of selenium
exposure for a particular fish species within an aquatic system. The parameter is derived from
species-specific TTF values representing the food web characteristics of the aquatic system, wt,
the proportion of species consumed. See text for further explanation.
66
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A) Three trophic levels (simple):
rprpjjcomposite rjirji-piTL3 ^ rjirjijjTLl
TTF713 T7I'TL2
< <> < SR
B) Four trophic levels (simple):
y 7'Pcomposite 4 ^ ^ yy 'j_^'TL2
yy/,77.7 yyyTLJ yy/,77.2
~ 4> ~
C> Three trophic levels (mix within trophic levels):
jjpcon.posite = TTFTL3 x [(77^312 x WJ+ x WJ]
Til''1'13 | W7 / r7F'
^2 ^ ^ ' *
TTF'_
D) Three trophic levels (mix across trophic levels):
T]Fcon,polite = (pjpTLl x WJ+ x x
77V® , li
:^iv
< ——
TTF
E)Four trophic levels (mix across trophic levels):
jjpcomposite = ^JpTM ^ jjpTLl ^ ^jyM x wJ]x jjpTLl
J"lpTL4 ]-]],-TI.S TTJJTL2 /Jtk+
V
W1 ^ ^ ^ VNf*
I
V Wi
TTFVL4
Figure 3.4. Example Aquatic System Scenarios and the Derivation of the Equation
Parameter TTF0"^8.
Because EPA's objective is to derive an equation that translates a fish tissue
concentration of selenium to a water column concentration, the term Cwater is reintroduced into
67
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Equation 9 by defining the enrichment function EF representing the steady state proportional
bioconcentration of dissolved selenium at the base of the aquatic food web given as:
EF = cvarticulate (Equation 12)
£water
Where:
Cparticuiate = Selenium concentration in particulate material (|ig/g)
CWater = Concentration of selenium dissolved in water (|ig/L)
EF = Enrichment function (L/g)
Rearranging the terms of Equation 12:
Cparticulate ~ EF x Cwater (Equation 13)
Substituting EF X Cwater for Cparticuiate in Equation 9 results in:
CM.body = TTFcom^ x EF x CWflter (Equation 14)
Solving for the concentration of selenium in water in Equation 14 results in:
C
whole-body
— = jjpcomroai, y £F (Equation 15)
Because Equation 15 relates a concentration of selenium in water to the concentration of
selenium throughout all tissues of the body, Cwhoie-body must be converted to an equivalent
concentration in eggs or ovaries. EPA achieved this conversion by incorporating a species-
specific conversion factor (CF) into Equation 15. CI'' represents the species-specific proportion
of selenium in egg or ovary tissue relative to the concentration of selenium in all body tissues
and is given as:
C
QP _ egg-ovary
r
whoh-body (Equation 16)
Where:
CF = Whole-body to egg-ovary conversion factor (dimensionless ratio).
68
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Cegg-ovary = Selenium concentration in the eggs or ovaries of fish (|ig/g)
Cwhole-body = Selenium concentration in the whole body of fish (|ig/g).
Rearranging the terms of Equation 16 yields:
C
egg-ovar y
CF (Equation 17)
C
ggg o vEr y
Substituting Cwhoie-body in Equation 15 with yields the translation equation:
CF
r
whole-body
r
^ _ egg-ovar y
^ Mint
Yjp composite ^ ^ Qp
(Equation 18)
where TTF comP°slte equals the product of all trophic transfer factors from trophic level 2 through
the target fish species.
Equation 18 describes an ecosystem-dependent relationship between the concentration of
selenium in the eggs and ovaries of fish with the concentration of selenium in the water column.
This approach explicitly recognizes the sequential transfer of selenium between environmental
compartments (water, particulate material, invertebrate tissue, fish tissue, and eggs and/or ovary
tissue) by incorporating quantitative expressions of selenium transfer from one compartment to
the other. Because this approach uses food web modeling along with species-specific TTF and
CF parameters to quantify most of the transfer between compartments, the only field
measurements needed to relate selenium in egg-ovary and water are measurements from the
water column and particulate material sufficient to calculate EF.
3.2.2 Equation Parameters
Empirical or laboratory data related to selenium bioaccumulation in aquatic organisms
are needed to derive the equation parameters EF, TTF, and CF. EPA obtained data from
published literature as described above The search resulted in the retrieval of 63 acceptable
studies containing a total of 8,707 selenium measurements at 768 aquatic sites (2,927 from
water, 373 from algae, 29 from detritus, 821 from sediment, 1,324 from various species of
69
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invertebrates, and 3,233 from various species of fish) and 34 acceptable studies yielding 139
physiological constants (48 values of ke, 81 values of AE, and 10 values of IR). EPA used this
collection of selenium measurements to calculate site-specific EF values and develop species-
specific TTF and CF values in an unbiased and systematic manner. A more detailed description
of how EPA calculated EF is described below. How EPA calculated TTF and CF is described in
detail in Appendix B.
3.2.2.1 Derivation of Trophic Transfer Factor (TTF) Values
EPA derived TTF values for taxonomic groups of invertebrates and fish by either using
physiological coefficients found in the literature, or by evaluating the empirical relationship
between matched pairs of selenium measurements in organisms and the food they consumed.
When physiological coefficients were available, EPA calculated a TTF value using Equation 3
(Section 3.2.1):
TTF=^
^e (Equation 3)
Where:
^e = Elimination rate constant (/d)
AE = Assimilation efficiency (%)
IR = Ingestion rate (g/g-d)
EPA also derived TTF values using empirical measurements of selenium from field
studies. EPA searched its collection of available selenium measurements and identified
measurements taken from aquatic organisms. For each measurement from an aquatic organism,
EPA searched for additional measurements from other aquatic organisms or particulate material
that was collected from the same aquatic site and of a type deemed likely to be ingested as a food
source or in conjunction with feeding activity (i.e., a lower trophic level). If multiple lower
trophic level measurements were matched to an aquatic organism measurement, the median of
the lower trophic level measurements was calculated. Each pair of measurements, one taken
from an aquatic organism and the other taken from lower trophic level organisms or particulate
material, was designated as a matched pair. EPA limited particulate data used to calculate
70
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invertebrate TTFs from field data to those aquatic sites with at least two particulate selenium
measurements paired with invertebrate selenium measurements, and only used sediment
measurements if there was at least one measurement from algae or detritus. If selenium
concentrations from more than category of particulate material (algae, detritus, or sediment) were
available, EPA used the median Se concentration of the available categories as the particulate
concentration for that site.
Because selenium is transferred to aquatic animals primarily through aquatic food webs,
the observable concentration of selenium in different environmental compartments may vary
over time. To establish an appropriate time period with which to define matched pairs of
selenium measurements, the effect of sample collection time on the relationship between
selenium concentrations in different media was analyzed. EPA defined matched pairs of
selenium measurements as described above using different relative collection time ranges and
estimated the strength of the relationship between the two measurements by calculating the
Pearson product-moment correlation coefficient (r). Figure 3.5 shows the correlation coefficients
for selenium measurements taken from the same aquatic sites when the measurement collection
times were systematically shifted relative to one another. Each correlation coefficient was
calculated from a set of data within a specified range of relative collection times with respect to
the higher trophic level. For example, the correlation coefficient calculated from invertebrate and
fish measurements with a relative sample collection time of 30 to 60 days were from invertebrate
and fish samples collected at the same site, with the fish samples collected 30 to 60 days after the
invertebrate samples. Similarly, the correlation coefficient calculated from invertebrate and fish
measurements with a relative collection time of -60 to -30 days were from invertebrate and fish
samples that were collected at the same site, with the fish samples collected 30 to 60 days before
the invertebrate samples.
71
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Particulate versus invertebrate
1
# £ • «•
+ i
i
i
i
{ "
1 \
i
i
i
i J
~
-1
Invertebrate versus fish
i i • ¦ • I
I
i « ~
.£
-1
Uj Uj
I-Ix-e-s-
2 if
c _ o c c s o o
ft <5:
o o
a s
I
o § o 8 o 8
8 8
oooooooooooooooooooo
DOOOOOOOOOOOOO
8 s s a s «
o o o o o
Number of days between collection time of paired samples
Figure 3.5. Effect of Relative Sample Collection Time on Correlation Coefficients of
Selenium Measurements in Particulate Material, and Invertebrate and Fish Tissue.
Error bars indicate the 95% confidence interval of r calculated using Fisher's r to z
transformation. Horizontal dashed line indicates r = 0; vertical dashed line indicates relative
collection time expected to have the highest correlation. The absence of a correlation coefficient
indicates an insufficient quantity of data at the specified relative collection time range.
The results of this analysis suggest that the relationship between selenium concentrations
in particulate material and invertebrate tissue and between invertebrate tissue and fish tissue is
insensitive to relative collection time within a one year time period. These results also suggest
that selenium becomes relatively persistent in the aquatic ecosystem once dissolved selenium
transforms to particulate selenium and becomes bioavailable. On the basis of these analyses,
EPA concludes that selenium measurements from samples collected at the same aquatic site
within one year of each other are acceptable to use as matched pairs of measurements from the
aquatic sites. Note that EPA chose a relative collection time period of one year on the basis of
data taken from many different aquatic sites. Individual aquatic sites may have selenium loads
and/or bioaccumulation characteristics that require different relative collection time criteria to
accurately characterize selenium relationships.
After matched pairs of selenium measurements from samples collected in the field were
identified, EPA evaluated two different analytical approaches to derive species-specific TTF
72
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values from them. TTF was previously defined above as the steady state proportion relating the
concentration of selenium in the tissue of aquatic organisms to the concentration of selenium in
the food they ingest such that:
Ct^ue = TTF x Cfood (Equation 4)
Rearranging the terms of Equation 4 yields Equation 19:
C
yyy tissue
~ r
f°od (Equation 19)
Because TTF can be defined as the ratio of the concentration of selenium observed in the
tissue of an aquatic organism to the concentration of selenium observed in the tissue or material
the organism ingests, one approach for deriving TTF values from field data is to simply use the
ratio of the two values. EPA evaluated this approach by calculating the ratios for all matched
pairs of selenium measurements, and for each species or taxonomic group, used a statistic of
central tendency of the distribution of ratios as the TTF value. An advantage of quantifying the
relationship between selenium in two environmental compartments using ratios is that it is a
simple and straightforward method that is conceptually similar to a bioaccumulation factor
(BAF). A disadvantage of this approach is that it presumes that the quality and quantity of data
used to derive the ratios adequately represent the relationship being characterized. Furthermore,
many aquatic organisms tend to bioaccumulate more metals at low environmental concentrations
(McGeer et al. 2003; Borgman et al. 2004; DeForest et al. 2007; U.S. EPA 2007). Thus a
distribution of ratios could be biased toward larger values if the data are obtained from aquatic
systems with low selenium concentrations.
Another analytical approach for deriving TTF values from matched pairs of selenium
measurements is to model the species-specific relationships using linear regression. One
possibility is to regress the concentration of selenium in the food of a particular species or
taxonomic group with the concentration of selenium in the organism's tissue, and use the
regression coefficient as the TTF. EPA evaluated this approach by applying ordinary least
73
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squares (OLS) linear regression on the matched pairs of data. The regression coefficient (slope of
the fitted line) was then taken as the TTF value for that species or taxonomic group. An
advantage of this regression approach is that it estimates the quantitative relationship of selenium
across a range of environmental concentrations in a manner that allows statistical assessment.
Disadvantages of this regression approach include the assumption that the underlying data are
normally distributed; one or a few very high values can have a disproportionate influence on the
slope of the fitted line; and the bioaccumulation model does not account for a non-zero y-
intercept. Constraining the y-intercept to zero (also known as regression through the origin or
RTO) eliminates the added complexity of a non-zero y-intercept. However, RTO further
increases the disproportionate influence of one or a few high values on the slope of the fitted
line. Furthermore, RTO does not provide a straightforward way of evaluating goodness of fit
(Gordon 1981).
After evaluating both approaches, EPA decided to use a hybrid approach by designating
the median of the ratio of matched pairs of selenium measurements as the TTF value, but only if
OLS linear regression of those data resulted in a significant (P < 0.05) fit and positive regression
coefficient. Requiring a significant positive OLS linear regression coefficient confirms the
relationship between selenium in organisms and the food they ingest is adequately represented
by the available data. Using the median of the individual ratios provides an estimate of central
tendency for that relationship that is less sensitive to potential bias from measurements taken
from aquatic systems with very high or very low selenium concentrations. Some aquatic
organisms exhibit selenium bioaccumulation inversely related to water concentration (McGeer et
al. 2003; Borgman et al. 2004; DeForest et al. 2007). This inverse relationship is likely due to
saturation uptake kinetics of specific transport mechanisms that regulate metals bioaccumulation
within certain ranges (U.S. EPA 2007). EPA evaluated the effect of very high and very low
selenium concentrations on the calculation of TTF values using the hybrid approach described
above by calculating TTF values excluding selenium measurements above 10, 25, 50, and 100
Hg/g and below 0.1, 0.5, 1.0, and 2.0 |j,/g. EPA found that excluding very high or very low
selenium measurements had minor effects on TTF values. EPA concludes that using the median
ratio effectively attenuates effects of selenium concentration on the calculation of TTF values
using the hybrid approach described above and allows the use of all available data without the
need to introduce additional arbitrary exclusion criteria.
74
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EPA calculated TTF values for 13 invertebrate species and 32 fish species that live in
freshwater aquatic environments in North America. The data used to derive these TTF values are
provided in Appendix B. The final TTF values are listed in Table 3.10 and Table 3.11. The
presence of physiological coefficients for a taxon in Table 3.10 and Table 3.11 indicates that the
TTF values were calculated using those parameters. The absence of physiological coefficients for
a taxon indicates that EPA derived the TTF value using field data. If a TTF value could be
calculated from both physiological coefficients and field data, EPA used the TTF value
calculated from the substantially larger number of field measurements to minimize statistical
uncertainty.
Table 3.10. EPA-Derived Trophic Transfer Factor (TTF) Values for Freshwater Aquatic
Invertebrates.
Com moil name
Scientific name
\i:
IK
K
Ill
Crustaceans
amphipod
Hyalella azteca
-
-
-
1.22
copepod
copepods
0.520
0.420
0.155
1.41
crayfish
Astacidae
-
-
-
1.46
water flea
Daphnia magna
0.406
0.210
0.116
0.74
Insects
dragonfly
Anisoptera
-
-
-
1.97
damselfly
Coenagrionidae
-
-
-
2.88
mayfly
Centroptilum triangulifer
-
-
-
2.38
midge
Chironimidae
-
-
-
1.90
water boatman
Corixidae
-
-
-
1.48
Mollusks
asian clama
Corbicula fluminea
0.550
0.050
0.006
4.58
zebra mussel
Dreissena polymorpha
0.260
0.400
0.026
4.00
Annelids
blackworm
Lumbriculus variegatus
0.165
0.067
0.009
1.29
Other
zooplankton
zooplankton
-
-
-
1.89
a Not to be confused with Potamocorbula amurensis
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Table 3.11. EPA-Derived
rophic Transfer Factor (TTF) Values for Freshwater Fish.
Common name
Scientific name
\i:
IK
K
1 IK
Cypriniformes
blacknose dace
Rhinichthys atratulus
-
-
-
0.71
bluehead sucker
Catostomus discobolus
-
-
-
1.04
longnose sucker
Catostomus catostomus
-
-
-
0.90
white sucker
Catostomus commersonii
-
-
-
1.11
flannelmouth sucker
Catostomus latipinnis
-
-
-
0.98
common carp
Cyprinus carpio
-
-
-
1.20
creek chub
Semotilus atromaculatus
-
-
-
1.06
fathead minnow
Pimephales promelas
-
-
-
1.57
red shiner
Cyprinella lutrensis
-
-
-
1.31
redside shiner
Richardsonius balteatus
-
-
-
1.08
sand shiner
Notropis stramineus
-
-
-
1.56
Cyprinodontiformes
western mosquitofish
Gambusia affinis
-
-
-
1.21
northern plains killifish
Fundulus kansae
-
-
-
1.27
Esociformes
northern pike
Esox lucius
-
-
-
1.78
Gasterosteiformes
brook stickleback
Culaea inconstans
-
-
-
1.79
Perciformes
black crappie
Pomoxis nigromaculatus
-
-
-
2.67
bluegill
Lepomis macrochirus
-
-
-
1.03
green sunfish
Lepomis cyanellus
-
-
-
1.12
largemouth bass
Micropterus salmoides
-
-
-
1.39
smallmouth bass
Micropterus dolomieu
-
-
-
0.86
striped bass
Morone saxatilis
0.375
0.335
0.085
1.48
walleye
Sander vitreus
-
-
-
1.60
yellow perch
Perca flavescens
-
-
-
1.42
Salmoniformes
brook trout
Salvelinus fontinalis
-
-
-
0.88
brown trout
Salmo trutta
-
-
-
1.38
mountain whitefish
Prosopium williamsoni
-
-
-
1.38
cutthroat trout
Oncorhynchus clarkii
-
-
-
1.12
rainbow trout
Oncorhynchus mykiss
-
-
-
1.07
Scorpaeniformes
mottled sculpin
Cottus bairdi
-
-
-
1.38
sculpin
Cottus sp.
-
-
-
1.29
Siluriformes
black bullhead
Ameiurus melas
-
-
-
0.85
channel catfish
Ictalurus punctatus
-
-
-
0.68
76
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For fish species without sufficient data to directly calculate a TTF value, EPA estimated
the TTF value by sequentially considering higher taxonomic classifications until one or more
taxa for which a calculated TTF value was available matched the taxon being considered. If the
lowest matching taxon was common to more than one species with a TTF value available, EPA
used the median TTF from the matching species. For example, although data to directly calculate
TTF for Chrosomus eos (northern redbelly dace) were not available, this species is in the family
Cyprinidae, which also includes Rhinichthys atratulus (blacknose dace), Cyprinus carpio
(common carp), Semotilus atromaculatus (creek chub), Pimephales promelas (fathead minnow),
Cyprinella lutrensis (red shiner), Richardsonius balteatus (redside shiner), and Notropis
stramineus (sand shiner). Because Cyprinidae is the lowest taxonomic classification where
Chrosomus eos matches a species with an available TTF value, the median of the blacknose
dace, common carp, creek chub, fathead minnow, red shiner, redside shiner, and sand shiner TTF
values was used as the TTF value for northern redbelly dace. The data and analyses used to
calculate all TTF values including those estimated by taxonomic classification are provided in
Table B-8 of Appendix B.
3.2.2.2 Derivation of Whole-Body to Egg-Ovary Conversion Factor (CF) Values
The parameter CF (conversion factor) in Equation 18 (Section 3.2.1) represents the
species-specific partitioning of selenium as measured in the whole-body and in egg-ovary tissue.
EPA derived species-specific CF values by applying the same method used to derive species-
specific TTF values using empirical measurements of selenium concentrations in different tissues
of the same fish. To derive whole-body to egg-ovary CF values, EPA defined matched pairs of
selenium measurements from the whole-body and from the eggs or ovaries measured from the
same individual fish or from matched composite samples. Egg-ovary concentration was defined
as a measurement from either the eggs or the ovaries. If multiple measurements from both eggs
and ovaries of the same individual or matched composite sample were available, the average
value was used. For example, both egg and ovary measurements were available for five of the 27
egg-ovary concentrations used to calculate the bluegill egg-ovary to whole body CF (Coyle et al.
1993), and 16 of the 69 measurements used to calculate the cutthroat trout egg-ovary to muscle
CF (Kennedy et al. 2000).
Similar to the procedure used to derive TTF values, EPA first confirmed a statistical
relationship between egg-ovary and whole body selenium for each species using OLS linear
77
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regression of the matched pairs of measurements. If the regression resulted in a significant fit
(P<0.05) with a positive regression coefficient, EPA calculated the ratio of the egg-ovary to
whole body selenium concentration of each matched pair and used the median ratio as the CF
value for the species. A detailed comparison of the advantages and disadvantages of the median
ratio and least squares regression approaches to calculating CFs, along with a comparison of CFs
calculated from median ratios, OLS regression following log transformation, and total least
squares (TLS) regression following log transformation is included in Appendix N.
EPA had sufficient egg-ovary and whole-body selenium measurements to directly derive
egg-ovary to whole body CF values for 13 species of fish. However, matched pairs of selenium
measurements in eggs and/or ovaries and muscle tissue, and matched pairs of selenium
measurements in muscle and whole body were also available. To derive CF values for additional
fish species, EPA used either the additional data or a taxonomic classification approach to
estimate CF.
For those species of fish with neither sufficient data to directly calculate an egg-ovary to
whole body CF, nor data to calculate a conversion factor for egg-ovary to muscle or whole body
to muscle, EPA first estimated CF following the approach described above for the estimation of
TTF values. In this first approach, EPA sequentially considered higher taxonomic classifications
until one or more taxa for which a calculated CF value was available matched the taxon being
considered, and if the lowest matching taxon was common to more than one species with a CF
value available, EPA used the median CF from the matching species. For example, CF data are
not available to directly calculate CF for Lepomis microlophus (redear sunfish); however, genus-
level CFs for Lepomis cyanellus (green sunfish) and Lepomis macrochirus (bluegill) are
available. Thus, EPA used the median CF values of Lepomis cyanellus and Lepomis macrochirus
for redear sunfish.
For fish species without sufficient data to directly calculate an egg-ovary to whole body
CF, but which had sufficient data to calculate a conversion factor for either egg-ovary to muscle
or whole body to muscle, EPA followed a two stage approach based on taxonomic similarity. If a
fish species had a species specific egg-ovary to muscle conversion factor, but no whole body
data with which to calculate an egg to whole body CF, available data for other species would be
used to estimate a muscle to whole body conversion factor for that species based on taxonomic
relatedness. The estimated muscle to whole body factor would be multiplied by the directly
78
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measured egg-ovary to muscle factor to estimate an egg-ovary to whole body CF for that species.
For example, rainbow trout has a species specific egg-ovary to muscle conversion factor of 1.92,
but does not have a species specific egg-ovary to whole body CF. Using the taxonomic approach
described above, the most closely related taxa to rainbow trout with muscle to whole body
conversion factors are in the class Actinopterygii. The median conversion factor for the eight
species within that class is 1.27. The final egg-ovary to whole body CF for rainbow trout is 2.44
(Table 3.12), or 1.92 x 1.27.
EPA derived 13 CF values directly from matched pairs of egg-ovary and whole-body
selenium measurements and an additional seven CF values by multiplying EO/M and M/WB
conversion factors. Variability in the CF values for 19 of the 20 fish species was low (Table
3.12). Excluding mountain whitefish, CFs ranged from 1.20 to 3.11, a 2.6-fold difference. CF
variability within each species was also low for 7 of 13 species for which egg-ovary to whole-
body CFs were calculated. The two species with relatively high standard deviations for their CF
values (brown trout and cutthroat trout) contained potentially anomalous hatchery data that
contributed to the variability (see Table 3.12 footnote). These species specific CF values are
listed below in Table 3.12 and in Table B-5 of Appendix B. All CF values including those
estimated using the taxonomic classification approach are provided in Table B-6 in Appendix B.
Table 3.12. EPA-Derived Egg-Ovary to Whole-Body Conversion Factor (CF) Values
Com moil name
Scientific name
CI
Sid. Dev.'1
Acipenseriformes
white sturgeon
Acipenser transmontanus
1.69
Cypriniformes
bluehead sucker
Catostomus discobolus
1.82
0.19
flannelmouth sucker
Catostomus latipinnis
1.41
0.20
white sucker
Catostomus commersonii
1.38
0.36
desert pupfish
Cyprinodon macularius
1.20
0.10
common carp
Cyprinus carpio
1.92
0.49
roundtail chub
Gila robusta
2.07
0.29
fathead minnow
Pimephales promelas
1.40
0.75
creek chub
Semotilus atromaculatus
1.99
1.00
razorback sucker
Xyrauchen texanus
3.11
Esociformes
northern pike
Esox lucius
2.39
Perciformes
bluegill
Lepomis macrochirus
2.13
0.68
79
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Com moil nninc
Scicnlil'ic inline
CF
Slil. Dev.'1
green sunfish
Lepomis cyanellus
1.45
0.23
smallmouth bass
Micropterus dolomieu
1.42
0.19
Salmoniformes
brook trout
Salvelinus fontinalis
1.38
Dolly Varden
Salvelinus malma
1.61
brown trout
Salmo trutta
1.45
1.81"
rainbow trout
Oncorhynchus mykiss
2.44
cutthroat trout
Oncorhynchus clarkii
1.96
2.03b
mountain whitefish
Prosopium williamsoni
7.39
a Standard deviation for CF values for those species that hac
egg-ovary and whole body
concentrations.
b The brown trout and cutthroat trout standard deviations for CF' values of 1.81 and 2.03 are
considerably higher than the other standard deviations in this table. The brown trout data were
taken from two studies, NewFields (2009) and Osmundson et al. (2007). CF values for three of
the four fish samples from Osmundson et al. were four to six times greater than the median.
Also, the NewFields data consisted of samples collected from natural streams and samples
collected from a fish hatchery. The CF values for the fish hatchery samples were four to seven
times lower than the median value. Although collectively, the data set meets the criteria for
including the brown trout CF, the CF values for Osmundson et al. and NewFields hatchery
samples may be anomalously high and low, respectively. Excluding these potentially anomalous
data reduces the brown trout standard deviation to 0.47. The cutthroat trout CF values are from
two sources (Formation 2012 and Hardy 2005). The reason for the higher variability in the
cutthroat trout CF values is due to the relatively higher CF values in the hatchery fish from the
Formation study. The standard deviation for cutthroat trout drops to 0.62 if the hatchery fish are
excluded. See Appendix B for a presentation of the data for both of these species.
3.2.2.3 Calculation of Site-Specific Enrichment Factor (EF) Values
The most influential step in selenium bioaccumulation occurs at the base of aquatic food
webs (Chapman et al. 2010). The parameter EF characterizes this step by quantifying the
partitioning of selenium between the dissolved and particulate state. EF can vary by at least two
orders of magnitude across aquatic systems (Presser and Luoma 2010). The greatest reduction in
uncertainty when translating a fish tissue concentration of selenium to a water column
concentration using Equation 18 is achieved when spatially and temporally coincident site-
specific empirical observations of dissolved and particulate selenium of sufficient quality and
quantity are used to accurately characterize EF. Thus, EPA only used aquatic sites with sufficient
data to calculate a reasonably reliable EF value.
To calculate the EF of aquatic systems, EPA searched its collection of selenium
concentration measurements from field studies (see Section 2.7.8 for a description of data
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sources and acceptability criteria) and identified aquatic sites with measurements from both
particulate material and the water column. EPA first identified all selenium measurements from
algae, detritus, or sediment, and then searched for corresponding water column measurements
from samples collected at the same aquatic site within one year of the particulate sample. If more
than one water measurement was available for any given particulate measurement, the median
was used. For each of these matched pairs of particulate and water measurements, EPA
calculated the ratio of particulate concentration to water concentration. If more than one ratio for
any given category of particulate material (algae, detritus, or sediment) was calculated at an
aquatic site, EPA used the median ratio. The geometric mean of the algae, detritus, and sediment
ratios was used as the site EF. Because there were at most only three possible values (one for
algae, one for detritus, and one for sediment), EPA used the geometric mean in order to reduce
the potential for one of the values to have excessive influence on the final site EF value.
The availability of selenium measurements from particulate material was limited. In
addition, the majority of particulate measurements were from sediment samples with a
significantly lower correlation to selenium in water (r = 0.34) compared to algae (r = 0.68; Fisher
r-to-z transformation, P < 0.001) and detritus (r = 0.94; Fisher r-to-z transformation, P < 0.001).
Therefore, to reduce uncertainty in estimating site-specific EF values, EPA limited its analysis to
those aquatic sites with at least two particulate selenium measurements with corresponding water
column measurements, and only used sediment measurements if there was at least one other
measurement from either algae or detritus. On the basis of these requirements, EF values were
calculated for 96 individual aquatic sites.
3.2.3 Food-Web Models
For the aquatic sites with a calculated EF value, EPA modeled the food webs for the fish
species the studies indicated were present. Some of those studies provided information about the
species and proportions of organisms ingested by fish, either through direct analysis of stomach
contents, or examination of the presence and prevalence of invertebrate species. For those
studies, that site-specific information in the food web models was used. Most studies, however,
did not provide site-specific food web information. In those cases, the food webs of fish species
present were modeled using information about their typical diet and/or eating habits obtained
from the NatureServe database (http://www.natureserve.org).
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After EPA developed food web models, EPA identified the appropriate species-specific
TTF values for each model and calculated Although individual TTF values were
derived for several different taxa of invertebrates and fish (Table 3.10 and Table 3.11), some of
the food web models included one or more taxa for which no TTF value was available. EPA
estimated TTF values for these taxa using the same taxonomic approach used to estimate egg-
ovary to whole body, egg-ovary to muscle, and muscle to whole body conversion factors for taxa
without sufficient data. In brief, for taxa with insufficient data to calculate a TTF value, EPA
sequentially considered higher taxonomic classifications until one or more taxa for which a TTF
value was available matched the taxon being considered. If the lowest matching taxon was
common to more than one species with a TTF value available, EPA used the median TTF from
the matching species. EPA used site-specific food-web models to translate the egg-ovary
criterion element to a set of water column concentrations in order to derive the water column
concentration element of the selenium criterion. Details of these food web models are shown in
Table B-8 of Appendix B.
3.2.4 Classifying Categories of Aquatic Systems
Transformation reactions that convert dissolved selenium to particulate forms are the
primary route of entry into aquatic food webs, and are critical steps in selenium bioaccumulation
and toxicity (Chapman et al. 2010). Site-specific characteristics can result in substantial
bioaccumulation variability and consequently different risks of selenium toxicity for a given
dissolved selenium concentration. Freshwater systems fall into two distinct categories: lotic
systems such as rivers and streams, characterized by flowing water, and lentic systems, such as
lakes and ponds, characterized by largely standing water (e.g., Jones 1997). Water residence time
is generally shorter in lotic systems than in lentic systems, and subsequently, aquatic organisms
living in lentic systems tend to bioaccumulate more selenium than organisms living in lotic
systems for a given dissolved selenium concentration (ATSDR 2003; EPRI 2006; Luoma and
Rainbow 2005; Orr et al. 2006; Simmons and Wallschlagel 2005).
Although the distinction between lotic and lentic aquatic systems is often straightforward,
some aquatic systems possess both lotic and lentic characteristics. For example, flow rate can
vary greatly among lotic systems, with slow flowing low gradient systems (such as sloughs)
having longer residence times relative to fast flowing high gradient systems. Lotic systems can
also become more lentic during dry periods as hydrologic connectivity between deeper pools
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decrease or cease with decreasing flow (Buffagni et al. 2009). Downstream reaches of some low
gradient coastal rivers can also be influenced by tides (Riedel and Sanders 1998). Some lentic
systems can exhibit some degree of flow, such as lakes fed and drained by one or more streams;
however, the magnitude of flow is generally small compared to a lotic system. Even after
accounting for flow, the majority of water movement in a lentic system is driven typically by
wind or convection rather than gravity (e.g., Jones 1997). Finally, human-made reservoirs have
some features that are intermediate between typical lotic and lentic systems. For example,
reservoirs tend to be longer and narrower than natural lakes, and they have somewhat shorter
water retention time than a natural lake of comparable volume (Thornton et al. 1990). Overall,
however, reservoirs as a general class are considered more lentic than lotic, and have historically
been classified as a type of lake (Thornton et al. 1990).
To verify the suitability of lentic and lotic aquatic system categories as the basis for
independent water column criterion element values, EPA evaluated the aquatic systems that
provided data for the 96 EF values. EPA utilized the description provided by the study authors to
categorize each aquatic system as either lotic or lentic. Of the 39 lentic sites, the authors
identified them as ponds (n = 18), lakes (n = 13), reservoirs (n = 4), or marshes (n = 4). Of the 57
lotic sites, the authors identified them as creeks (n = 31), rivers (n = 16), artificial channels
(drains and wasteways, n = 3), springs (n = 2), sloughs (n = 2), or ephemeral systems (draws and
washes, n = 3). The three ephemeral aquatic sites (two washes and one draw) were categorized as
lotic because there was flowing water at the time they were sampled (Butler et al. 1995; Presser
and Luoma 2009). EF values for these aquatic systems are shown in Figure 3.6.
83
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OMa
8
Lake Reserv. Marsh Pond Creek Spring River Drain Ephem. Slough
Lentic
Lotic
Figure 3.6. Enrichment Factors (EF) for 96 Aquatic Sites Derived from Published Studies
and Organized by Waterbody Type.
The dashed line represents the median EF for the 39 lentic sites (0.9 L/g), and the solid line
represents the median EF for the 57 lotic sites (0.4 L/g). See text for information on labeled data
points.
Because the six labeled aquatic sites in Figure 3.6 (Ma, Ba, Bn, Hi, El and Fl) appear as
outliers, EPA selected them for further scrutiny. Data from site "Ma" result in an EF value of 5.2
L/g. Site "Ma" was a small irrigation pond within the Mancos River Valley watershed in
southwestern Colorado (Butler et al. 1997). This watershed drains the Mancos Shale, a region
that is naturally high in selenium. Data from sites "Hi," "Bn," and "Ba" resulted in EF values of
5.0, 5.9, and 12.5 L/g, respectively. Data from site "Hi" were from High Rock Lake, NC, data
from site "Bn" were from Barnes Lake, British Columbia (Orr et al. 2006), and data from site
"Ba" was from Badin Lake, NC (Lemly 1985). The high EF values at these three lakes were the
result of a relatively high selenium concentration in particulate matter coupled with low aqueous
84
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selenium concentrations. Data from site "El" result in an EF value of 6.3 L/g. Site "El" is an
upstream site in the Elk River watershed in southeastern British Columbia, and the relatively
large EF is the primarily the result of a low aqueous selenium concentration (McDonald and
Strosher 1998). Data from "Fl" result in an EF value of 7.1 L/g. Site "Fl" is within Flathead
wetland in southeastern British Columbia, and the relatively large EF is primarily the result of a
low aqueous selenium concentration (Orr et al. 2012).
Figure 3.7 illustrates the variability in EF values across aquatic systems and substantial
overlap between lotic and lentic categories. Some of this variability can be attributed to
differences in the ambient concentration of selenium in the water column at these aquatic sites.
EF is the ratio of selenium in particulate material (Cparticuiate) to selenium in the water column
(Cwater)- As expected, the selenium concentrations in particulate material are positively correlated
with the selenium concentrations in the water column (Figure 3.7A). The plot of Cparticuiate versus
Cwater shows a significant (P<0.001) positive relationship for both lentic (slope = 0.65, 95%
confidence interval = [0.50, 0.80]) and lotic (slope = 0.55, 95% confidence interval = [0.43,
0.68]) aquatic systems. However, selenium accrual in particulate matter is lower at aquatic sites
with a higher water concentration of selenium compared to aquatic sites with a lower water
concentration of selenium (Figure 3.7B). The plot of Cwater versus EF shows a significant
(P0.001) negative relationship for both lentic (slope = -0.36, 95% confidence interval = [-0.51, -
0.22]) and lotic (slope = -0.42, 95% confidence interval = [-0.55, -0.30]) aquatic systems.
Consistent with other studies (e.g., Hamilton and Palace 2001; Brix et al. 2005; Orr et al. 2006),
these results illustrate that the overall longer residence times of lentic systems result in increased
bioaccumulation of selenium compared to lotic systems.
85
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100
10.00
Lentic R2 = 0.68
Lotic R2 = 0.59
*•
1.00
Particulate
(Hg/g)
X )tjn\ *
X
EF (L/g)
0.10
* Lotic
* Lotic
Lentic R2 = 0.42
Lentic
• Lentic
Lotic R2 = 0.46
0.01
100
10.0
100.0
Water (|xg/L)
Water (fig/L)
Figure 3.7. The Relationship between Cwater and Cparticulate, and Cwater and EF for the 39
Lentic and 57 Lotic Aquatic Systems.
A: Relationship between Cwater and Cparticuiate by site category.
B: Relationship between Cwater and Eh' by site category.
Solid line, ordinary least squares linear regression of logged data from lentic aquatic systems.
Dashed line, ordinary least squares linear regression of logged data from lotic aquatic systems.
Figure 3.8 shows the distribution of EF values grouped by lotic and lentic aquatic system
categories. Although EPA derived the lentic and lotic EF values from aquatic sites with a similar
range of water concentrations, the relative proportion of EF values collected at sites with higher
water concentrations is larger for lentic sites than lotic sites. In particular, 6 of the 39 lentic EF
values were from ponds in the Kesterson National Wildlife Refuge where Cwater ranged from
38.6-196 |ig/L (Saiki and Lowe 1987; Schuler et al. 1990). Despite the influence of selenium
water concentration on EF, the median of EF values from lentic and lotic aquatic systems are
significantly different from each other (Mann-Whitney U, P = 0.002). EPA concludes from these
analyses that lentic and lotic aquatic system categories are appropriate categories for
differentiating Se bioaccumulation. A listing of all aquatic-sites from which EFs were calculated
is provided in Appendix H.
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8
6
O)
LD
4
2
0
_Q_
Lentic (n=39)
Lotic (n=57)
Waterbody Type
Figure 3.8. Distribution of EF Values for the Same 96 Aquatic Systems.
(As shown in Figure 3.6 and Figure 3.7 grouped by lentic and lotic aquatic system categories).
Boxes show the 25th centile, median, and 75th centile EF values; whiskers show the 10th and 90th
centiles. Circles represent EF values greater than 1.5 times the interquartile (25th-50th - lower
circles; 50th-75th -upper circles) range. Dashed line represents the median EF of all 96 sites (0.63
L/g). The EF value of 12.48 L/g from Badin Lake (Lemly 1985) is off scale.
3.2.5 Deriving Protective Water Column Concentrations for Lentic and Lotic System
Categories
To derive the water column element of the selenium criterion, EPA translated the egg-
ovary criterion element to a distribution of water column concentration values for lentic and lotic
aquatic systems. EPA uses the EF values calculated for 96 aquatic sites, available information
about the fish species present at those sites, and food web models of those fish species. Because
translation of the egg-ovary criterion element is site- and species-specific, several studies
identifying more than one species of fish could potentially provide more than one translated
water column concentration (one translated water value for each species). EPA considered using
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all water column values for all species present to generate distributions of translated water
column values from lentic and lotic aquatic sites. However, the number of reported fish species
at aquatic sites with an EF value varied from one to six fish species. Furthermore, the studies
providing data for 31 of the 96 sites with EF values do not provide information on the species of
fish that may have been present at the aquatic site. Because the number of fish species at an
aquatic site was not consistently reported, and because the number of reported fish species does
not necessarily indicate the number of species present at a site, EPA calculated one translated
egg-ovary criterion element to water column value for each aquatic site with both an EF value
and at least one reported fish species. When more than one species was reported at a site, the
EPA used the lowest translated water value for that site. Using this methodology, EPA translated
the egg-ovary FCV into water column concentrations at 26 lentic and 39 lotic aquatic sites. EPA
used these distributions of water concentration values translated from the egg-ovary criterion
element to derive chronic water column criterion element values for lentic and lotic aquatic
systems. Table 3.13 shows the model parameter values used to translate the egg-ovary criterion
element to site-specific water concentrations, and Figure 3.9 shows the distribution of the
translated values.
88
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Table 3.13. Data for the 65 Site Minimum Translations of the Egg-Ovary Criterion Concentration Element to a Water Column
Concentration.
lik'iiliriciilion
Model Pnrnmeleis
Tmnsliilion
UcTcmuv
Silo
Species
1 > |)0
/:r
( / *'
(
x U.lIlT
1! irk nor 1 TX
Lasi Allen Rosen on; Mcdioinc Bow \VY
low a daricr
Lcnlic
2.} 1
1.45
"" X"
1.5"
Birkner 1978
Galett Lake, Laramie WY
Iowa darter
Lentic
0.88
1.45
2.87
4.15
Birkner 1978
Larimer Highway 9 Pond, Fort Collins CO
northern plains killifish
Lentic
1.70
1.20
2.44
3.04
Birkner 1978
Meeboer Lake, Laramie WY
northern plains killifish
Lentic
0.58
1.20
2.44
8.96
Birkner 1978
Miller's Lake, Wellington CO
Iowa darter
Lentic
2.37
1.45
2.87
1.53
Birkner 1978
Sweitzer Lake, Delta CO
fathead minnow
Lentic
0.87
1.40
2.78
4.45
Birkner 1978
Twin Buttes Reservoir, Laramie WY
Iowa darter
Lentic
1.21
1.45
2.87
3.01
Bowie et al. 1996
Hyco Reservoir
bluegill
Lentic
2.35
2.13
2.00
1.51
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
brown trout
Lentic
1.26
1.45
2.78
2.98
Butler etal. 1997
Large pond south of G Road, southern
Mancos Valley
fathead minnow
Lentic
2.00
1.40
2.78
1.94
Butler etal. 1997
Pond downstream from site MNP2, southern
Mancos Valley
smallmouth bass
Lentic
5.15
1.42
1.93
1.07
Butler etal. 1997
Pond on Woods Canyon at 15 Road
fathead minnow
Lentic
0.90
1.40
2.78
4.29
Grasso etal. 1995
Arapahoe Wetlands Pond
fathead minnow
Lentic
0.86
1.40
2.78
4.49
Lemly 1985
Badin Lake
red shiner
Lentic
12.48
1.95
2.27
0.27
Lemly 1985
Belews Lake
red shiner
Lentic
1.75
1.95
2.27
1.94
Lemly 1985
High Rock Lake
red shiner
Lentic
4.99
1.95
2.27
0.68
Muscatello and
Janz 2009
Vulture Lake
northern pike
Lentic
1.01
2.39
4.02
1.56
Orr et al. 2012
Clode Pond 11
cutthroat trout
Lentic
0.71
1.96
2.29
4.70
Orretal. 2012
Elk Lakes 14
cutthroat trout
Lentic
1.64
1.96
2.29
2.05
Orr etal. 2012
Fording River Oxbow 10
cutthroat trout
Lentic
1.34
1.96
2.29
2.50
Orretal. 2012
Henretta Lake 27
cutthroat trout
Lentic
0.50
1.96
2.29
6.72
Saiki and Lowe
1987
Kesterson Pond 11
western mosquitofish
Lentic
0.51
1.20
2.37
10.52
Saiki and Lowe
1987
Kesterson Pond 2
western mosquitofish
Lentic
0.32
1.20
2.37
16.83
Saiki and Lowe
1987
Kesterson Pond 8
western mosquitofish
Lentic
0.60
1.20
2.37
8.84
Saiki and Lowe
1987
Volta Pond 26
western mosquitofish
Lentic
0.93
1.20
2.37
5.69
89
-------
lik'iiliriciilion
Model Pnrnmeleis
Tmnsliilion
UcTcmuv
Silo
Species
1 > |)0
/:r
( / *'
(
x U.lIlT
Stephens et al.
1988
Marsh 4720
common carp
Lentic
0.10
1.92
1.58
52.02
Butler etal. 1991
Uncompahgre River at Colona
rainbow trout
Lotic
0.63
2.44
2.33
4.21
Butler etal. 1993
Spring Cr. at La Boca
brown trout
Lotic
0.18
1.45
2.78
20.97
Butler etal. 1995
Hartman Draw near mouth, at Cortez
fathead minnow
Lotic
0.15
1.40
2.78
26.04
Butler etal. 1995
McElmo Cr. at Hwy. 160, near Cortez
fathead minnow
Lotic
0.90
1.40
2.78
4.32
Butler etal. 1995
McElmo Cr. downstream from Alkali Cyn.
fathead minnow
Lotic
0.37
1.40
2.78
10.57
Butler etal. 1995
McElmo Cr. downstream from Yellow
Jacket Cyn.
red shiner
Lotic
0.12
1.95
2.27
28.34
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
red shiner
Lotic
0.10
1.95
2.27
35.60
Butler etal. 1995
Navajo Wash near Towaoc
speckled dace
Lotic
0.20
1.95
1.36
29.07
Butler etal. 1995
San Juan River at Four Comers
red shiner
Lotic
0.26
1.95
2.27
12.97
Butler etal. 1995
San Juan River at Mexican Hat Utah
common carp
Lotic
0.29
1.92
1.58
17.24
Butler etal. 1995
Woods Cyn. Near Yellow Jacket
fathead minnow
Lotic
0.40
1.40
2.78
9.60
Butler etal. 1997
Cahone Canyon at Highway 666
green sunfish
Lotic
0.20
1.45
2.29
23.22
Butler etal. 1997
Mud Creek at Highway 32, near Cortez
fathead minnow
Lotic
0.07
1.40
2.78
55.27
Casey 2005
Deerlick Creek
rainbow trout
Lotic
2.24
2.44
2.33
1.18
Casey 2005
Luscar Creek
rainbow trout
Lotic
0.33
2.44
2.33
8.14
Formation 2012
Crow Creek - 1A
brown trout
Lotic
0.80
1.45
2.96
4.42
Formation 2012
Crow Creek - 3 A
brown trout
Lotic
0.81
1.45
2.97
4.37
Formation 2012
Crow Creek - CC150
brown trout
Lotic
1.04
1.45
2.91
3.44
Formation 2012
Crow Creek - CC350
brown trout
Lotic
1.16
1.45
2.97
3.02
Formation 2012
Crow Creek - CC75
brown trout
Lotic
1.19
1.45
2.87
3.07
Formation 2012
Deer Creek
brown trout
Lotic
1.55
1.45
3.00
2.25
Formation 2012
Hoopes Spring - HS
brown trout
Lotic
0.24
1.45
3.86
11.06
Formation 2012
Hoopes Spring - HS3
brown trout
Lotic
0.54
1.45
2.63
7.40
Formation 2012
Sage Creek - LSV2C
brown trout
Lotic
0.45
1.45
3.01
7.76
Formation 2012
Sage Creek - LSV4
brown trout
Lotic
0.69
1.45
2.88
5.22
Formation 2012
South Fork Tincup Cr.
brown trout
Lotic
1.32
1.45
3.05
2.58
Hamilton and
Buhl 2004
Lower East Mill Creek
cutthroat trout
Lotic
1.32
1.96
2.29
2.55
McDonald and
Strosher 1998
Elk R. above Cadorna Cr. (745)
mountain whitefish
Lotic
6.30
7.39
2.97
0.11
McDonald and
Strosher 1998
Fording R. above Swift Cr. (746)
cutthroat trout
Lotic
0.23
1.96
2.29
14.91
Orretal. 2012
Elk River 1
cutthroat trout
Lotic
0.55
1.96
2.29
6.14
90
-------
lik'iiliriciilion
Model Pnrnmeleis
Tmnsliilion
UcTcmuv
Silo
Species
1 > |)0
/:r
( / *'
(
x U.lIlT
Orretal. 2012
Elk River 12
cutthroat trout
Lotic
2.67
1.96
2.29
1.26
Orretal. 2012
Fording River 23
cutthroat trout
Lotic
0.21
1.96
2.29
16.20
Orretal. 2012
Michel Creek 2
cutthroat trout
Lotic
0.28
1.96
2.29
11.85
Saiki and Lowe
1987
San Luis Drain
western mosquitofish
Lotic
0.36
1.20
2.37
14.81
Saiki and Lowe
1987
Volta Waste way
western mosquitofish
Lotic
1.03
1.20
2.37
5.17
Saiki etal. 1993
Mud Slough at Gun Club Road
bluegill
Lotic
1.37
2.13
1.47
3.53
Saiki etal. 1993
Salt Slough at the San Luis National
Wildlife Refuge
bluegill
Lotic
0.43
2.13
1.47
11.29
Saiki etal. 1993
San Joaquin R. above Hills Ferry Road
bluegill
Lotic
0.36
2.13
1.47
13.50
Saiki etal. 1993
San Joaquin R. at Durham Ferry State
Recereation Area
bluegill
Lotic
0.75
2.13
1.47
6.46
a - Geometric mean of the median enrichments functions (/•.'/<) for all available food types (algae, detritus, and sediment). EF (L/g) = Cf00d/Cwater-
b - Taxa-specific conversion whole-body to egg ovary conversion factor (CF; dimensionless ratio),
c - Composite trophic transfer factor (777'"'""v"'v'"'). Product of TTF values for all trophic levels.
d - Translated water concentration corresponding to an egg-ovary criterion element of 15.1 mg Se/kg dw, calculated by Equation 18.
91
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Cumulative
proportion
~
m
I x *
! • *
i i *x
• *
» • X
• *
. • X
m X
X
• X
• *
" • X
1 *
J *
*¦ X
«t X
•' xx
• , X
• X * Lotic
, • | ;
¦* • Lentic
i 1
•
X .
* I
• X
X I
m *
X *
1 1 1 ( ( ( ( 1 |
¦ . —
0
1
10
100
Water (n-g/'L)
Figure 3.9. Probability Distribution of the Water Column Concentrations Translated from
the Egg-Ovary Criterion Element at 26 Lentic and 39 Lotic Aquatic Sites.
Dashed and dash-dot lines show the 20th percentiles of the lentic and lotic distributions,
respectively.
EPA selected the 20th percentile from the distribution of translated water column values
of each category as the final national water column criterion element concentrations (3.1 |ig/L
for lotic waters and 1.5 |ig/L for lentic waters) because the 20th percentile is consistent with past
practice as it provides a high probability of protection for most aquatic systems in both lentic and
lotic categories. Table 3.14 provides the 20th percentile of the water concentration values
translated from the egg-ovary criterion element value.
Table 3.14. Water Column Criterion Element Concentration Values Translated from the
Egg-Ovary Criterion Element.
l.entic
Lotic
20th percentile
(final EPA-recommended water column criterion element)
1.5 jig/L
3.1 jig/L
As discussed in Section 2.2.2, selenium bioaccumulation potential depends on several
biogeochemical factors that characterize a particular aquatic system. Uncertainty in the
translation of the egg-ovary criterion element to the water column element can be reduced by
deriving a site-specific criterion that uses site-specific selenium data and information on food-
web dynamics from a biological assessment of the aquatic system. The general considerations
are provided in Appendix K. The derivation of water column criterion element values described
92
-------
above is constrained by the need to apply a national criterion value to a large number of aquatic
systems for lentic and lotic systems.
3.2.6 Derivation of Averaging Period for Chronic Water Criterion Element
In the context of selenium bioaccumulation in a single trophic level, k would be the first-
order depuration coefficient, and 1/k would equal the time needed to depurate to a concentration
of 1/e times the initial concentration (where e=2.718). For depuration of two trophic levels
sequentially, invertebrates and fish, the characteristic time is likewise the time needed for c/c0 to
reach a value of 1/e. This differs from typical criteria averaging periods based on U.S. EPA
(1995), where the concept that the criterion averaging period should be less than or equal to the
"characteristic time" describing the toxic speed of action due to direct waterborne toxicity of
metals (i.e., where characteristic time = 1/k, where k is the first-order kinetic coefficient in a
toxicokinetic model fitted to the relationship between LC50 and exposure duration). For the first
trophic level, the kinetics for algal bioaccumulation and depuration were assumed to be rapid
compared to the kinetics for larger organisms at higher trophic levels; that is, the characteristic
time for algae was assumed to be negligible.
For the second trophic level, invertebrates, values for kTL2 are tabulated elsewhere in the
document. A value of 0.1/day appears to be environmentally conservative, considerably higher
than those for Lumbriculus, Asian clam, and zebra mussel, but slightly lower than copepods,
which are very small in size. This corresponds to a characteristic time of 10 days.
For fish, the median depuration coefficient measured by Bertram and Brooks (1986) for
6-9 month-old (early adult) fathead minnows is applied, providing a kTL3 value of 0.02/day. This
corresponds to a characteristic time of 50 days. Because of the small size of adults of this
species, this represents faster kinetics than would likely be applicable to the salmonids and
centrarchids of greatest concern for selenium toxicity, consonant with the Newman and Mitz
(1988) inverse relationship between depuration rate and organism size. The striped bass k value
of Baines et al. (2002) is inapplicable here because it was measured in the early juvenile life
stage, a size that is too small to be relevant to reproductive impairment stemming from exposure
of adult females.
As shown in Appendix J, the characteristic time for the combined second and third
trophic levels (invertebrates and fish) is the approximate sum of the above two characteristic
times, or 60 days. The analysis of the protectiveness of a 30-day averaging period, shorter than
93
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the characteristic time, was performed and is shown in Appendix J. That analysis demonstrated
that a 30-day averaging period for the chronic water criterion element affords protection under
all conditions, and is therefore the duration recommended for the chronic water column criterion
element.
3.3 Intermittent-Exposure Water Criterion Element: Derivation from
the Chronic Water Criterion Element
Chapman et al. (2009) noted that selenium acute toxicity has been reported rarely in the
aquatic environment and that traditional methods for predicting effects based on direct exposure
to dissolved concentrations do not work well for selenium. As demonstrated in Appendix J, the
kinetics of selenium accumulation and depuration are sufficiently slow that attainment of the
water criterion element concentration by ambient 30-day averages will protect sensitive aquatic
life species even where concentrations exhibit a high degree of variability.
To address situations where pulsed exposures of selenium could result in
bioaccumulation in the ecosystem and potential chronic effects in fish, EPA is providing an
intermittent exposure water criterion element concentration intended to limit cumulative
exposure to selenium, derived from the chronic 30-day water criterion element magnitude and
from its duration, which was obtained from the kinetic analysis of Appendix J. That is, the
intermittent criterion element is based on the same kinetic analysis used to derive the water
chronic averaging period (30 days).
To illustrate the concept of the intermittent criterion element and its dependence on the
30-day criterion element magnitude and duration, Figure 3.10 shows a possible sequence of
exposures over a 30-day period.
94
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Figure 3.10. Illustration of Intermittent Spike Exposure Occurring for a Certain
Percentage of Time (e.g., 10%) Over a 30-Day Period, and Background Exposure
Occurring for the Remaining Percentage of Time (e.g., 90%).
The 30-day average concentration, C30day, is given by Equation 20:
C30-day ~ Cintfint Cbkgmd(1 — f int)
(Equation 20)
Where:
Qnt = the intermittent spike concentration (|ig/L)
fint = the fraction of any 30-day period during which elevated selenium
concentrations occur
Cbkgmd = the average daily background concentration occurring during the
remaining time, integrated over 30 days.
C30-day i s not to exceed the chronic criterion element, WQC3o-day. If the intent is to apply a
criterion element, WQCmt, to the intermittent spike concentrations, then replacing C,nt with
WQCmt and Cso-day with WQC3o-day in the above equation, and then solving for WQCmt yields
Equation 21:
WQCint =
WQC^q day Cbkgrndi.1 fint)
fint
(Equation 21}
95
-------
The equation expresses the intermittent exposure water criterion element in terms of the
30-day average chronic water criterion element, for a lentic or lotic system, as appropriate, while
accounting for the fraction in days of any 30-day period the intermittent spikes occur and for the
concentration background occurring during the remaining time. The reasonable worst-case
assumption inherent in this approach is that selenium bioaccumulation is linear over a very wide
range of concentrations, that is, EF and TTF values do not decrease significantly as
concentrations increase.
If the heights of three spikes in Figure 3.10 were to differ somewhat among each other,
the intermittent element would apply to the arithmetic mean of the three. If the background
concentrations were to vary somewhat, then the arithmetic mean background would be entered
into the equation. Where concentrations vary smoothly over time, it does not matter where the
line is drawn defining elevated versus background concentrations. The intermittent element will
yield the same level of protection as the 30-day average element, provided that the equation uses
(a) the average of the concentrations occurring for the fraction of time defined as being
intermittently elevated, and (b) the average of the concentrations occurring for the remaining
time, defined as being background. The intermittent element will only be exceeded under
conditions that would have caused the 30-day element to be exceeded, had it been applied.
Table 3.15 illustrates example values for the intermittent element. The bottom row of the
lotic and lentic values and the right column are to emphasize that WQCmt '\§ not an independent
element but a re-expression of the 30-day average water criterion element concentration. WQCmt
converges to WQCw-cby when the background concentration is already at WQC3o-day or when the
intermittent exposure is said to occur throughout the 30-day period.
96
-------
Table 3.15. Representative Values of the Intermittent Water Criterion Element
Concentration.
likurml
l-'raction oi l
ime. in a 30-dav period
Cone.
0.03333
0.05
0.1
0.2
0.5
1
^ hlt^niil
(1 day)
(1.5 (lavs)
(3 (lavs)
(6 davs)
(15 davs)
(30 davs)
(MK/I-)
l.olic Inlerniillenl Criterion Klcment. II OC,m(iig/l.)
U
93
t>2
31
15.5
t>.2
3.1
1
64
43
22
11.5
5.2
3.1
2
35
24
13
7.5
4.2
3.1
2.5
20.5
14.5
8.5
5.5
3.7
3.1
3 1
3 1
3 1
3 1
3 1
3 1
3 1
l.enlic Inlerniillenl Criterion Klemenl. H (X';,,,(ii«/l.)
0
45
30
15
7.5
3
1.5
0.5
30.5
20.5
10.5
5.5
2.5
1.5
1
16
11
6
3.5
2
1.5
1.25
8.8
6.3
3.8
2.5
1.8
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
If the value of fnt, the intermittent exposure fraction of the month, is assigned a value less
than one day, the intermittent criterion element value could exceed water concentrations that
have been shown to be acutely toxic to sensitive species in 2- or 4-day toxicity tests (compiled in
U.S. EPA 2004). Because the concentrations that would be acutely toxic in exposures of less
than one day might not be much greater than those observed to be toxic in 2-4 day exposures, the
intermittent fraction of the month must not be assigned a value less than 0.033, corresponding to
one day.
97
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4 National Criterion for Selenium in Fresh Waters
The available data indicate that freshwater aquatic life would be protected from the toxic
effects of selenium by applying the following four-part criterion, recognizing that fish tissue
elements supersede the water elements (except in special situations, see footnotes 3 and 4, Table
4.1) and that the egg-ovary tissue element supersedes all other tissue elements:
1. The concentration of selenium in the eggs or ovaries of fish does not exceed 15.1 mg/kg,
dry weight; 1
2. The concentration of selenium (a) in whole-body of fish does not exceed 8.5 mg/kg dry
weight, or (b) in muscle tissue of fish (skinless, boneless fillet) does not exceed 11.3
mg/kg dry weight;
3. The 30-day average concentration of selenium in water does not exceed 3.1 |ig/L in lotic
(flowing) waters and 1.5 |ig/L in lentic (standing) waters more than once in three years
on average;
4. The intermittent concentration of selenium in either a lentic or lotic water, as appropriate,
i,i tAmr WQC30-(iay ~ Cbkgrnd(l~f int) ,1 • ,1
does not exceed WQCint = - more than once in three years on
/ int
average.3
98
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Table 4.1. Summary of the Recommended Freshwater Selenium Ambient Chronic Water
Quality Criterion for Protection of Aquatic Life.
Media
Type
Criterion
Klcmcnl
Magnitude
Duration
l-'requencv
I'isli Tissue1
K jig/Ovary 2
I'isli W hole
liody or
Muscle'
\Yater Column4
Monthly
Average
Kxposurc
1 n 1 erin i11ent K x pos u re"
1 5 I mg/kg dw
8.5 mg/kg dw
whole body
or
11.3 mg/kg
dw muscle
(skinless,
boneless filet)
1.5 |ig/L in
lentic aquatic
systems
3.1 |ig/L in lotic
aquatic systems
WQCint =
WQCzo-day ~ Cftkgrnd^X ~ f int)
fint
Instantaneous
measurement6
Instantaneous
measurement6
30 days
Number of days/month with an
elevated concentration
Not to be
exceeded
Not to be
exceeded
Not more than
once in three
years on
average
Not more than once in three years
on average
1. Fish tissue elements are expressed as steady-state.
2. Egg/Ovary supersedes any whole-body, muscle, or water column element when fish egg/ovary concentrations are
measured, except as noted in footnote 4 below.
3. Fish whole-body or muscle tissue supersedes water column element when both fish tissue and water concentrations are
measured, except as noted in footnote 4 below.
4. Water column values are based on dissolved total selenium in water and are derived from fish tissue values via
bioaccumulation modeling. When selenium inputs are increasing, water column values are the applicable criterion element
in the absence of steady-state condition fish tissue data.
5. Where WQC30-day is the water column monthly element, for either a lentic or lotic waters; Cbkgrnd is the average
background selenium concentration, and fmt is the fraction of any 30-day period during which elevated selenium
concentrations occur, with fint assigned a value >0.033 (corresponding to 1 day).
6. Fish tissue data provide instantaneous point measurements that reflect integrative accumulation of selenium over time and
space in fish populations) at a given site.
EPA recommends that states and tribes adopt into their water quality standards a
selenium criterion that includes all four elements, and express the four elements as a single
criterion composed of multiple parts, in a manner that explicitly affirms that the whole-body or
muscle elements supersede the water column element, and the egg-ovary element supersedes any
other element. The magnitude of the fish egg-ovary element is derived from analysis of the
99
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available toxicity data. The magnitudes of the fish whole-body element and fish muscle elements
are derived from the egg-ovary element coupled with data on concentration ratios among tissues.
The magnitudes of the water column elements are derived from the egg-ovary element coupled
with bioaccumulation considerations. Inclusion of the fish whole-body or fish muscle element
into the selenium criterion ensures the protection of aquatic life when fish egg or ovary tissue
measurements are not available, and inclusion of the water column elements into the selenium
criterion ensures protection when neither fish egg-ovary nor fish whole-body nor muscle tissue
measurements are available. To ensure that the contribution of short-term exposures to the
bioaccumulation risks is accounted for in all situations, EPA is also recommending that the
intermittent exposure element be included in the selenium criterion, as noted above. EPA is not
recommending a separate acute criterion derived from the results of toxicity tests having water-
only exposure because selenium is bioaccumulative and toxicity primarily occurs through dietary
exposure. Application of the intermittent exposure criterion element values to single day, high
exposure events will provide protection from the most important selenium toxicity effect,
reproductive toxicity, by protecting against selenium bioaccumulation in the aquatic ecosystem
resulting from short-term, high exposure events. It is unnecessary to have an additional acute
water column criterion element because the intermittent exposure criterion element will be more
stringent than an acute criterion element. Further, as noted in this document, there have been few
if any acute exposure, water column-only selenium aquatic toxicity events documented in the
literature.
In implementing the water quality criterion for selenium under the NPDES permits
program, states may need to establish additional procedures due to the unique components of the
selenium criterion. Where states use the selenium water column concentration criterion element
values only (as opposed to using both the water column and fish tissue elements) for conducting
reasonable potential (RP) determinations and establishing water quality-based effluent
limitations (WQBELS) per 40 CFR 122.44(d), existing implementation procedures used for
other acute and chronic aquatic life protection criteria may be appropriate. However, if states
also decide to use the selenium fish tissue criterion element values for NPDES permitting
purposes, additional state WQS implementation procedures (IPs) will be needed to determine the
need for and development of WQBELs necessary to ensure that the fish tissue criterion
element(s) are met.
100
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EPA recommends that states use the default monthly average exposure water column
elements of the criterion, adopted as part of the state's water quality criterion. Alternatively,
states may want to develop and adopt, and submit for EPA approval, either a site-specific water
column criterion (see Appendix K for details), or a procedure to facilitate the translation of a fish
tissue criterion element concentration into site-specific water concentration values. A site-
specific water column criterion element or set of lentic/lotic criterion element values may be
developed using a mechanistic modeling approach (Presser and Luoma 2010) or using the
empirical bioaccumulation factor approach, both described in Appendix K, for the specific
waterbody or waterbodies, or a on a state-wide basis. A translation procedure must be
scientifically defensible and able to produce repeatable and predictable outcomes, and must be
consistent with either the mechanistic modeling approach or the empirical bioaccumulation
factor approach described in Appendix K. The chronic selenium criterion is derived to be
protective of the entire aquatic community, including fish, amphibians, and invertebrates. Fish
are the most sensitive to selenium effects. Selenium water quality criterion elements based on
fish tissue (egg-ovary, whole body, and/or muscle) sample data override the criterion elements
based on water column selenium data due to the fact, noted above, that fish tissue concentrations
provide the most robust and direct information on potential selenium effects in fish. However,
because selenium concentrations in fish tissue are a result of selenium bioaccumulation via
dietary exposure, there are two specific circumstances where the fish tissue concentrations do not
fully represent potential effects on fish and the aquatic ecosystem: 1) in "fishless" waters, and 2)
in areas with new selenium inputs.
Fishless waters are defined as waters with insufficient instream habitat and/or flow to
support a population of any fish species on a continuing basis, or waters that once supported
populations of one or more fish species but no longer support fish (i.e., extirpation) due to
temporary or permanent changes in water quality (e.g., due to selenium pollution), flow or
instream habitat. Because of the inability to collect sufficient fish tissue to measure selenium
concentrations in fish in such waters, water column concentrations will best represent selenium
levels required to protect aquatic communities and downstream waters in such areas.
New inputs are defined as new activities resulting in selenium being released into a lentic
or lotic waterbody. New inputs will likely result in increased selenium in the food web, likely
resulting in increased bioaccumulation of selenium in fish over a period of time until the new or
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increased selenium release achieves a quasi-"steady state" balance within the food web. EPA
estimates that concentrations of selenium fish tissue will not represent a "steady state" for several
months in lotic systems, and longer time periods (e.g., two to three years) in lentic systems,
depending upon the hydrodynamics of a given system such as the location of the selenium input
related to the shape and internal circulation of the waterbody, particularly in reservoirs with
multiple riverine inputs, hydraulic residence time, and the particular food web. Estimates of
steady state under new or increased selenium input situations are expected to be site dependent,
so local information should be used to better refine these estimates for a particular waterbody.
Thus, EPA recommends that fish tissue concentration not override water column concentration
in these situations until these periods of time have passed in lotic and lentic systems,
respectively, or steady state conditions can be estimated.
4.1 Protection of Downstream Waters
EPA regulations at 40 CFR 131.10(b) provide that "[i]n designating uses of a waterbody
and the appropriate criteria for those uses, the state shall take into consideration the water quality
standards of downstream waters and ensure that its water quality standards provide for the
attainment and maintenance of the water quality standards of downstream waters." Especially in
cases where downstream waters are lentic waterbody types (e.g., lakes, impoundments), or
harbor more sensitive species, a selenium criterion more stringent than that required to protect
in-stream uses may be necessary to ensure that water quality standards provide for the attainment
and maintenance of the water quality standards of downstream waters.
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5 Site-specific Criteria
All four elements of the freshwater selenium criterion may be modified to reflect site-
specific conditions where the scientific evidence indicates that different values will be protective
of aquatic life and provide for the attainment of designated uses.
Since the fish egg-ovary criterion element is based on toxicity data, a state may modify
that element by applying the Recalculation Procedure (U.S. EPA 2013b) to edit the species
toxicity database to reflect taxonomic relatedness to the site assemblage, while including tested
surrogates for untested resident species.
It is important to note that species in the national data set that are not present at a site
should not be deleted from the data set because those species serve as surrogate(s) for other
species known or expected to be present at a site. Confidence in the applied tissue criterion
element can be improved by further testing of fish species resident at the site. The most relevant
testing would measure the survival and occurrence of deformities in offspring of wild-caught
female fish to determine an ECio for selenium in the eggs or ovaries (e.g., following Janz and
Muscatello 2008).
Using either the EPA national recommended egg-ovary, whole-body, or muscle criterion
concentration element or a site-specific egg-ovary, whole-body, or muscle criterion element,
translation of the fish tissue criterion to a protective water concentration can be performed in a
manner that accounts for site-specific conditions. Appendix K provides a step-wise process for
deriving each parameter used in Equation 18 to perform a site-specific translation. These steps
include:
1. selecting a target fish species for the waterbody,
2. determining the primary food source for the target species
3. determining the appropriate TTF values,
4. determining the appropriate EF value, and
5. determining the appropriate CF value.
Appendix K also provides information on the data necessary to derive a site-specific
criterion, as well as scientifically defensible methods, including the use of traditional
Bioaccumulation Factors (BAFs), in addition to the more comprehensive mechanistic modeling.
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6 Effects Characterization
6.1 Fish and Amphibians
6.1.1 Principles for Using Studies for which ECms Cannot Be Calculated
When the data from an acceptable chronic test met the conditions for logistic regression
analysis, the ECio was used. When data did not allow calculation of ECs but did allow
calculation of closely spaced NOECs and LOECs, the NOEC was used to approximate the ECio.
No NOEC values were used in calculating the tissue criterion element values.
When significant effects were observed at all treatment concentrations, such that no
treatment concentration was classified as a NOEC, then the chronic value was assigned as "less
than" (<) the lowest tested concentration. When no significant effects were observed at any
concentration, such that no treatment concentration was defined as an LOEC, then the chronic
value was assigned as "greater than" (>) the highest tested concentration.
A number of the chronic values in Sections 3.1.1 and 6.1.2 (reproductive effects) and in
Section 6.1.9 (nonreproductive effects) include a "greater than" (>) or "less than" (<) sign
because of an inability to resolve an exact value when all exposure concentrations of a study
yielded either too little or too much effect to provide a point estimate of a chronic value. The
decision to use chronic values with a "greater than" or "less than" sign in calculating an SMCV
followed a rule based on whether these values add relevant information to the mean, as described
below. None of these values were used in this assessment to derive the tissue criterion element
values.
6.1.1.1 Evaluation Approach
• Neither a low "greater than" value nor a high "less than" value were used to
calculate the SMCV;
• Both a low "less than" value and a high "greater than" value were included in the
SMCV calculation. However, none of these values were used in this assessment to
calculate the numeric criterion values for fish tissue.
For example, a chronic value reported here as ">15 mg Se/kg" is ignored if the tentative
SMCV is 20 mg Se/kg. The ">15 mg Se/kg" value indicates that no significant effects were
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observed at the study's highest tested concentration of 15 mg Se/kg. As this is consistent with
what would be expected if the SMCV were 20 mg Se/kg, it provides no information to support
modifying the SMCV. However, a different study showing no effects at its highest tested
concentration and yielding the value ">25 mg Se/kg" is not consistent with an SMCV of 20 mg
Se/kg, and indicates that the ">25 mg Se/kg" value provides information for modifying the mean
upwards. Conversely, a chronic value reported here as "<15 mg Se/kg" indicates that significant
effects were observed even at the study's lowest tested concentration of 15 mg Se/kg. As this is
not consistent with a 20 mg Se/kg SMCV, it indicates the utility of the "<15 mg Se/kg"
information for modifying the SMCV downwards. On the other hand, a value reported here as
"<25 mg Se/kg" would not be used to recalculate a 20 mg Se/kg SMCV. The intent of the
approach is to use all quality information that is relevant and appropriate for calculating the
SMC Vs.
6.1.2 Acceptable Studies of Fish Reproductive Effects of Genera that were not among the Four
Most Sensitive Genera
The following is a brief synopsis of the experimental design, test duration, relevant test
endpoints, and other critical information regarding the genera that were not the four most
sensitive but were included in the number of GMCVs in the dataset (see Section 3.1.3), The
studies in this section involve effects on the offspring of exposed female fish. Data are
summarized in Table 3.1. Details of these studies are contained in Appendix C.
6.1.2.1 Cyprinidae
Pimephales promelas (fathead minnow)
Schultz and Hermanutz (1990) examined the effects of selenium transferred from
parental fish (females) on fathead minnow larvae. The parental fathead minnows were first
exposed to selenite (10 |ig/L) that was added directly to the water in artificial streams in a
mesocosm study. The selenite entered the food web and contributed to exposure via diet.
Spawning platforms were submerged into treated and control streams. Embryos were collected
from the spawning platforms and transferred to a proportional diluter where they were reared in
incubation cups for observation. Treated embryos in the egg cups were exposed to 10 |ig/L
selenium. Edema and lordosis were observed in approximately 25 percent of the larvae spawned
and reared in natural water spiked with 10 jag Se/L and in < 6 percent of control larvae. Although
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a case can be made that the selenium treatment had a higher rate of edema and lordosis, there are
some issues that add uncertainty to the estimation of an effect concentration (R. Erickson,
personal communication). Heavy mortality/loss of embryo/larvae during monitoring and the
erratic occurrence of the abnormalities (e.g., significant incidence of edema in only 3 of 10
replicates for the Se treatment) led to the conclusion that results should not be used for criterion
derivation. The data from this study support the range of reproductive effect levels determined in
other fish studies. The Se concentration in embryos from the 10 |ig/L treatment stream of 3.91
mg/kg ww converts to 25.6 mg/kg dw using 15.3% dw (N=3 range 14.7 - 15.6%) for fathead
minnow eggs (R. Erickson, personal communication).
Two other studies suggest fathead minnows are less sensitive to selenium than other fish.
Young et al. (2010) observed that fathead minnow populations remained after selenium
contamination of Belews Lake had eliminated most other fish species, including bluegill and
largemouth bass. In a maternal transfer laboratory study with fathead minnows, GEI (2008)
estimated ECioS for larval survival and deformities that ranged from 35 -65 mg Se/kg dw
expressed as maternal whole body, as noted in Appendix E, Figures E-2 and E-3.
6.1.2.2 Esocidae
Esox lucius (northern pike)
Muscatello et al. (2006) collected spawning northern pike from four sites near a uranium
milling operation in north-central Saskatoon, Canada, with egg concentrations ranging from 2.7
to 48 mg Se/kg dw. The four sites included a reference site and three sites 2, 10 and 15 km
downstream of the effluent discharge, representing a gradient of selenium exposure. Milt and ova
were stripped from gravid fish. Eggs were then fertilized in the field and incubated in the
laboratory for observations and measurements. The test was terminated when the majority of the
fry exhibited swim-up and had absorbed the yolk.
Mean egg diameter, fertilization success and cumulative embryo mortality were not
significantly different among the sites. Significant increases in percent total deformities
including edema, skeletal deformities, craniofacial deformities and fin deformities were observed
in fry originating from pike collected at the medium exposure site. The concentrations of
selenium in the northern pike eggs collected at the reference and low exposure site were very
similar, as were the percent total deformities in embryos/fry. The geometric mean of selenium in
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the eggs of the adult females at the reference and low exposure sites was 3.462 mg Se/kg dw and
the corresponding arithmetic mean of the percent total deformities was 13.20%. There were only
4 adult females from exposed sites, and all had relatively similar concentrations in their eggs, all
close to the geometric mean concentration of 34.00 mg Se/kg dw. Likewise, all four exposed
females had relatively similar percent total deformities, not far from their arithmetic mean of
33.40%. This is not a sufficient level of effect for applying TRAP to determine an ECio.
Furthermore, the relatively large spread between the two clusters of exposure concentrations
(3.462 and 34.00 mg Se/kg dw) would render a NOEC and LOEC unreliable and unsuitable for
defining a threshold. That is, the NOEC and LOEC would be "greater than" and "less than"
values, >3.462 and <34.00 mg Se/kg dw respectively, providing little information on the
sensitivity of northern pike compared to other species.
Instead, making use of the clustering of data at low exposure and effects and at elevated
exposure and effects, the effect level for the elevated exposure eggs was normalized to the low
exposure condition and rescaled to a 0-100% range. The rescaled (i.e., Abbott-adjusted) percent
of total deformities for the elevated exposure eggs was 24% (relative to the low exposure eggs).
Thus the concentration of selenium in the elevated exposure eggs (34 mg Se/kg dw) was
equivalent to an EC24, and is the only effects concentration that can be calculatedfor this test,
given the limitations in the range of concentrations tested and effects observed. Although the
EC24 is not directly translatable to an EC10 for use in determining the criterion, it is useful for
comparison with the EC24 in other species in order to determine species sensitivity rank. The
EC24 for skeletal deformities from the Holm et al. (2005) study of rainbow trout, calculated to be
30.9 mg Se/kg dw in eggs, is slightly lower than the northern pike value, indicating these two
species may be similar in tolerance, with the northern pike being slightly more tolerant (see
Appendix C for more details.)
6.1.2.3 Salmonidae
Seven publications provide quantitative data on the effects of selenium on salmonid
embryo/larval survival and deformity that were used in calculating criterion values. All involve
wild-caught adults taken from selenium contaminated streams and spawned for effects
determination. Exposure for all studies was therefore through the parents. Data are available for
rainbow trout (Oncorhynchus mykiss), cutthroat trout (1Oncorhynchus clarkii), Dolly Varden
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(,Salvelinus malma) and brown trout (Salmo trutta). The studies with Salvelinus are discussed
below; Oncorhynchus and Salmo were previously discussed in Section 3.1.2,
Salvelinus fontinalis (brook trout)
These data were not used directly in the criterion calculations. See Section 6.1.5 for
discussion of the available data.
Salvelinus malma (Dolly Varden)
Golder (2009) collected adult Dolly Varden from a reference site and two sites
downstream from the Kemess Mine in northern British Columbia, one with a high and one with a
moderate selenium exposure in the fall of 2008. Fertilized eggs were taken to the laboratory
where they were monitored for survival and deformities until 90% of the larvae reached swim-
up, approximately five months after fertilization. Alevin mortality was <1% in the treatments
collected from the exposed sites and not considered an effect. The prevalence of deformities
increased sharply after the selenium egg concentration exceeded 50 mg/kg dw (Appendix C).
The proportion of Dolly Varden larvae without any type of deformity (skeletal, craniofacial, and
finfold as well as edema), as a function of the log of the selenium concentration in the eggs using
TRAP, produced an EC io value of 56.22 mg Se/kg dw and an EC20 value of 60.12 mg Se/kg dw.
6.1.2.4 Salmonidae SMCV and GMCV Summary
As given in Section 3.1.2, the SMCV for cutthroat trout, Oncorhynchus clarkii, is 26.2
mg Se/kg dw in eggs derived from Rudolph et al. (2008), and Nautilus Environmental (2011),
(24.7, and 27.7 mg Se/kg dw respectively). The GMCV for the genus Oncorhynchus is 25.3 mg
Se/kg dw in eggs, derived from the 24.5 mg Se/kg dw EC10 from the combined Holm (2002) and
Holm et al. (2005) rainbow trout data, the above mean of the Rudolph et al. (2008) and Nautilus
Environmental (2011) Westslope cutthroat trout studies. The GMCV for the genus Salvelinus is
the EC10 value of 56.22 mg Se/kg dw for Dolly Varden (S. malma) from the Golder (2009) study.
6.1.2.5 Poeciliidae
Data are available for two species in this family. These studies are not represented in
Table 3.1 because they are live-bearing rather than egg-laying, but the relative tolerance of these
species is accounted for in derivation of the criterion.
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Gambusia holbrooki (eastern mosquitofish)
Staub et al. (2004) collected male and gravid female eastern mosquitofish from a
contaminated ash basin and a reference pond in July 1999. Male fish were used for measuring
standard metabolic rate and the reproductive endpoints. Brood size and percent viability of live
offspring at parturition were measured using the live-bearing females. Standard metabolic rates
of males, brood size of females, and offspring viability were not significantly different between
sites. Average concentrations of selenium in females were 11.85 and 0.61 mg/kg dw in the
contaminated ash basin and reference sites, respectively. The chronic value in whole body tissue
is >11.85 mg Se/kg dw whole-body (Appendix C). In a community of equally exposed fish taxa
(fish taxa having whole body tissue concentrations >11.85 mg Se/kg dw), the median egg-ovary
concentration among egg-laying fish would be expected to be 1.71 higher, or >20.26 mg Se/kg
dw.
Gambusia affinis (western mosquitofish)
Western mosquitofish were collected in June and July 2001 from sites in the grassland
water district in Merced County, California. Mosquitofish were collected from two sites that
were contaminated with selenium and from two reference sites in the same area with relatively
low selenium water concentrations (Saiki et al. 2004). Seventeen to 20 gravid females
(mosquitofish are live-bearers) from each site were held in the laboratory for two weeks to
quantify live and dead births and to make other measurements. Live and dead fry were visually
examined under low magnification with a binocular microscope for evidence of external
abnormalities (teratogenic symptoms such as spinal curvature, missing or deformed fins, eyes
and mouths and edema). The percentage of live births was high at both selenium-contaminated
sites (96.6 to 99.9%) and reference sites (98.8 to 99.2%). There were no obvious anomalies (e.g.,
deformities, edema) observed during the study. The concentration of selenium in four postpartum
females from the site with the highest selenium concentration ranged from 13.0 to 17.5 mg Se/kg
dw (geometric mean of the high and low is 15.1 mg Se/kg dw). The chronic value in whole body
tissue is >15.1 mg Se/kg dw (Appendix C). Similar to Staub et al. (2004), this value can be
converted to egg-ovary concentrations that would be expected in accompanying egg-laying fish,
by multiplying by the median fish egg-ovary to whole-body concentration ratio, 1.71. This yields
a >25.82 mg Se/kg dw equivalent egg-ovary concentration.
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Gambusia, which have been reported to be tolerant to selenium contamination, are often
one of the few remaining species at sites with high levels of selenium contamination (Cherry et
al. 1976; Lemly 1985a; Saiki et al. 2004; Young et al. 2010; Janz et al. 2010). The two studies
discussed above support this observation with a GMCV of >13.4 mg Se/kg dw in whole body
tissue, combining these "greater than" values as described in Section 6.1.1, It may be concluded
that this genus is not among the most sensitive to selenium.
6.1.2.6 Cyprinodontidae
Cyprinodon macularius (desert pupfish)
Besser et al. (2012), using a diet of oligochaete Lumbriculus that had fed on selenized
yeast, exposed desert pupfish to six levels of dietary and waterborne selenium. Five-week old
juveniles (Fo) were exposed for 85 days, during which time survival and growth were measured.
Upon reaching maturity at the end of this exposure period, the 60-day reproductive study was
begun, during which Fi eggs were collected, counted, and further tested for percent hatch,
survival, growth, and deformities. The authors observed no significant differences in pupfish
survival, growth, total egg production, hatch, or deformities among treatments. Although the
authors noted a potential interaction between the timing of egg production and treatment, a
comprehensive re-analysis of this data, described in Appendix C, indicated that the phenomenon
was neither statistically nor biologically significant. It is concluded that the egg concentration, 27
mg Se/kg (dw), for the test's highest treatment was not sufficiently high to define a
concentration-response curve. Although desert pupfish is thus not among the most sensitive
species, the slightly reduced survival observed at 27 mg Se/kg egg dw egg suggests that the ECio
may be close to that concentration, as also noted by the authors.
6.1.2.7 C entrarchi dae
Micropterus salmoides (largemouth bass)
A laboratory study was conducted by Carolina Power & Light (1997) in which adult
largemouth bass obtained from a commercial supplier were fed an artificial diet spiked with a
gradient of selenomethionine concentrations for several months. Approximately 100 eggs from
each spawn were monitored for mortality and deformities up to the larval swim-up stage. The
authors combined survival and deformities into a single metric (i.e., survival as normal
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offspring). The average concentration of selenium in the ovaries ranged from 3.1 mg/kg dw in
the control to 77.6 mg/kg dw in the high dietary treatment (53.1 mg/kg dw). A plot of the percent
survival of larval largemouth bass as a function of the selenium concentration in the parental
female ovary shows two groups of data; one at background survival with considerable variability
(mean 90.3%, standard deviation 10.9%) and one with <10% survival, with most of the data
being at 0% survival (see Microplerus summary in Appendix C, Figure 1). Due to inadequate
partial effects, a TRAP interpolation was used to estimate an ECio value. Based on a risk
management decision that the LOEC cannot be any higher than the lowest concentration with 0%
survival (32.9 mg/kg) and that any ECx should be below this, this establishes the higher
concentration point for the interpolation (an ECioo of 32.9 mg/kg) and requires that the highest 4
NOECs not be considered in setting the ECo. The lower concentration point for the interpolation
is therefore set here to 24.6, the next highest NOEC with greater than the average 90.3%
background survival. This results in an ECio of 26.3 mg/kg (and a steep slope of 16). Please see
Appendix C for more detailed information.
6.1.3 Reproductive Effects in Catfish (Ictaluridae)
Some important families of fish are not represented in the effects assessment, such as the
catfish family (Ictaluridae). In their compilation of egg-ovary versus whole-body ratios,
Osmundson et al. (2007) found comparatively high concentrations of selenium in egg-ovary
compared to whole body in black bullhead, Ameiurus melas, which are related to the Ictaluridae.
This raises a question about the potential risks of reproductive effects in this species and possibly
in related Ictaluridae. In addition to this concern about how much selenium such species may
accumulate in their eggs, U.S. Fish and Wildlife Service (2005) has suggested that offspring of
channel catfish (Ictaluruspunctatus) and related species might be affected at unusually low egg
concentrations. This is based on results of a study in which adult female catfish were injected
with seleno-L-methionine (Doroshov et al. 1992b). Effects were found in the offspring at egg
concentrations between 3.2 mg/kg (NOEC) and 6.3 mg/kg (LOEC), below levels observed in the
studies summarized in Section 3.1.2 and documented in Appendix C. These data were not
included in derivation of the criterion because the injection route of exposure is not an acceptable
experimental protocol for studies used in criterion derivation due to its difference from exposure
routes in the environment (water column and diet).
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In the absence of valid tests yielding an Ictaluridae ECio or chronic value, EPA evaluated
the potential vulnerability of the taxonomic group that includes catfish by examining
comparative fisheries observations of Ictaluridae and Centrarchidae sharing the same selenium-
contaminated water body. Crutchfield (2000) reports results of annual cove rotenone sampling
performed from 1982 to 1997 in Hyco Reservoir, North Carolina. The sampling was begun after
centrarchid populations in this reservoir had collapsed due to the release of ash pond selenium
from a coal-fired power plant. The plant began operating a dry fly ash handling system in
January 1990, thereby eliminating the aquatic discharge of selenium; the sampling continued
through the recovery period.
Crutchfield (2000) reports abundance data (kg/ha) for 20 fish taxa, including four
Ictaluridae and three Centrarchidae. These data were examined to determine the relationship
between the Ictaluridae and the selenium-affected Centrarchidae populations. The correlation
matrix between annual measured abundance of the seven taxa is shown below in Table 6.1.
Correlation with the reciprocal of measured average concentrations of selenium in invertebrates
is also shown. Because the reciprocal of the selenium concentration is used, a positive correlation
means that abundance decreases as selenium concentration increases. Conversely, a negative
correlation means abundance decreases as selenium concentration decreases.
Table 6.1. Correlation Matrix (Values of r) for Ictaluridae and Centrarchidae Abundance
and for Selenium Food Chain Contamination for the Hyco Reservoir.
(Data Reported by Crutchfield 2000).
Ictaluridae
("enlrarchidae
1 .aiue-
I'omoxis
("humid
While
Hal
. \mcimns
111 CHI I ll
SPP
1 1 n\ erleh
catfish
catfish
hull head
spp
IJIueui
II hass
(crappie)
Se Cone
Channel catfish
1.00
-0.36
0.18
0.68
0.08
-0.33
-0.08
-0.44
White catfish
-0.36
1.00
0.02
-0.32
-0.31
-0.24
-0.15
-0.06
Black bullhead
0.18
0.02
1.00
0.40
0.32
-0.08
0.08
-0.03
Ameiurus spp.
0.68
-0.32
0.40
1.00
0.22
-0.24
-0.05
-0.31
Bluegill
0.08
-0.31
0.32
0.22
1.00
0.78
0.76
0.80
Largemouth bass
-0.33
-0.24
-0.08
-0.24
0.78
1.00
0.78
0.92
Pomoxis spp.
(crappie)
-0.08
-0.15
0.08
-0.05
0.76
0.78
1.00
0.69
1 Inverteb.
Se Cone.
-0.44
-0.06
-0.03
-0.31
0.80
0.92
0.69
1.00
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The centrarchid abundances are well correlated with each other and are closely related to
selenium concentrations in the food chain, with fish abundance decreasing as selenium
concentrations increase. Ictaluridae abundances, however, are unrelated either to the selenium-
sensitive centrarchid abundances or to the selenium concentrations in the food chain.
Figure 6.1 shows abundance as both mass and numbers of individuals of channel catfish
(CCF) and largemouth bass (LMB) observed by Crutchfield (2000) during the period 1982-1997.
Both species are long lived. Crutchfield (2000) notes that the decline of reproductive success and
abundance of Hyco's largemouth bass (and bluegill) was first documented in the mid-1970s.
Because this study was initiated after the largemouth bass recreational fishery had collapsed,
Figure 6.1 does not show the largemouth bass decline, only the period of its depression and
subsequent recovery.
Numbers of largemouth bass were very low at the beginning of the study period; their
numbers and mass do not begin to recover until invertebrate selenium drops below 30 mg Se/kg
dw. In the later portion of the study period, 1989-1997, largemouth bass numbers and mass
increase 100-fold. These observations are fully consistent with the premise that the earlier
observations of elevated selenium concentrations had been impairing reproduction of largemouth
bass.
In contrast, the ups and downs of channel catfish numbers, mass, and size seem to vary
randomly throughout the period of study. In 1984 catfish numbers reached their third highest
value while their average size was at its minimum: that is, there were many young individuals.
Simultaneously, largemouth bass was near its minimum for both numbers and mass. The next
year (1985) catfish numbers jumped to their maximum for the study period, and mass reached
near maximum. Such observations are easily explained if reproduction is taking place. But they
seem inexplicable under a premise that channel catfish reproduction was even more impaired
than largemouth bass reproduction, and its population merely a senescent non-reproducing
remnant of the pre-contamination population. Rather the observations indicate that if selenium
was having any effect on catfish reproduction, it was far less than on largemouth bass
reproduction and was no hindrance to rapid population increases.
Observations of selenium-contaminated Belews Lake accord with the above observations
of Hyco Reservoir. Young et al. (2010) indicate that as many as 29 resident fish species were
documented prior to contamination, but only common carp, catfish, and fathead minnows
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remained after contamination. The Doroshov et al. (1992b) injection study results suggesting that
channel catfish is sensitive at egg concentrations of 5 mg Se/kg dw, four-fold below the
largemouth bass Chronic Value, thus conflict with field observations. As demonstrated in the
Appendix C discussion of the Cleveland et al. (1993) toxicity tests with juvenile bluegill, the
exposure route by which selenium was accumulated can have a dramatic influence on the
potency of a given tissue concentration. That is, to accord with the Cleveland et al. (1993) data,
the whole-body EC50 would be expected to be at least four-fold higher when accumulated via
diet than when accumulated via water. For this reason, the criterion is derived only from tests
using the environmentally relevant exposure route of diet.
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400
300
200
100
0
•CCF N/ha
LMB N/ha
/\ '
/ x-"
1982
1984 1986 1988 1990 1992 1994 1996
CCF kg/ha
LMB kg/ha
1982 1984 1986 1988 1990 1992 1994 1996
0.5
fi0.4
a>
N
In
<
0.3
CCF kg/N
1982
1984 1986
1988 1990
1992
1994 1996
txo
*3o
80
60
20
Tilapia All treatment
Reinitiation of bass
accidently processes
tournaments 1994.
introduced, operational,
CCF and LMB
1984 , early 1990
consumption ad-
visories lifted 1995.
Invertebrate Se Cone
i i i i i i i
1982
1984 1986 1988 1990
1992
1994 1996
Figure 6.1. Crutchfield (2000) Observations of Channel Catfish (CCF) and Largemouth
Bass (LMB) in Hyco Reservoir Beginning a Few Years after Populations of Largemouth
Bass had been Reduced by Se Contamination.
(A) number of individuals/ha, (B) mass/ha, (C) mass/ha divided by number/ha, yielding average
weight per individual, and (D) invertebrate Se concentration (mg Se/kg dw), and noting other
events relevant to management of the fishery.
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6.1.4 Reproductive Effects in Amphibians (Xenopus laevis)
Masse et al. (2015) has conducted the only maternal transfer study conducted with an
amphibian under controlled laboratory conditions. The African clawed frog {Xenopus laevis) was
fed a control diet (0.73 mg/kg Se dw) and three spiked diets containing selenium concentrations
of 10.92, 30.4 and 94.2 mg/kg dw. Trophic transfer to the frog's eggs was approximately 1:1
with measured selenium concentrations in the control and three spiked diets of 1.6, 10.82, 28.13,
and 81.66 mg/kg egg dw, respectively. Deformities were assessed in 200 tadpoles per female
(1800 - 2000 tadpoles per treatment group). ECio values determined by the authors for abnormal
spinal curvature, abnormal craniofacial structure and abnormal lens structure were 57.3, 38.4,
and 34.5 mg/kg Se egg dw, respectively. The ECio value for total deformities of 44.9 mg/kg Se
egg dw is in the upper-range of ECio values for fish (see Table 3.2). Although X laevis is a non-
native amphibian with a different reproductive strategy, their upper-range sensitivity suggests
amphibians are protected by the fish chronic criterion elements.
6.1.5 Reproductive Studies Not Used in the Numeric Criterion Derivation
Danio rerio (zebrafish)
Two studies (Penglase et al. 2014; and Thomas and Janz 2014) have shown the zebrafish,
Danio rerio (family Cyprinidae), to be sensitive to selenium. Penglase et al. (2014) assessed the
interaction of selenium with mercury through a maternal transfer study but did have two
treatments with selenium exposures resulting in 1.17 mg/kg egg dw (control) and 6.24 mg/kg egg
dw. The higher Se egg concentration had significantly reduced embryo survival and fecundity
relative to the control, however embryo survival in the controls was low at 54%. With only one
selenium treatment exposure, the data were not amenable to TRAP analysis. Thomas and Janz
(2014) conducted a maternal transfer study using adult zebrafish that were fed a control diet and
three levels of selenomethionine, 3.7, 9.6, and 26.6 mg/kg Se dw for 90 days before breeding the
exposed fish and collecting the fertilized embryos for assessment. TRAP analysis of larval
survival and larval deformities of 2-6 days post fertilization fish produced very low ECio values.
The lowest ECio was for deformities at 7.0 mg/kg egg dw. This value is markedly lower than any
of the ECio's in the current data set. The slope of the concentration-response curve for both
deformities and larval survival was very shallow, which was different than the selenium
responses for all other fish species for which data were available (see Figure E-6 in Appendix E).
Further, the control mortality in the experiment continuing over 160 days was high, over 40%.
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This zebrafish ECio for deformities contrasts with the absence of deformities in the
related species, fathead minnow, observed by GEI (2008) at concentrations up 40 mg/kg in adult
whole body (dw) as presented in Figure E-3 in Appendix E. The GEI (2008) fathead minnow
study was not directly used for criterion derivation because the offspring survival data for Sand
Creek appeared to be confounded by multiple stressors in this industrial waterway. However, its
deformity data appear unequivocal, indicating that the fathead minnow deformity endpoint is
relatively insensitive to selenium.
Since the zebrafish is a non-native cyprinid species, EPA assessed the information
available on zebrafish sensitivity to selenium compared to the sensitivity of native cyprinid
(minnow) species across the U.S. (Appendix E in the 2016 criterion document), including several
studies where native cyprinids were investigated in selenium-impacted waters (NAMC 2008).
Data from these studies suggest that native cyprinids are likely less sensitive to selenium than the
non-native zebrafish.
The anomalous nature of the concentration-response curve, with the very low value
coupled with field and other laboratory data suggesting that cyprinids are not particularly
sensitive to selenium was the basis for not including the zebrafish ECio in the data for deriving
the criterion. A detailed write up of this study and a summary of field and laboratory studies
indicating native cyprinids are not one of the more sensitive families are provided in Appendix
E.
Oncorhynchus clarkii (cutthroat trout)
Kennedy et al. (2000) reported no significant differences in mortality and deformity in
eggs, larvae, and fry from wild-caught cutthroat trout between a reference and an exposed site
(Fording River, British Columbia, Canada). The observations were made on eggs reared in well
water from spawning age females collected from the two locations (N = 17 and 20, respectively)
and fertilized by one male collected at each site. The mean selenium content in eggs from fish
collected from the reference site was 4.6 mg/kg dw and from fish collected from the Fording
River was 21.2 mg/kg dw. The chronic value for eggs is >21.2 mg Se/kg dw. These values were
not used in the criterion derivation because they represent high "greater than" values, as
discussed above, and provide no additional important quantitative data for the analyses.
Hardy (2005) fed cutthroat trout experimental diets containing a range of
selenomethionine (0-10 mg/kg dw) for 124 weeks. No significant growth or survival effects were
117
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observed in the adult fish over the 124 weeks. The whole body concentration reached 12.5 mg/kg
dw selenium after 44 weeks. Embryo-larval observations (percent hatch and percent deformed)
were not related to whole body selenium concentrations in the spawning females (9.37 mg/kg
dw) fed the selenium-laden diet for 124 weeks. The concentration of selenium in eggs from these
females was 16.04 mg/kg dw. For this study the chronic value, an unbounded NOEC, is thus
>16.04 mg Se/kg dw in eggs. This value was not used in the criterion derivation.
Salvelinus fontinalis (brook trout)
Holm et al. (2005) collected spawning brook trout from streams with elevated selenium
contaminated by coal mining activity and from reference streams in 2000, 2001 and 2002.
Similar to procedures described by these authors for rainbow trout, above, fertilized eggs were
monitored in the laboratory for percent fertilization, deformities (craniofacial, finfold, and spinal
malformations), edema, and mortality. Embryos from the contaminated stream had on average a
higher frequency of craniofacial deformities than fry from the reference stream (7.9% for the
contaminated stream compared to 2.1% in the reference stream). Although this increased rate of
craniofacial deformities was calculated to be statistically significant when compared across sites,
the Abbott-adjusted effect is only 6% and is thus below the 10% effect represented by an ECio.
But more important, when comparing across adult females (the more reliable analysis for
selenium reproductive toxicity studies of this type, and the one used to obtain the related rainbow
trout ECio for these authors' studies), there is no apparent relationship between brook trout
craniofacial deformities and exposure across a broad range of concentrations, as illustrated in
Appendix C. An environmentally conservative estimate of the NOEC might be considered to be
the average concentration of selenium in eggs from the high exposure site (Luscar Creek), >7.78
mg Se/kg ww or >20.5 mg Se/kg dw using the 61.2% moisture content for rainbow trout eggs
cited above. However, the effect threshold appears to be substantially higher based on the
absence of any consistent concentration-response relationship up to the maximum observed egg
concentration of 18.9 mg Se/kg ww or 48.7 mg Se/kg dw, as shown in the Appendix C graphs.
Given the point estimate ECio available for the related species, Salvelinus malma (Dolly Varden,
Section 6.1.2.3), the "greater than" chronic value for brook trout is not used to obtain the
GMCV, in accordance with the principles listed in Section 6.1.1,
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Lepomis macrochirus (bluegill)
Applicable chronic reproductive data for bluegill can be grouped by exposure type: field
and laboratory. In some field studies, chronic value estimates were "less than" fairly high
selenium concentrations (Bryson et al. 1984, 1985a; Gillespie and Baumann 1986). This low
resolution is due to the observed effect occurring at a single observed high exposure
concentration relative to a reference condition. In the Bryson et al. (1984, 1985a) and Gillespie
and Baumann (1986) studies, the artificially crossed progeny of females collected from a
selenium contaminated reservoir (Hyco Reservoir, Person County, NC) did not survive to swim-
up stage, irrespective of the origin of milt used for fertilization. Measured waterborne selenium
concentrations prior to the experiments ranged from 35 to 80 |ig/L. The ovary tissue selenium
concentration associated with this high occurrence of mortality of hatched larvae was <30 mg/kg
dw tissue, as reported by Bryson et al. (1985a), and <46.30 mg/kg dw tissue, as reported by
Gillespie and Baumann (1986). In the case of the latter, nearly all swim-up larvae from the Hyco
Reservoir females were edematous, none of which survived to swim-up.
Bryson et al. (1985b) examined percent hatch and percent swim-up larvae from spawns
using bluegills collected from Hyco Reservoir and a control site. There were no differences in
the Hyco measurements relative to the control. The concentration of selenium in the liver of the
parental Hyco bluegill was 18.6 mg/kg dw. The chronic values for this embryo-larval
development test was >18.6 mg Se/kg dw liver. The high "less than" and low "greater than"
chronic values obtained from Bryson et al. (1984, 1985a, b) and Gillespie and Baumann (1986)
were not used in the SMCV calculation because these values are consistent with and yet provide
no numeric basis for modifying the SMCV obtained from the ECioS.
6.1.6 Salmo GMCV: EPA Re-analysis of a Key Study Used in Criterion Derivation
Previously, in the draft selenium criterion document submitted for external peer review in
May 2014, the lowest GMCV in the reproductive effects dataset was for Salmo (15.91 mg/kg
dw) based on larval deformities. Subsequently, in 2015, EPA conducted a careful re-analysis in
response to stakeholder comments to confirm the validity of the approach used in 2014, resulting
in the calculation of an ECio at 18.09 mg/kg dw based on larval mortality from hatch through
swim up, prior to a lab overflow accident during the post swim up feeding portion of the test.
The dataset was constrained to hatch through swim up information due to uncertainty introduced
by the loss of larvae from an overflow event caused by clogged drains during the post swim-up
119
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portion of the test (Formation 2011). The hatch through swim up deformity endpoint was not
considered because of the preferential selection of visibly non-deformed fish for the post swim
up portion of the test (Response letter to EPA, J.R. Simplot Company 2014). This is important
because the primary endpoint of interest during the post-swim up phase is deformity rate.
Random selection of living fish would have been more appropriate since visibly healthy fish may
be less likely to express deformities in this later stage of the test.
Following the release of the 2015 draft selenium criterion document, the larval survival
from hatch through swim up dataset was reanalyzed, and it was determined that the TRAP model
resulting in an ECio of 18.09 mg/kg was not appropriate, because the ECio was lower than one of
the treatment levels within the background no-effect range. In order to calculate an ECio that
would not fall below the highest background concentration, a weighted least squares nonlinear
regression was calculated in TRAP, resulting in an ECio of 21.0 mg/kg. Additional details
describing this weighted nonlinear regression approach are described in Appendix C.
6.1.7 Impact of Number of Tested Species on Criterion Derivation
Many of the species used for testing the toxicity of selenium are those observed to be
affected at contaminated sites or otherwise suspected to be particularly sensitive. Six of the eight
minimum data requirements were met, and the other two (for planktonic and benthic crustaceans)
were waived (see Section 2.6). Of the N=15 genera used for the calculation of the criterion, ten
are fish, which are more sensitive than invertebrates, based on the available data. Of the ten fish
genera, five are either salmonids or centrarchids. Had a broader array of expected insensitive
taxa been included, the four most sensitive genera would not likely change, but N would
increase. The criterion calculation for selenium is relatively insensitive to the effect of increasing
the value of N by adding more tests with different genera than those already represented. Setting
N=20 (leaving the four most sensitive the same) would only raise the egg-ovary criterion element
from 15.1 mg Se/kg to 16.0 mg Se/kg. This insensitivity occurs because the four lowest GMCVs
are closely spaced, such that the calculated egg-ovary criterion element is never distant from the
lowest GMCV.
6.1.8 Comparisons between Concentrations in Different Tissues
Researchers often report concentrations of selenium in fish eggs or ovaries (e.g.,
Formation Environmental 2011, 2012; Holm et al. 2005; Osmundson et al. 2007). Osmundson et
120
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al. (2007) found reduced levels of selenium in ovaries after spawning, presumably due to the loss
of selenium through spawning and release of eggs with relatively high concentrations of
selenium. Of the 14 chronic values determined from the maternal transfer reproductive studies,
12 values represent selenium measured in eggs. Two values represent selenium measured in the
ovaries: Hermanutz et al. (1992, 1996) and Carolina Power & Light (1997). Hermanutz et al.
(1992, 1996) sampled adult female bluegill just prior to spawning and at the end of the test (post
spawning) and found no decreases in the concentration of selenium in the post-spawned fish. In
the Carolina Power & Light (1997) study, selenium in ovaries of largemouth bass was measured
from fish sampled just after spawning. No comparison to prespawning fish or selenium in eggs
can be made for the largemouth bass study, however, the ECio of 26.3 mg Se/kg ovary dw was
mid-range in the SSD indicating this test was not overly conservative due to lower selenium
measurements in post spawning ovaries. Based on the observations stated above, egg selenium
and ovary selenium were considered equal for the toxicity data set. Any potential error resulting
from this assumption would be conservative since the effect of spawning only lowers the
selenium concentration in the ovary. EPA recognizes selenium ovary concentrations may vary in
field collected samples due to fish reproductive cycles and will address such concerns in the
implementation information.
6.1.9 Studies of Non-Reproductive Effects
Non-reproductive effect studies do not involve effects on the offspring of exposed female
adults, and their results are not expressed as selenium concentrations in egg or ovary tissue.
Because selenium concentrations in whole body and muscle are generally lower than in egg and
ovary, with observed egg-ovary to whole-body ratios ranging from 1.3 to 7.4, and egg-ovary to
muscle ratios ranging from 1.0 to 5.8, whole-body, muscle, and egg-ovary effect concentrations
can only be compared after accounting for the inherent differences in the selenium
concentrations in these different media. Non-reproductive effects were determined to provide a
less reliable basis for a criterion, in part because comparatively few of such studies provided
sigmoidal concentration-response curves. Non-reproductive SMCVs and GMCVs are shown in
Table 6.2 below and summaries of the acceptable non-reproductive studies are included in
Appendix D.
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Table 6.2. Freshwater Chronic Values from Acceptable Tests - Non-Reproductive Endpoints.
(Parental Females Not Exposed).
l'l\poMirc mule
Toxicologic;!!
Chronic Y;iluc
SMCY
CM( V
Species
Reference
iiiid (lui'iilioii
Selenium Itiriii
cndpoinl
niii/kii (In ''
m;*/kg (Im
nig/kg (In
Acipenser
transmontanus
white sturgeon
Tashjian et al.
dietary (lab)
seleno-L-methionine in
artificial diet
ECiojuvenile growth
15.08 WB
27.76 M
ECio
15.1 WB
27.8 M
15.1 WB
2006
8 weeks
seleno-L-methionine in
artificial diet
EC2o juvenile growth
17.82 WB
32.53 M
ec20
17.8 WB
32.5 M
27.8 M
NOEC
10.1 M
Pogonichthys
dietary (lab)
9 months
LOEC
15.1 M
10.1 M
10.1 M
macrolepidotus
Sacramento splittail
Teh et al. 2004
selenized-yeast
MATC juvenile
deformities (juvenile
exposure only)
12.34 M
15.1 M
12.3 M
15.1 M
12.3 M
Pimephales promelas
fathead minnow
Bennett etal. 1986
dietary (lab)
9 to 19 days
algae exposed to selenite
then fed to rotifers which
were fed to fish
Chronic value for
larval growth
51.40 WB
51.40 WB
69.83 M
51.40 WB
69.83 M
Pimephales promelas
fathead minnow
Dobbsetal. 1996
dietary and
waterborne
(lab)
8 days
algae exposed to selenate
in water then fed to
rotifers which were fed
to fish
LOEC for larval fish
dry weight after 8 d
<73 WBb
water: selenate; diet:
Xyrauchen texanus
razorback sucker
Beyers and
Sodegren 2001a
dietary and
waterborne (lab)
28 days
algae exposed to selenate
in water then fed to
rotifers which were fed
to fish
NOEC for survival
and growth
>12.9 WBb
see text
see text
Xyrauchen texanus
razorback sucker
Beyers and
Sodegren 2001b
dietary and
waterborne (lab)
28 days
water: site waters; diet:
algae exposed to site
water then fed to rotifers
which were fed to fish
NOEC for survival
and growth
>42 WBb
water: selenate;
Catostomus latipinnis
flannelmouth sucker
Beyers and
Sodegren 2001a
dietary and
waterborne (lab)
28 days
diet: algae exposed to
selenate in water then
fed to rotifers which
were fed to fish
NOEC for survival
and growth
>10.2 WB
>10.2 WB
>10.2 WB
Oncorhynchus
tshawytscha
Hamilton et al.
1990
dietary (lab)
60 days
mosquitofish spiked with
seleno -DL-methionine
ECio for juvenile
growth
7.355 WB
ECio
9.052 WB
ECio
9.052 WB
122
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Species
Keleivnce
l'l\poMirc mule
iiiid (lui'iilioii
Selenium I n nil
Toxicologic;!!
cndpoinl
C hronic Y;iluc
niii/kii (In ''
SMCY
nii*/kK cl«
CM( V
m«/k*i (l\\
chinook salmon
EC20 for juvenile
growth
10.47 WB
ec20
12.83 WB
mosquitofish spiked with
SLD diet
ECio for juvenile
growth
11.14 WB
EC20 for juvenile
growth
15.73 WB
Oncorhynchus mykiss
rainbow trout
Hilton and Hodson
1983;
Hicks et al. 1984
dietary (lab)
16 weeks
sodium selenite in food
preparation
juvenile growth
NOEC
21 Liver
NOAEC
28.98 L
LOAEC
84.68 L
MATC
49.52 L
LOEC
71.7 Liver
MATC
38.80 Liver
Oncorhynchus mykiss
rainbow trout
Hilton etal. 1980
dietary (lab)
20 weeks
sodium selenite in food
preparation
juvenile survival and
growth
NOEC
40 Liver
LOEC
100 Liver
MATC
63.25 Liver
Morone saxitilis
striped bass
Coughlan and
Velte 1989
dietary (lab)
80 days
Se-laden shiners from
Belews Lake, NC
LOEC for survival of
yearling bass
<16.2 Mc
<16.2 M
<16.2 M
Lepomis macrochirus
bluegill
Lemly 1993a
dietary and
waterborne (lab)
180 days
20 to 4°C
diet: seleno-L-
methionine
water: 1:1
selenate: selenite
LOEC for juvenile
mortality at 4°C
<7.91 WB
4°C
ECi o-NO AEC
8.15 WB
4°C
ec20-loaec
8.80 WB
9°C ECio
14.0 WB
9°C EC20
14.6 WB
4°C & 9°C
9.33 WB
Threshold prior to
"winter stress"
5.85 WB
dietary and
waterborne (lab)
180 days 20°C
diet: seleno-L-
methionine
water: 1:1
selenate: selenite
NOEC for juvenile
mortality at 20°C
>6.0 WB
Lepomis macrochirus
bluegill
Mclntyre et al.
2008
dietary and
waterborne (lab)
182 days
20 to 4°C (ESI)
diet: Lumbriculus fed
selenized-yeast
water: 1:1
selenate: selenite
ECiojuv. survival
ESI
9.27 WB
EC20juv. survival
ESI
9.78 WB
dietary and
waterborne (lab)
182 days
20 to 9°C (ES3)
diet: Lumbriculus fed
selenized-yeast
water: 1:1
selenate: selenite
ECiojuv. survival
ES3
14.00 WB
EC2ojuv. survival
ES3
14.64 WB
dietary and
waterborne (lab)
182 days
20 to 4°C (ES2)
diet: seleno-L-
methionine
water: 1:1
selenate: selenite
NOEC juv. surv. ES2
>9.992 WB
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Species
Reference
l'l\poMirc mule
iiiid (lui'iilioii
Selenium Itiriii
Toxicologic;!!
cndpoinl
Chronic Y;iluc
niii/kii (In ''
SMCV
m;*/kg (Im
c;mcy
nig/kg (In
Lepomis macrochirus
bluegill
Bryson et al.
1985b
dietary (lab)
60 days
seleno-DL-cysteine
NOEC for juvenile
growth
>3.74 WBb
Lepomis macrochirus
bluegill
Cleveland et al.
1993
dietary (lab)
90 days
seleno-L-methionine
NOEC for juvenile
survival
>13.4 WBb
All chronic values reported in this table are based on the measured concentration of selenium in whole body (WB), muscle (M)
or liver (L) tissues.
Chronic value not used in SMCV calculation (see text).
Tissue value converted from ww to dw. See Appendix C for conversion.
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6.1.9.1 Comparison of Fish Chronic Reproductive Effects and Chronic Non-Reproductive
Effects
A chronic criterion element concentration of 15.1 mg/kg dw in the egg/ovary addresses
the toxic effect identified by the Chapman et al. (2009, 2010) expert workshop to be of greatest
concern, reproductive effects, and is expected to be protective of non-reproductive endpoints
such as juvenile survival and growth.
If the information in the reproductive-effect GMCV Table 3.2 (expressed as whole-body)
were combined with the information in the nonreproductive-effect Table 6.2, and the lower of
the reproductive or nonreproductive GMCVs for each tax on were used to construct a combined
distribution of whole-body chronic values, the resulting criterion element (corresponding to
N=18, accounting for three additional fish genera only having nonreproductive-effect GMCVs),
the FCV would be calculated to be 9.1 mg Se/kg WB dw, similar to the 8.5 mg Se/kg WB dw
FCV for reproductive effects expressed as whole-body Figure 6.2.
256
128
T3
0
CO
1
_0J
o
64 L
32
16
• Fish (TL3) WB Repro GMCV
~ Fish (TL3) WB Nonrepro GMCV
~ Inverteb (TL2) GMCV
Fish (TL3)WB FCV
t-JL-I
6
Rank
10
12
Figure 6.2. Distribution of Fish Reproductive Effect GMCVs from Figure 3.2 and
Distribution of Fish Nonreproductive Effect GMCVs and Invertebrate GMCVs.
For establishing a reliable criterion, the sufficiency of and consistency among the data
underlying the reproductive-endpoint GMCVs favor their use over any non-reproductive
endpoint data (see Section 3.1.1 and Appendix C). Most of the reproductive studies involved
125
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examining the offspring of wild-caught females, exposed under real-world conditions. Most had
concentration-response curves that supported ECio estimates.
In contrast, the non-reproductive endpoint studies provide fewer data for supporting a
criterion, and fewer of these studies yielded the type of concentration-response data that could
support EC 10 estimates. Furthermore, the non-reproductive data are not as consistent, as noted by
Janz et al. (2010). The reproductive effect data also show more clear-cut concentration-response
relationships than the non-reproductive effect data (11 of the reproductive chronic values are
specific ECs, compared to only five of the non-reproductive chronic values), are more readily
reproducible, and are better corroborated by field observations. Reproductive effects represent
the endpoint of greatest concern (Chapman et al. 2009, 2010); all non-reproductive GMCVs are
protected by a criterion derived from the reproductive GMCVs. The reproductive endpoint data,
expressed relative to selenium concentrations in fish eggs and ovaries, thus provide a more
reliable and protective basis for the criterion. Because the data set used to derive the criterion is
comprised primarily of the aquatic species considered most sensitive to selenium (salmonids and
centrarchids) and because the criterion is designed to protect 95% of the genera, the egg-ovary
criterion element concentration of 15.1 mg/kg dw ovary/egg should be protective of aquatic
populations of fish and invertebrates.
6.1.10 Special conditions for consideration of primacy of water column criterion elements over
fish tissue criterion elements
The chronic selenium criterion is derived to be protective of the entire aquatic
community, including fish, amphibians, and invertebrates. Fish are the most sensitive taxa to
selenium effects. Selenium water quality criterion elements based on fish tissue (egg-ovary,
whole body, and/or muscle) sample data supersede the criterion elements based on water column
selenium data, when measured in the same approximate time frame (approximately one year) and
site. This is due to the fact, noted above, that fish tissue concentrations provide the most robust
and direct information on potential selenium effects in fish. However, because selenium
concentrations in fish tissue are a result of selenium bioaccumulation via dietary exposure, there
are two specific circumstances where the fish tissue concentrations do not fully represent
potential effects on fish and the aquatic ecosystem: 1) In "fishless" waters, and 2) new selenium
inputs. Fishless waters are defined as waters with insufficient instream habitat and/or flow to
support a population of any fish species on a continuing basis, or waters that once supported
126
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populations of one or more fish species but no longer support fish (i.e., extirpation) due to
temporary or permanent changes in water quality (e.g., due to selenium pollution), flow or
instream habitat. Because of the inability to collect sufficient fish tissue to measure selenium
concentrations in fish within such waters, water column concentrations will best represent
selenium levels required to protect aquatic communities and downstream waters in such areas.
New inputs are defined as new activities resulting in selenium being released into a lentic or lotic
waterbody. New inputs will likely result in increased selenium in the food web, resulting in
increased bioaccumulation of selenium in fish over a period of time until the new selenium
release achieves a quasi-"steady state" balance within the food web. EPA estimates that
concentrations of selenium fish tissue will not represent a "steady state" for several months in
lotic systems, and longer time periods (e.g., 2 to 3 years) in lentic systems, dependent upon the
hydrodynamics of a given system; the location of the selenium input related to the shape and
internal circulation of the waterbody, particularly in reservoirs with multiple riverine inputs; and
the particular food web. Estimates of time to achieve steady state under new selenium input
situations are expected to be site dependent, so local information should be used to better refine
these estimates for a particular waterbody. Thus, EPA recommends that fish tissue concentration
not supersede water column concentration until these periods of time have passed in lotic and
lentic systems, respectively, or until steady state concentrations can be determined.
6.2 Water
6.2.1 Validation of Translation Equation for Developing Water Column Concentrations
EPA evaluated the efficacy of the equation used to translate the egg-ovary criterion
element to a water column concentration. EPA's translation equation is given as:
C
q egg-ovary
"*' ~ TTF™"™" xEFxCF (Equation 18)
Because selenium levels in fish are relatively stable over a long time period if the ecosystem is at
steady state with respect to selenium concentration, single measurements of selenium in fish
tissue are likely to be less variable and a better representation of selenium loads to the aquatic
system than single measurements of selenium in the water column. Thus, EPA used a validation
approach based on fish tissue measurements rather than single water measurements.
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Rearranging Equation 18 to solve for egg-ovary concentration yields:
c,s-0v„ = C„r x TTFx EF x CF (Equation 22)
EPA used Equation 22 to calculate the predicted concentration of selenium in the eggs and
ovaries of fish from all spatially and temporally relevant measurements in the water column.
EPA then compared those predicted values to the measured concentration in the fish.
EPA searched its collection of selenium measurements in fish tissue taken from aquatic
sites with a previously calculated EF value. Identified tissue measurements from other than eggs
or ovaries were converted to equivalent egg-ovary concentrations using species-specific
conversion factors as described previously. For each tissue measurement, EPA searched its
collection of selenium measurements again for water column measurements that were taken from
the same aquatic site and within one year of the tissue measurement. If more than one water
column measurement was matched to a tissue measurement, the median water column
measurement was used. For each matched pair of tissue and water measurements, appropriate
species-specific TTF and CF values were identified as described previously, and the EF value
from the site samples were taken. EPA then used Equation 22 to calculate the predicted egg-
ovary concentration from the observed water column concentration. Finally, EPA compared the
predicted egg-ovary concentrations with the observed egg-ovary concentrations.
EPA identified 317 tissue measurements associated with one or more water column
measurements. A predicted egg-ovary concentration was calculated for each water column
concentration as described above. Figure 6.3 shows all 317 predicted egg-ovary concentrations
plotted against the measured egg-ovary concentrations. Because both the predicted and observed
selenium concentrations exhibited substantial heteroscedasticity (the variability of one variable is
unequal across the range of values of a second variable that predicts it), they are plotted and
analyzed on a log scale. The predicted and measured concentrations are highly correlated
(r=0.82, t(3i5)=25.30, P<0.001). Data used to generate Figure 6.3 can be found in Appendix I.
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1000.0
Observed
egg-ovary
concentration
(mg/kg dw)
100.0
10.0
1.0
0.
Ega-ovarv criterion element (mg/kg dw)
4
Egg-ovary
criterion
element
(mg/kg dw)
0.1 1.0 10.0 100.0 1000.0
Predicted egg-ovary concentration (mg/kg dw)
Figure 6.3. Scatter Plot of Predicted Versus Measured Concentrations of Selenium in Fish.
Solid line shows unity y = x line; dashed lines show the egg-ovary criterion element value.
Although there is a strong correlation between predicted and observed egg-ovary
concentration values, Figure 6.3 shows more data points above the y = x line at low selenium
concentrations. This result suggests the model underestimates bioaccumulation at low selenium
concentrations. Such behavior is likely the result of the inherent model assumption of constant
bioaccumulation rates regardless of selenium concentration, whereas selenium bioaccumulation
has been shown to be inversely related to water concentration (see Sections 3.2.2 and 3.2.4 for
further discussion). Within the range of concentrations near the egg-ovary criterion element
value, however, the relationship between predicted and observed selenium concentrations are
evenly dispersed around the y = x line. Thus the model is unlikely to result in biased estimates
near egg-ovary concentrations that may require regulatory action.
Dispersion around the unity line is likely attributable to several sources of uncertainty
including small sample sizes, temporal or spatial variability in selenium exposure, and local
variability in aquatic food webs. EPA limited this analysis to only those aquatic sites with at least
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two particulate measurements available to calculate an EF value and with at least one of them
from algae or detritus. The requirement of at least two particulate measurements was made
because a single measurement was considered insufficient. The requirement that at least one of
the measurements be for algae and/or detritus was made because selenium within these
particulate types was more highly correlated to water (Section 3.2.2.3), Nevertheless, only one or
two measurements of algae and/or detritus were available for 62 of the 96 aquatic sites evaluated.
Although the minimum data requirements described above reduce uncertainty when applying
Equation 22 to available data, EPA believes that two particulate measurements are only
marginally sufficient. Another potential source of uncertainty is the frequent absence of site-
specific information about the types and proportions of organisms ingested by fish. In most
cases, EPA estimated the type and proportion of prey organisms using general knowledge of the
fish species and aquatic system location. Notwithstanding the limitations in available data, the
EPA concludes from this analysis that Equation 18 provides a reasonable translation of the egg-
ovary criterion element to a site-specific water concentration.
6.2.2 Sulfate-Selenium Interactions
Several investigators (Brix et al. 2001; Ogle and Knight 1996; Williams et al. 1994) have
previously evaluated the role of sulfate on the bioavailability and toxicity of selenium in
freshwater organisms. A report from DeForest et al. (2014) notes that a sulfate-dependent
selenium criteria would apply only to selenate-dominated, well-oxygenated streams, a subset of
freshwater systems in the U.S. The DeForest publication discussed experiments to assess
influence of sulfate on selenate uptake on one species of macrophyte (Lemna minor) and one
algal species (Pseudokirchnella subcapitata), a limited data set of primary producers. The
authors note that, "It does need to be emphasized here, however, the analysis currently does not
include Se data for periphyton and benthic diatoms, as these data are not available." The authors
also note that, "due to methodological challenges and high costs, it is difficult to
comprehensively evaluate the influence of sulphate on bioconcentration and transfer up the food
chain."
Including any type of sulfate relationship in the national criterion derivation would
necessitate having sulfate measurements to accompany all observed selenium water
concentrations included in the derivation database. That is, the absence of an accompanying
sulfate observation would necessitate excluding the water observation. The resulting reduction in
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the number of sites included in the database would reduce the confidence in its ability to
represent the nation's waters. For the above reasons, EPA has not included a sulfate relationship
in the 2016 selenium criterion.
6.3 Uncertainty
This section examines several areas where EPA addressed uncertainty in the development
of the selenium water quality criterion. This section represents a qualitative treatment of specific
parts of the derivation process for the selenium freshwater chronic criterion where EPA has
identified the potential for uncertainty, and also describes the approaches that the Agency used to
reduce uncertainty.
EPA developed a tissue-based water quality criterion designed to be protective of aquatic
life from the chronic effects of selenium. In general, EPA followed the procedure detailed in the
document, Guidelines for Deriving Numerical National Water Quality Criteria for the Protection
of Aquatic Organisms and Their Uses (hereafter referred to as the "Guidelines") (Stephan et al.
1985). The Guidelines sets forth a methodology for deriving ambient water quality criteria for
the protection of aquatic life that includes a rigorous list of data quality requirements. Because
selenium is a bioaccumulative chemical with maternal diet and transfer as the primary route of
exposure for chronic toxicity, EPA included additional data quality requirements such as the
requirement of a dietary exposure. See Section 2.7.5 Analysis Plan for Derivation of the Chronic
Fish Tissue-Based Criterion Elements for how chronic effect levels were determined for
selenium. The Guidelines provide several recommended approaches that reduce uncertainty in
the derivation of criterion. It provides a strict set of guidelines for the acceptance of data to be
used in criteria derivation. It provides a minimum set of data requirements (MDRs) that define an
assemblage of aquatic organisms that can be used in a genus sensitivity distribution to derive a
criterion that is protective of 95% of aquatic species. The requirements in the Guidelines reduce
the uncertainty in the ability of a criterion to be protective of aquatic life.
6.3.1 Tissue Criterion Element
The tissue criterion element is based on reproductive effects caused by selenium and is
expressed in three different tissue types, egg/ovary, muscle and whole body. Non-reproductive
effects were also determined but not used in the derivation of the criterion because of less
certainty in the endpoints and effect levels (Section 6.1.9 and Table 6.2). A comparison of fish
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reproductive and non-reproductive effects and the conclusion that the reproductive criterion is
protective of the non-reproductive effects is given in Section 6.1.9.1,
The dataset used to derive the tissue-based criterion consists primarily of fish species: 12
fish species representing 10 genera and 7 families. Although this might be viewed as a small
number of the nearly 800 native freshwater fish species (36 families) of fish in the United States,
it is a large number of species relative to chronic criteria derivations for other pollutants.
Furthermore, the fish species that have been the focus of some of the research have been the
species observed to be those first affected (most sensitive) at selenium-contaminated sites such
as Belews Lake and Hyco Reservoir, i.e., bluegill sunfish and largemouth bass. The data set
contains three acceptable chronic toxicity studies with bluegill sunfish, the second most sensitive
genus in the dataset and one with largemouth bass, the fifth most sensitive genus. The three
replicate chronic values for bluegill are 14.7, 22.6, and 26.3 mg Se/kg egg-ovary dw. Of these
three values, 14.7 mg Se/kg ovary dw is likely the least certain because the study (Hermanutz et
al. 1992, 1996) was not designed to minimize uncertainty in characterizing the tissue
concentrations associated with its observed levels of effect.
Three genera representing five species from Salmonidae, a family considered to be
generally sensitive to contaminants, are in the data set. Two salmonid genera, Salmo and
Oncorhynchus are the third and fourth most sensitive taxa in the data set. Salmo is represented by
a single study, but because the study included a large number of individuals across a broad
spectrum of exposure, the uncertainty associated with its 21 mg Se/kg egg dw might not be
viewed as particularly large. The chronic values for the three studies with Oncorhynchus are
confined to the narrow range 24.5 - 27.7 mg Se/kg egg dw, and on that basis may be considered
to have low uncertainty. Although the numbers of species and families of fish in the data set are
a fraction of what are native to the United States, the fish species contained in the data set are
known to be those most sensitive to selenium based on field observations or known to be
sensitive in general to contaminants. With the lowest six chronic values falling in the relatively
narrow range 15.6-27 mg Se/kg egg-ovary dw, the selenium tissue criterion element should
probably be considered to have the smallest amount of uncertainty among the existing aquatic
life criteria.
As stated in the previous paragraph, the data set primarily consists of fish species and
contains only three invertebrate species. The cases in the field where adverse effects have been
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observed to fish and water birds (e.g., Belews Lake, Hyco Reservoir, Kesterson Reservoir) have
not documented any adverse effects on macroinvertebrates either on a species or community
level (Janz et al. 2010). The effect levels determined for the three invertebrate species contained
in the data set are consistent with the field observations that macroinvertebrates are in general
less sensitive to selenium than fish species. EPA recognizes that there may be more sensitive
oviparous taxa (fish and amphibians), as well as macroinvertebrate taxa than those in the current
data set and supports the testing of different species.
6.3.1.1 Reproductive Endpoints
Reproductive endpoints were determined from studies in which adults were exposed to
selenium either in the laboratory or field. Effects were measured in the offspring which received
selenium exposure via maternal transfer. Larval mortality and teratogenic deformities such as
skeletal, craniofacial, and fin deformities, and various forms of edema that result in mortality are
the most sensitive indicators of selenium toxicity in fish larvae. Recent research suggests the
mode of action of selenium-induced toxicity in fish larvae is due to oxidative stress and appears
to be related to glutathione homeostasis (See Section 2.3 for more detail on this subject.).
Linking the mode of action directly to the assessment endpoint used in the derivation of the
tissue-based criterion provides a consistent concentration-response relationship among the
studies used in the data set. Using the most sensitive assessment endpoint (based on the state of
the science) reduces uncertainty in the ability of the criterion to protect aquatic life.
6.3.1.2 Egg Ovary Chronic Values
Chronic Values (CV) were based on the most direct representation of exposure to the
effect in the offspring, that is, the concentration of selenium in the egg/ovary. One way to assess
the precision of the chronic values used in the derivation of the criterion is to look at the
reproducibility of tests used to calculate the CV for a taxon. This precision assessment can be
done with two tests conducted with cutthroat trout and three tests conducted with bluegill
sunfish. The two cutthroat trout studies (Rudolph et al. 2008 and Nautilus Environmental 2011)
had very similar ECio values (24.7 and 27.7 mg Se/kg egg dw, respectively) for the same
endpoint (larval survival) using fish collected at the same site. Two of the three bluegill tests
(Coyle et al. 1993 and Doroshov et al. 1992a) also had very similar ECio values (26.3 and 22.6
mg Se/kg egg dw, respectively) for larval endpoints determined in laboratory exposures. An
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ECio of 14.7 mg Se/kg ovary dw was determined in the third bluegill test, a mesocosm exposure
study reported by Hermanutz et al. (1992, 1996). Although the mesocosm study had a lower
ECio value when compared with Coyle et al. (1993) and Doroshov et al. (1992a), it was within a
factor of 1.8 and 1.5, respectively. Delos (2001) found such differences to be typical when
equivalent toxicity tests of the same species are compared. The relatively low variability between
chronic toxicity tests conducted with the same species indicates precision in the CV estimates,
which reduces the uncertainty the tissue-based criterion.
Most of the CVs were determined using an ECio value and a few were estimated using
the NOEC. ECio values were considered more appropriate than EC20, because selenium is a
tissue-based criterion due to its nature of exposure and effects for this bioaccumulative chemical.
See Section 2.7.1 for a discussion of why EC10S were favored over EC20S. The use of EC10S and
NOECs increases the certainty that the criterion will be protective of aquatic life.
6.3.1.3 Whole Body and Muscle Chronic Values
Effect levels (ECio or NOECs) were determined directly for whole body or muscle
tissues when the selenium concentrations for these tissues were measured and reported in the
tests. Effect levels were calculated directly using muscle tissue for five of the chronic toxicity
tests: northern pike, cutthroat trout (Rudolph), bluegill (Doroshov and Hermanutz) and white
sturgeon, while effect levels for three tests were calculated directly using whole body selenium
concentrations: bluegill (Coyle and Hermanutz) and brown trout. For the other tests that did not
have muscle or whole body selenium measurements, conversion factors (CFs) were used to
convert the egg/ovary CV to a muscle or whole body CV. The direct calculation of the muscle
and whole body CVs (when data were available) reduced uncertainty in these effect level
estimates.
6.3.1.4 C onversi on F actors
When muscle or whole body chronic values could not be determined directly using
selenium concentrations measured and reported for the respective tissue, conversion factors (CF)
were used to convert the egg/ovary chronic value to either a muscle or whole body chronic value.
To derive egg-ovary to whole-body CF values, EPA defined matched pairs of selenium
measurements from the eggs or ovaries and from the whole-body measured from the same
individual fish or from matched composite samples. If multiple measurements from both eggs
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and ovaries of the same individual or matched composite sample were available, the average
value was used. Similar pairings were done for egg-ovary to muscle CF values.
After the data sets of the pairings were compiled, EPA first confirmed a statistical
relationship between egg-ovary and whole body selenium for each species using ordinary least
squares (OLS) linear regression of the matched pairs of measurements. If the regression resulted
in a significant fit (P<0.05) with a positive slope, EPA calculated the ratio of the egg-ovary to
whole body (or muscle) selenium concentration of each matched pair and used the median ratio
as the CF value for the species. A detailed comparison of the advantages and disadvantages of
the median ratio and least squares regression approaches to calculating CFs, along with a
comparison of CFs calculated from median ratios, OLS regression following log transformation,
and total least squares (TLS) regression following log transformation is in Appendix N. Table N-
3 provides a comparison of the median-based and regression-based CFs when they are used to
convert an egg-ovary selenium concentration to muscle or whole body. Generally, the median-
based and TLS-based CFs were similar for both tissue types and this similarity resulted in
similar criterion element values (bottom row of Table N-3). The muscle criterion element value
for the data set that contained directly calculated CVs and converted CVs was similar whether
median or TLS CFs were used, 11.3 and 10.2, respectively. The whole body criterion element
value was also similar using these two approaches, 8.5 and 9.4, respectively. The median-based
CF approach was considered to be better than the regression-based CF approaches at reducing
uncertainty. A detailed comparison and rationale for the median approach is discussed in
appendix N.
EPA had sufficient egg-ovary and whole-body selenium measurements to directly
calculate egg-ovary to whole body CF values for 13 species of fish. Similarly, there were
sufficient egg-ovary and muscle selenium measurements to directly calculate egg-ovary to whole
body CF values for 16 species of fish. To derive CF values for additional fish species, EPA used
a taxonomic-relatedness approach (most similar taxon) approach to estimate CF. This approach
is consistent to that done for TTF estimates, and is described in Section 3.2.2, and in greater
detail in Appendix B.
The variability of CFs between fish species and within fish species was fairly low. EPA
derived 13 CF values directly from matched pairs of egg-ovary and whole-body selenium
measurements and an additional seven CF values by multiplying EO/M and M/WB conversion
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factors (Table 3.12). Excluding mountain whitefish (CF= 7.4), CFs for 19 of the 20 species
ranged from 1.20 to 3.11, a 2.6-fold difference. CF variability within each species was also low
for 11 of the 13 species for which egg-ovary to whole-body CFs were determined directly and a
standard deviation calculated (Table 3.12). The two species with relatively high standard
deviations contained data that were potentially anomalous. When the potentially anomalous data
were removed the standard deviations for these two species were reduced considerably (see
footnote to Table 3.12).
6.3.2 Trophic Transfer Factors
A Trophic Transfer Factor (TTF) represents the transfer of selenium from one trophic
level to the next higher trophic level. T'/T's are used in the translation of the tissue criterion
element concentration to a water element value. For a description of how TTFs are used in
translation, see Section 3.2.1, Translation from Fish Tissue Concentration to Water Column
Concentration.
Similar to CFs, EPA calculated TTFs from field data using the median-ratio approach
after first performing OLS regression of matched pairs of selenium measurements for the two
taxa representing successive trophic levels to determine if the relationship is significant (P<0.05)
and has a positive slope. EPA also evaluated using only OLS regression results to calculate TTF
values. OLS regression was performed using matched concentrations of selenium in the food of a
particular species or taxonomic group with the concentration of selenium in the organism's
tissue, and then the slope of the regression was used as the TTF for that species or taxonomic
group. An advantage of the regression approach is that it estimates the quantitative relationship
of selenium across a range of environmental concentrations in a manner that allows statistical
assessment. Disadvantages of this regression approach include the assumption that the
underlying data are normally distributed; the possibility that one or a few very high or low values
can have a disproportionate influence on the slope of the fitted line; and the fact that the
bioaccumulation model does not account for a non-zero y-intercept. Constraining the y-intercept
to zero (also known as regression through the origin or RTO) eliminates the added complexity of
a non-zero y-intercept. However, RTO further increases the disproportionate influence of one or
a few high values on the slope of the fitted line. Furthermore, RTO does not provide a
straightforward way of evaluating goodness of fit (Gordon 1981).
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The median-ratio approach, following confirmation of a significant (P<0.05) relationship
and positive slope, was considered to be more appropriate for deriving T'/T's from field data that
the OLS regression approach. Requiring a significant positive OLS linear regression coefficient
confirms the relationship between selenium in organisms and the food they ingest is adequately
represented by the available data. Using the median of the individual ratios provides an estimate
of central tendency for that relationship that is less sensitive to potential bias from measurements
taken from aquatic systems with very high or very low selenium concentrations. Some aquatic
organisms exhibit selenium bioaccumulation inversely related to water concentration (McGeer et
al. 2003; Borgman et al. 2004; DeForest et al. 2007). This inverse relationship is likely due to
saturation uptake kinetics of specific transport mechanisms that regulate metals bioaccumulation
within certain ranges (U.S. EPA 2007). EPA evaluated the effect of very high and very low
selenium concentrations on the calculation of TTF values using the hybrid approach (use of
median ratios for matched data with significant relationship and positive slope) described above
by excluding selenium measurements above various minimum and/or below various maximum
selenium concentrations. EPA found that using the median ratio effectively attenuates any effects
of selenium concentration on the calculation of TTF values using the hybrid approach described
above without the need to introduce additional arbitrary exclusion criteria.
TTFs were also determined using physiological coefficients (see Section 3.2.2.1,
Derivation of Trophic Transfer Factors (TFF) Values. However, if a TTF value could be
calculated from both physiological coefficients and field data, EPA used the TTF value
calculated from the substantially larger number of field measurements to minimize statistical
uncertainty.
TTFs were calculated for 32 fish species, and ranged from 0.68 to 2.67 (Table 3.11). The
majority of fish TTFs fell within a relatively narrow range, with an interquartile range (25th - 75th
centile) of 1.03 to 1.42. Variability of TTFs among the 13 invertebrate taxa was higher, ranging
from 0.74 to 4.58 (Table 3.10). Much of the variability among invertebrate TTFs was related to
taxonomic groups. The two bivalve TTFs ranged from 4.00 to 4.58. The five insect TTFs ranged
from 1.48 to 2.88, the five crustacean TTFs ranged from 0.74 to 1.89, and the TTF for
blackworms was 1.29.
EPA translated the tissue criterion element concentration to water element values at field
sites that had selenium measurements in the required water, particulates, invertebrates, and fish.
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For species without sufficient data to directly calculate a TTF value at these sites, EPA estimated
the TTF value by sequentially considering higher taxonomic classifications until one or more
taxa for which a calculated TTF value was available matched the taxon being considered. If the
lowest matching taxon was common to more than one species with a TTF value available, EPA
used the median TTF from the matching species.
6.3.3 Enrichment Factors
Enrichment factors are discussed in Section 3.2.2.3 and Appendix H. This factor,
describing how the bottom of the food chain takes up selenium, is the most variable between
sites. Variability among EFs is the main reason that fish BAFs vary so much between sites, and
this variability is the reason the national criterion for selenium needed to be tiered, with tissue
having priority over water, to increase certainty that the criterion is protective as intended. The
range of site EF values shown in Appendix H spans more than a 100-fold range.
The EF value measured at a particular site is also likely to be the site's most uncertain
parameter, being a ratio of measurements of algae, detritus, and sediment, which may vary
within a site in uncertain ways, and measurements of water, which vary over time. The approach
for setting site EFs was designed to reduce uncertainty. As described in Appendix H, EPA
calculated EF values by searching its database of selenium measurements and identifying all the
selenium measurements from algae, detritus, or sediment. EPA then searched for corresponding
water column measurements from samples collected at the same aquatic site within one year of
the particulate sample. If more than one water concentration was available for any given
particulate measurement, the median water concentration was used. For each of these matched
pairs of particulate and water measurements, EPA calculated the ratio of particulate
concentration to water concentration. If more than one ratio for any given category of particulate
material (algae, detritus, or sediment) was calculated at an aquatic site, EPA used the median of
those ratios. Selenium concentrations between particulate and water concentrations were higher
for algae and detritus than for sediment. To reduce uncertainty in EF values associated with
sediments, at least two particulate selenium measurements with corresponding water column
measurements were required, and sediment measurements were used only if there was at least
one other measurement from either algae or detritus. The geometric mean of the algae, detritus,
and sediment ratios was then calculated and used as the site EF. Because there were at most only
3 possible values (one for algae, one for detritus, and one for sediment), EPA used the geometric
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mean in order to reduce the potential for one of the values to have excessive influence on the
final site EF value. Sites with insufficient data to fulfill these data requirements were not used.
Had EPA increased the data requirements for setting a site EF, then the database would
be restricted to a smaller number of sites. Because the variability between sites is high, reducing
the number of sites in the database would decrease the confidence in the representativeness of
the few sites retained (that is, it would increase the potential for sampling error in attempting to
characterize the nation's waters). The EF determination process thus involved a balance between
having enough information to reasonably characterize each site, and having enough sites to
represent the range of the nation's waters.
Inclusion of selenium speciation information (such as selenate and selenite
concentrations) was infeasible. Very few sites would have the requisite information, thereby
increasing the uncertainty in the representativeness of any possible derived national criterion.
Likewise, inclusion of a sulfate relationship was not feasible on a national basis at this time, for
lack of sulfate data at many sites in the database.
Because EF is the BAF component that varies the most between sites, it is the most
important in determining what the water concentration would be for a site if its fish tissue
concentrations were hypothesized to be at the level of the fish tissue criterion element value.
That is, sites with higher EFs tabulated in Appendix H have lower translated water
concentrations in Table 3.13. Despite uncertainties in this parameter, model-predicted versus
observed fish-tissue concentrations in the vicinity of the water element criterion concentrations
are relatively unbiased, as shown in the figures of Appendix I.
For particular sites, the appropriateness of the national criterion can be resolved by site
specific criteria when necessary (e.g., when a permit limit for water is required), as
recommended in Appendix K. When taking measurements of a site, uncertainty in particulate
measurements (the numerator of the EF) can be bypassed by using site-specific fish BAFs, since
they only consider water and fish tissue selenium measurements. On the other hand, uncertainty
in characterizing time-variable water concentrations is a problem shared by EFs and BAFs.
However, this uncertainty can be reduced by sampling in a spatially and temporally robust
manner, appropriate for the site in question, and then using the mathematical modeling approach
to derive a site specific criterion.
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6.3.4 Water Values
Derivation of the water criterion element from the egg-ovary criterion element is
described in Sections 2.7.8 and 3.2, and involves EFs, TTFs, and CFs. Uncertainties in predicted
tissue-to-water ratios combine the uncertainties in the parameters from which they are predicted.
The prediction model is linear in all respects. Potential nonlinearities are therefore an
uncertainty. Section 6.2.1 and Appendix I assesses the accuracy of the predictions. As shown in
the figures of Appendix I, the predicted values perform reasonably well in the vicinity of the
water criterion element concentrations.
Although an earlier published draft document weighted sites by the number of fish
species sampled (between 1 to 6 species per site), that overweighting of sites with several
measured species was removed from this draft by using only the most bioaccumulative fish
species per site, thereby reducing uncertainty that the fish tissue criterion element will be
exceeded when using only water column concentration data. Lentic and lotic sites were assessed
separately, per Section 3.2.4, This increases the likelihood that the water criterion element
concentration will be appropriate for the site of application.
To reduce the likelihood that the water criterion element concentration will be under-
protective for any particular site of application, the 20th percentiles of translated water
concentrations for all lentic and lotic sites, respectively, were used as the water criterion element
concentrations. As described previously, these distributions represented the translated water
concentrations for the most bioaccumulative fish species at each site, which further reduces the
likelihood that the fish tissue criterion element would be exceeded if the water criterion element
was being met. These water criterion elements should not be interpreted to be potentially under-
protective in 20 percent of sites, because when applied to a site's 30-day once-in-three-year
maximum concentration (which is higher than its median), the 20th percentile site would not
attain. The actual percentage of sites protected would thus be greater than 80 percent, but the
exact percentage is uncertain.
6.4 Protection of Threatened or Endangered Species
The chronic toxicity dataset for selenium contains toxicity data for two Federally-listed
endangered species, Cyprinodon macularius (desert pupfish) and Oncorhynchus mykiss (listed as
steelhead, indicating anadromous individuals, but herein called rainbow trout, implying non-
anadromous individuals). The dataset also contains toxicity data for Acipenser transmontanus
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(white sturgeon), which is listed as endangered in specific locations, such as the Kootenai River
white sturgeon in Idaho and Montana. The white sturgeon also serves as a surrogate for other
sturgeon listed as threatened or endangered (e.g., pallid and shovelnose sturgeon). The Acipenser
GMCV of 15.6 mg/kg dw egg is the lowest value in the dataset and therefore provides protection
for other potentially sensitive sturgeon. The white sturgeon chronic value is greater than the
chronic egg-ovary criterion element value.
Desert pupfish, Cyprinodon macularius, with a chronic value estimated to be >27 mg
Se/kg dw egg, is not among the most sensitive species. Its chronic value of >27 mg Se/kg dw egg
is substantially above the chronic egg-ovary criterion element value of 15.1 mg Se/kg dw.
Oncorhynchus mykiss has an SMCV of 24.5 mg Se/kg dw egg, whose genus is the fourth
most sensitive species in the dataset. The dataset contains multiple studies with cutthroat trout
(Oncorhynchus clarkii) some subspecies of which are Federally listed as threatened. The SMCV
for cutthroat trout is 26.2 mg Se/kg dw egg. Both of these chronic values for Oncorhynchus
species are greater than the chronic egg-ovary criterion element.
The dataset also contains toxicity information for Salvelinus malma (Dolly Varden)
which is not threatened or endangered, but is so closely related to the threatened Salvelinus
confluentus (bull trout) that it can hybridize with that species, producing fertile offspring (Baxter
et al. 1997). Dolly Varden is the least sensitive fish species for which information is available,
with an SMCV of 56 mg Se/kg dw egg. Salvelinus fontinalis, brook trout, can also hybridize
with bull trout, but the offspring are sterile, suggesting that it is less closely related. With the
available study of brook trout, although in Section 6.1.5 the NOEC is conservatively set to >20.5
mg Se/kg dw egg, which was the average concentration at the Holm et al. (2005) high-exposure
site. The concentration-response information for the offspring of individual females, presented in
Appendix C, suggests that its ECio could be substantially higher, possibly as high as that for
Dolly Varden.
The egg-ovary criterion element value of 15.1 mg Se/kg (dw) is below all of the above
mentioned chronic egg-ovary values for threatened and endangered (or closely related) species.
However, because other threatened or endangered species could be more sensitive, if relevant
new information becomes available in the future, it should be considered in state- or site-specific
criterion calculations.
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The protectiveness of the whole body criterion element concertation of 8.5 mg/kg dw to
threatened and endangered species is also supported by a recent non-reproductive study with two
sturgeon species. De Riu et al. (2014) fed juvenile green and white sturgeon (-30 g body weight)
diets containing a range of selenium concentrations (selenomethionine added to diet formulation;
2.2 mg/kg Se in control diet (no added Se) and 19.7, 40.1 and 77.7 mg/kg Se in the three
treatment diets). Several endpoints were monitored over the 8-week exposure period including
survival and percent body weight increase (% BWI). White sturgeon had no mortalities through
the highest dietary treatment. Green sturgeon juveniles had 0%, 7.7% and 23.1% mortality with
the three dietary treatments. TRAP analysis (threshold sigmoid nonlinear regression) of the green
sturgeon survival data resulted in a whole body ECio value of 28.93 mg/kg dw. ECio values were
lower for % BWI using TRAP. For % BWI, the whole body ECio value for green sturgeon was
16.36 mg/kg dw, and 23.94 mg/kg dw for white sturgeon.
Also notable, the background concentrations of selenium in the juvenile green and white
sturgeon were also elevated at 7.2, 6.5 and 7.1 mg/kg dw (green sturgeon whole body), and 4.8
7.3 and 5.6 mg/kg dw (white sturgeon whole body) at test initiation, and after four and eight
weeks of exposure, respectively.
The De Riu et al. (2014) study suggests that green sturgeon may be more sensitive to
selenium than white sturgeon and also that the EPA whole body concentration of 8.5 mg/kg dw
will be protective, based on the survival and growth data and the observation in De Riu 2014 that
the control whole body tissue concentrations (up to 7.2 mg/kg dw) are approaching the proposed
criterion. This is important because white sturgeon, as well as juvenile green sturgeon (up to
three to four years), spend most of their time in the coastal rivers and estuaries. All species in the
Acipenseriformes (sturgeon and paddlefish) spawn in freshwaters (Bemis and Kynard 1997) or
spend their entire life in freshwater. The white sturgeon's ECio in the dataset provides surrogacy
for the threatened and endangered species from this group. For more information on the De Riu
et al. (2014) study, see Appendix E.
6.4.1 Special Consideration for Pacific Salmonid Juveniles
The current criterion is based on reproductive effects (larval mortality and/or deformities)
for offspring of selenium-exposed adults, and the whole-body criterion element is derived from
the egg-ovary element, with an implicit assumption of adult exposure to selenium. One peer-
reviewer of the 2014 EPA External Peer Review Draft criterion document raised concerns
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regarding the protection of anadromous salmonids, since there is at least some evidence (e.g.,
Hamilton et al. 1990) that juvenile growth may be comparable in sensitivity to reproductive
effects endpoints used by EPA. Anadromous salmon species (e.g., Chinook salmon) in the
Pacific Northwest are unique in that reproductively mature adults are not exposed to selenium in
the freshwater environment due to their life history; young juvenile salmon leave freshwater
streams and rivers as smolts and mature to adulthood in the marine environment until migration
for spawning begins. Furthermore, they are semelparous, breeding only once in their lifetime and
subsequently dying, so there is no potential selenium exposure following spawning in freshwater.
Juvenile salmon have evolved different strategies for growth and maturation to the smolt
stage, and may spend from three months to two years in freshwater (depending on timing of egg
hatching and other factors) before migrating to estuarine areas as smolts and into the ocean to
feed and mature. Salmon remain in the ocean for one to six years (more commonly two to four
years), with the exception of a small proportion of yearling males (called jack salmon), which
mature in freshwater or return after two or three months in salt water (NOAA 2011).
The physiological and morphological changes that allow these species to adapt to marine
conditions as juveniles are reversed in returning adults preparing to migrate up natal streams to
spawn. One key change is the cessation of feeding prior to re-entry into freshwater. Since mature
females are not feeding after returning to freshwater, it is not representative to predict
reproductive effects for anadromous salmonid species based on egg-ovary selenium
concentrations, because the exposure is wholly from selenium sources in the marine environment
(Groot and Margolis 1991).
6.4.1.1 Selenium Toxicity to Juvenile Salmonids
Hamilton et al. (1990) assessed the toxicity of two organoselenium diets in 90-day partial
life cycle tests in freshwater with two life stages of Chinook salmon (Oncorhynchus
tshawytscha). The first diet consisted of fish meal made from low-selenium mosquitofish
(collected from a reference site) fortified with selenomethionine (here termed the SeMet diet).
The second diet contained fish meal made from high-selenium mosquitofish (Gambusia affinis)
collected from the San Luis Drain (SLD), California (here termed the SLD diet). This waterbody
is known to have high concentrations of selenium. A 90-day partial life cycle study was
conducted with swim-up stage salmon larvae in a standardized fresh water that simulated
dilution of San Luis Drain water.
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Survival and growth (length and weight) were measured at 30, 60, and 90 days.
Unexplained control mortality (33%) between day 60 and day 90 introduced an unacceptable
level of uncertainty into the overall health of the fish. The 1985 Aquatic Life Guidelines
(Stephan et al. 1985) and the Manual of Instructions for Preparing Aquatic Life Water Quality
Criteria Documents (Stephan 1987) require that excessive control mortality be treated as an
exclusionary threshold in data quality assessments for regulatory purposes such as deriving water
quality criteria. Therefore the 90-day survival data from this study was not used quantitatively.
At 60 days, larval control mortality was acceptable (1%), and 60-day larval survival was > 90%
in all SLD and SeMet treatments (3.2 ppm - 18.2 ppm) except for the high Se treatment (35.4
ppm). Whole body selenium concentrations were measured at 60 days, were 10.4 and 13.3 mg/kg
dw, respectively, for larvae fed the SeMet and SLD diets of 18.2 mg/kg dw (Hamilton et al.
1990).
Although survival was similar in response to the two diets, larval growth responses
differed between the SLD and SeMet diets. The salmon fed the SeMet mosquitofish diet had
significant reductions in both length and weight at 30, 60, and 90 days; but only at the two
highest concentrations (18.2 and 35.4 ppm). The average length and weight of the larvae fed the
SLD mosquitofish diet were significantly lower at all concentrations at 30, 60, and 90 days. The
greater effect on growth parameters fed the SLD mosquitofish meal diet could have been caused
by one or more of several factors: 1) additional forms of organic selenium (e.g., selenocysteine)
present in the SLD mosquitofish, 2) additional toxic elements (e.g., heavy metals) that were
accumulated by the SLD mosquitofish, and not present in the reference site mosquitofish, and 3)
differential metabolic processing of the organoselenium contained in the proteins of the SLD
mosquitofish and fed to the larval salmon, versus the larvae fed the diet containing the free
amino acid selenomethionine (Hamilton et.al. 1990).
EPA performed a regression on the 60-day weight and whole body concentrations, and
derived a whole body ECio value of 7.355 mg/kg dw for the SeMet diet for reduced growth, and
a whole body ECio value of 11.14 |ig/g dw for the SLD diet for reduced growth. These values
are the only two available ECio Species Mean Chronic Values (SMCVs) for non-reproductive
endpoints for the genus Oncorhynchus, and the Genus Mean Chronic Value (GMCV) is 9.052
mg/kg dw. This is greater than the national whole body criterion element concentration of 8.5
mg/kg dw, which will thus be protective of this genus.
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EPA recommends that states and tribes consider use of the whole-body criterion element
for juvenile (smolt) anadromous Pacific salmon species as the primary criterion element over the
other elements due to the unique life history of these species, specifically, the lack of exposure to
adult salmonids from selenium in freshwater prior to reproduction. The hierarchal structure of
the egg-ovary tissue over the other tissue criterion elements applies to all other species in the
family Salmonidae. The egg-ovary criterion element, as well as the other fish tissue criterion
elements and the water column criterion elements still apply, as applicable, to protect the
remainder of the aquatic community in these waters.
6.5 Aquatic-Dependent Wildlife is Beyond the Scope of this Aquatic
Criterion Derivation
AWQC that are developed by EPA typically focus directly on aquatic life, not aquatic-
dependent wildlife such as birds. As presented by Campbell (2011), EPA recognizes that
selenium effects on aquatic-dependent wildlife are also of concern but considers them beyond
the scope of this national criterion update. In the interest of providing updated guidance to
protect against the known risks of selenium exposure to fish, EPA decided to focus its analyses
on updating the existing selenium criterion for freshwater aquatic life based on the latest
scientific evidence.
In the future, EPA plans to consider the effects of selenium on aquatic-dependent
wildlife, potentially in the form of criteria expanded to address aquatic-dependent wildlife. When
translated to a water concentration, a criterion protective of aquatic-dependent wildlife may be
more stringent or less stringent than the values provided for aquatic life in this criterion
document. This is because data indicate that for most ecosystems, selenium concentrations are
generally conserved or increase incrementally at each trophic level in a food web (after a
substantial increase from water to trophic level 1 (e.g., algae). Certain specific ecosystems (e.g.,
estuarine and marine systems more commonly) with mollusk-based food-webs may create a
pathway for more selenium to bioaccumulate, particularly in molluscivorous predators (certain
fish and aquatic bird species), since the available data indicate that mollusks generally have a
higher trophic transfer factor than other invertebrate taxa. This level of bioaccumulation is
typically lower, and in contrast to other bioaccumulative chemicals such as mercury, which have
much greater biomagnification.
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As stated previously, the single largest step in tissue selenium accumulation in aquatic
environments occurs at the base of the food web where algae and other microorganisms
accumulate selenium from water (Orr et al. 2012; Stewart et al. 2010). Mollusks such as mussels
and clams accumulate selenium to a much greater extent than planktonic crustaceans and insects
due to higher ingestion rates of both particulate-bound (algae) and dissolved selenium from the
water column through filter feeding, and these organisms have a lower selenium elimination rate
(Luoma and Rainbow 2005). Thus, aquatic-dependent wildlife criteria for species that are
primarily molluscivores may have concentrations of concern that are not protected by the 2016
selenium criterion elements found in this document. The criteria values for aquatic-dependent
wildlife would be expected to depend on the aquatic systems, species, and food webs considered,
as well as spatial and temporal considerations related to selenium exposure and breeding and
nesting seasons. Where sensitive aquatic-dependent (e.g., bird) species are known to exist, states
should consider developing site-specific criteria based on data for such species.
6.6 Summary
EPA developed the 2016 national 304(a) Aquatic Life Ambient Water Quality Criterion
for Selenium in Freshwater to be protective of most aquatic life genera in most waters of the
United States, with an intended goal of protecting approximately 95% of aquatic genera in an
ecosystem. This freshwater chronic selenium criterion applies only to aquatic life, and is not
intended to address selenium toxicity to aquatic-dependent wildlife such as aquatic-dependent
birds. This document provides guidance to States and Tribes authorized to adopt water quality
standards under the Clean Water Act (CWA), to protect aquatic life from toxic effects of
selenium.
The 2016 selenium criterion is a chronic criterion that is composed of four elements. All
elements are protective against chronic selenium effects. Two elements are based on the
concentration of selenium in fish tissue and two elements are based on the concentration of
selenium in the water-column. The recommended elements are: (1) a fish egg-ovary element; (2)
a fish whole-body and/or muscle element; (3) a water column - element (one value for lentic and
one value for lotic aquatic systems); and (4) a water column intermittent element to account for
potential chronic effects from short-term exposures (one value for lentic and one value for lotic
aquatic systems). The assessment of the available data for fish, invertebrates, and amphibians
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indicates that a criterion value derived from fish is expected to be protective of the aquatic
community, based on available data.
EPA recommends that states and tribes adopt into their water quality standards a
selenium criterion that includes all four elements, and express the four elements as a single
criterion composed of multiple parts, in a manner that explicitly affirms that the whole-body or
muscle elements supersede the water column element, and the egg-ovary element supersedes any
other element. The magnitude of the fish egg-ovary element is derived from analysis of the
available toxicity data. The magnitudes of the fish whole-body element and fish muscle elements
are derived from the egg-ovary element coupled with data on concentration ratios among tissues.
The magnitudes of the water column elements are derived from the egg-ovary element coupled
with bioaccumulation considerations. Inclusion of the fish whole-body or fish muscle element
into the selenium criterion ensures the protection of aquatic life when fish egg or ovary tissue
measurements are not available, and inclusion of the water column elements into the selenium
criterion ensures protection when neither fish egg-ovary nor fish whole-body nor muscle tissue
measurements are available. There are two specific circumstances where the fish tissue
concentrations do not fully represent potential adverse effects on fish and the aquatic ecosystem:
1) "fishless" waters, because of the inability to collect sufficient fish tissue to measure selenium
concentrations in fish in such waters, and 2) areas with new selenium inputs, because the fish
tissue concentrations in such systems would not yet represent steady state conditions upon which
the criterion is based.
To ensure that the contribution of short-term exposures to the bioaccumulation risks is
accounted for in all situations, EPA is recommending that the intermittent exposure element be
included in the selenium criterion, as noted above. EPA is not recommending a separate acute
criterion element derived from the results of toxicity tests having water-only exposure because
selenium is bioaccumulative and toxicity primarily occurs through dietary exposure. Application
of the intermittent exposure criterion element values to single day, high exposure events will
provide protection from the most important selenium toxicity effect, reproductive toxicity, by
protecting against selenium bioaccumulation in the aquatic ecosystem resulting from short-term,
high exposure events.
The egg/ovary-based tissue criterion element of 15.1 mg Se/kg dw is based on a genus
sensitivity distribution that used the most sensitive assessment endpoint observed in toxicity
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tests, reproductive effects, and included fish species known to be sensitive to selenium (i.e.,
species from Salmonidae and Centrarchidae), as well as three endangered species (desert
pupfish, rainbow trout and white sturgeon).
With respect to the chronic water column criterion elements, EPA intends the lentic and
lotic values of 1.5 and 3.1 |ig/L, respectively, to be protective of most surface waters in the U.S.
These water concentrations represent the 20th percentile of the distribution of translated water
column values from sites across the U.S. The intermittent exposure water column criterion
element is derived from the chronic water column criterion element, which was derived from the
tissue-based criterion.
EPA recognizes selenium bioaccumulation potential depends on the structure of the food
web and several biogeochemical factors that characterize a particular aquatic system. Uncertainty
in the translation of the egg-ovary criterion element to the water column element can be reduced
by deriving a site-specific criterion that uses site-specific selenium data and information on food-
web dynamics from a biological assessment of the aquatic system. Appendix K provides
recommendations and examples for developing site-specific selenium criteria.
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Aquatic Life Ambient Water Quality
Criterion for
Selenium - Freshwater
2016
(Appendices A-N)
U.S. Environmental Protection Agency
Office of Water
Office of Science and Technology
Washington, D.C.
-------
List of Appendices
APPENDIX A: Selenium Chemistry A-l
1.0 Inorganic Selenium A-2
2.0 Organoselenium A-4
3.0 Departure from Thermodynamic Equilibrium A-5
4.0 Physical Distribution of Species in Surface Water A-5
APPENDIX B: Conversions B-1
1.0 Conversion of Wet to Dry Tissue Weight B-2
1.1 Methodology B-2
2.0 Derivation of Tissue Conversion Factors B-5
2.2 CF values calculated directly from whole-body and egg-ovary selenium
measurements B-7
2.3 Muscle to egg-ovary conversion factors B-22
2.4 Muscle to whole-body conversion factors B-42
3.0 Derivation of Trophic Transfer Factor Values B-59
3.1 Methodology B-59
3.2 TTF values from physiological coefficients B-61
3.2.1 Invertebrates B-61
3.2.2 Vertebrates B-66
3.3 TTF values from field data B-68
3.3.1 Invertebrates B-68
3.3.2 Vertebrates B-81
4.0 Food Web Models Used to Calculate Composite TTFs to Translate the Egg-Ovary
FCV to Water-Column Values B-163
APPENDIX C: Summaries of Chronic Studies Considered for Criteria Derivation C-l
APPENDIX D: Summary Studies of Non-Reproductive Effects D-l
1.0 Studies of Non-Reproductive Effects D-2
1.1 Acipenseridae D-2
1.1.1 Acipenser transmontanus (white sturgeon) D-2
1.2 Cyprinidae D-2
1.2.1 Pogonichthys macrolepidotus (Sacramento splittail) D-2
1.2.2 Pimephales promelas (fathead minnows) D-2
1.3 Catostomidae D-4
1.3.1 Xyrauchen texanus (razorback sucker) D-4
1.3.2 Catostomus latipinnis (flannelmouth sucker) D-5
1.4 Salmonidae D-5
1.4.1 Oncorhynchus tshawytscha (Chinook salmon) D-5
1.4.2 Oncorhynchus mykiss (rainbow trout) D-6
1.5 Moronidae D-6
li
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1.5.1 Morone saxitilis (striped bass) D-6
1.6 Centrarchidae D-7
1.6.1 Lepomis macrochirus (bluegill) D-7
APPENDIX E: Other Data E-1
1.0 Selenite E-2
2.0 Selenate E-2
3.0 Other Data - Endangered Species E-13
4.0 Other Data - Chronic Studies with Fish Species E-21
4.1 Evaluation of zebrafish (Danio rerio) and native cyprinid sensitivity to selenium...E-41
4.1.1 Part I. Chronic summary of Thomas (2014) and Thomas and
Janz (2014) I >43
4.1.2 Part II - Evaluating Sensitivity of Cyprinids (Cyprinidae) to Selenium
from Field and Laboratory Data E-46
5.0 Other Data - Chronic Studies with Invertebrate Species E-58
5.1 Rotifers E-58
5.2 Aquatic Worms E-58
5.3 Aquatic Insects (Plecoptera: Mayfly) E-58
5.4 Aquatic Insect (Midge: Chironimids) E-62
6.0 Other Data - Field Study West Virginia Impoundments E-62
7.0 Other Data - Nutritional Deficiency/Sufficiency Studies Containing Measured
Selenium in the Diet and Whole Body Fish Tissue E-64
APPENDIX F: Toxi city of S el enium to Aquati c PI ants F-l
1.0 Selenite F-2
2.0 Selenate F-2
APPENDIX G: Unused Data G-1
APPENDIXH: Calculation of EF Values II-l
APPENDIX I: Observed Versus Predicted Egg-Ovary Concentrations 1-1
APPENDIX J: Supplementary Information on Selenium Bioaccumulation in
Aquatic Animals J-l
1.0 Effects of Growth Rate on the Accumulation of Selenium in Fish J-2
2.0 Analysis of the Relative Contribution of Aqueous and Dietary Uptake on the
Bioaccumulation of Selenium J-3
3.0 Kinetics of Accumulation and Depuration: Averaging Period J-3
3.1 Background J-3
3.2 Approach for Modeling Effects of Time-Variable Se Concentrations J-5
3.2.1 Model Results J-8
3.2.2 Summary of Scenario Results J-10
3.2.3 Example Responses to Increases in Water Concentrations J-l 1
APPENDIX K: Translation of a Selenium Fish Tissue Criterion Element to a
Site-Specific Water Column Value K-l
in
-------
1.0 Translating the Concentration of Selenium in Tissue to a Concentration in Water
Using Mechanistic Bioaccumulation Modeling K-2
1.1 Relating the Concentration of Selenium in Fish Tissue and Water using the
Mechanistic Modeling Approach K-4
1.2 Steps for Deriving a Site-Specific Water Concentration Value from the
Egg-Ovary Criterion Element K-9
1.2.1 Identify the Appropriate Target Fish Species K-9
1.2.2 Model the Food-Web of the Targeted Fish Species K-13
1.2.3 Identify Appropriate TTF Values K-14
1.2.4 Determine the Appropriate EF Value K-18
1.2.5 Determine the Appropriate CF Value K-21
1.2.6 Translate the Selenium Egg-Ovary Criterion Element into a
Site-Specific Water Concentration Value using Equation K-l K-24
1.3 Managing Uncertainty using the Mechanistic Modeling Approach K-24
1.4 Example Calculations K-25
1.4.1 Example 1 K-26
1.4.2 Example 2 K-27
1.4.3 Example 3 K-28
1.4.4 Example 4 K-29
1.5.5 Example 5 K-30
1.5.6 Example 6 K-31
2.0 Translating the Concentration of Selenium in Tissue to a Concentration in Water
using Bioaccumulation Factors (BAF) K-32
2.1 Summary of the BAF Approach K-32
2.1.1 Example: Derivation of a site specific water column criterion for a
waterbody impacted by selenium K-33
2.2 Managing Uncertainty using the BAF Approach K-33
3.0 Comparison of Mechanistic Bioaccumulation Modeling and BAF Approaches K-36
3.1 Translation using the BAF Approach K-39
3.2 Translation using the Mechanistic Bioaccumulation Modeling Approach K-40
3.3 Summary Comparison of the Mechanistic Bioaccumulation and BAF
Approaches K-43
APPENDIX L: Analytical Methods for Measuring Selenium L-l
1.0 General Considerations when Measuring Concentrations of Selenium L-2
2.0 Analytical Methods Recommended for Measuring Selenium in Water L-2
2.1 American Public Health Standard Method 3114 B L-3
2.2 EPA Method 200.8 L-4
2.3 EPA Method 200.9 L-4
3.0 Analytical Methods Available for Measuring Selenium in Fish Tissue L-5
3.1 Strong acid digestion L-5
IV
-------
3.2 Dry-ashing digestion L-6
3.3 Analytical methods available for measuring selenium in particulate material L-6
APPENDIX M: Abbreviations M-l
Reference and site abbreviations M-2
APPENDIX N: Comparison of Approaches for Calculating Selenium Tissue
Conversion Factors N-l
1.0 Comparison of the Median Ratio and Regression Approaches N-2
2.0 Comparison of the Ordinary Least Squares and Total Least Squares Regression
Approaches N-6
2.1 Example 1 - Flannelmouth Sucker (Egg-ovary/Whole-body) N-9
2.2 Example 2 - Bluegill (Egg-ovary/Whole-body) N-12
3.0 Comparison of Median- and Regression-based Conversion Factors to Calculate
Chronic Values for Muscle and Whole Body Tissues N-14
v
-------
APPENDIX A: Selenium Chemistry
A-l
-------
Selenium in aquatic ecosystems exists in a broad range of oxidation states: (+ VI) in selenates
(HSe04, Se042") and selenic acid (H2Se04), (+ IV) in selenites (HSe03, Se032") and selenous acid
(H2Se03), 0 in elemental selenium, and (-II) in selenides (Se2~, HSe), hydrogen selenide (H2Se), and
organic selenides (R2Se). Selenium also shows some tendency to form catenated species like organic
diselenides (RseSeR). Within the normal physiological pH range and the reduction potential range
permitted by water, only Se, Se032, HSe03, and Se042" can exist at thermodynamic equilibrium (Milne
1998). While ionic reactions are expected to be rapid in water, oxidation-reduction reactions may be slow,
and the possibility exists for the formation of HSe" in living systems and some environments where
anoxic conditions arise. The parallel behavior of comparable species of sulfur and selenium in living
systems has often been observed, but it is important to recognize that their chemical characteristics are
different in many ways. For instance, selenate is comparable to chromate in oxidizing strength and far
stronger than sulfate [£°(Se042/H2Se03) = 1.15 V; £°(Cr2072VCr3+) = 1.33V; £°(S0427H2S03) = 0.200V
(standard potentials in acid solution: Weast 1969)], whereas selenide is a much stronger reducing agent
than sulfide [£°(Se/H2Se) = -0.36 V; £°[S/H2S ]= 0.14V)].
1.0 Inorganic Selenium
Selenate usually predominates in well-aerated surface waters, especially those with alkaline
conditions. In spite of its oxidizing strength, selenate (Se042 ) exhibits considerable kinetic stability in the
presence of reducing agents (Cotton and Wilkinson 1988). The radius of Se042" is comparable to that of
S042" (Frausto da Silva and Williams 1991), and uptake by cells is expected to take place via the same ion
channels or permeases for both anions. Competition between sulfate and selenate uptake has been
observed in many species: algae (Riedel and Sanders 1996), aquatic plants (Bailey et al. 1995),
crustaceans (Ogle and Knight 1996), fungi (Gharieb et al. 1995), HeLa cells (Yan and Frenkel 1994), and
wheat (Richter and Bergmann 1993). Reduced selenate bioconcentration with increasing sulfate
concentration has been demonstrated in Daphnia magna (Hansen et al. 1993). A significant inverse
relationship was shown to exist between acute selenate toxicity to aquatic organisms and ambient sulfate
concentrations (Brix et al. 2001a). Competition with selenate has also been observed for phosphate in
green algae (Riedel and Sanders 1996), and with chromate and tungstate in anaerobic bacteria (Oremland
et al. 1989).
Selenous acid species (HSe03" and Se032") can predominate in solution under the moderately
oxidizing conditions encountered in oxygenated waters. Between pH 3.5 and 9.0 biselenite ion is the
predominant ion in water, and at pH values below 7.0, selenites are rapidly reduced to elemental selenium
under mildly reducing conditions (Faust 1981), situations that are common in bottom sediments.
A-2
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Most selenite salts are less soluble than the corresponding selenates. The extremely low solubility
of ferric selenite Fe2(Se03)3 (Ks= 2.0 ± 1.7 x 10"31), and of the basic ferric selenite Fe2(0H)4Se03 (Ks =
10"61 7), is important to the environmental cycling of selenium. Selenites also form stable adsorption
complexes with ferric oxides, forming complexes of even lower solubility than the ferric selenites. Under
certain conditions, selenite (in contrast to selenate) seems to be completely adsorbed in high amounts by
ferric hydroxide and, to a lesser extent, by aluminum hydroxide (Faust 1981). Coprecipitation techniques
have been applied for preconcentration of selenium in natural waters, using iron (III) hydroxides, which
coprecipitates selectively the selenite, but not the selenate, species in river and sea waters (Yoshii et al.
1977). Alum and iron coagulation precipitation can be used in water treatment processes to remove
selenite (Clifford et al. 1986). The low levels of selenium in ocean waters have been attributed to the
adsorption of selenite by the oxides of metals, such as iron and manganese (National Academy of
Sciences 1976).
Relative to selenate, selenite is more reactive because of its polar character, resulting from the
asymmetric electron density of the ion, its basicity (attraction to bond with proton), and its nucleophilicity
(attraction to bond to a nucleus using the lone pair electrons of the ion). No evidence has yet been
presented to show that HSe03" or Se032" is taken up intact into the cell interior. Evidence indicates that
selenite is reduced rapidly, even before uptake in some cases, making it difficult to distinguish between
uptake and metabolic processes (Milne 1998). Freshwater phytoplankton process selenate and selenite by
different mechanisms, leading to different concentrations within the cell, and the concentrations attained
are affected by various chemical and biological factors in the environment (Riedel et al. 1991). These
authors suggested that selenate is transported into the cell by a biological process with low affinity,
whereas selenite appears to be largely physically adsorbed. Contradictory evidence suggesting that
selenite uptake is enzymatically mediated was found with marine phytoplankton (Baines and Fisher
2001). Experimental results supporting the hypothesis that separate accumulation mechanisms for
selenate and selenite are present in D. magna have been published (Maier et al. 1993). However, while
some organisms appear to absorb selenite nonspecifically, specific transport systems exist in other
species. Sulfate competition is insignificant in the aquatic plant Ruppia maritima (Bailey et al. 1995), and
specific uptake systems have been demonstrated in some soft line microorganisms (Heider and Boeck
1993). Selenite uptake in green algae, unlike selenate, is increased substantially at lower pH values, a
property that represents another difference between these two anions (Riedel and Sanders 1996). The
uptake of inorganic selenium species, selenate and selenite, by the green alga Chlamydomonas reinhardtii
(Dang) was examined as a function of pH over the range 5 to 9, and in media with varying concentrations
of major ions and nutrients using 75Se as a radiotracer. Little difference was noted in the uptake of
selenate as a function of pH, with the maximum uptake found at pH 8; however, selenite uptake increased
A-3
-------
substantially at the lower pH values. Differences in speciation are suggested to be the cause of these
differences. Selenate exists as the divalent ion Se042" over the range of pH tested; whereas monovalent
biselenite ion HSe03" is prevalent at these pH values. At the low end of the pH range, neutral selenous
acid may also play a role.
Elemental selenium is not measurably soluble in water. It has been reported that elemental
selenium is slowly metabolized by several bacteria (Bacon and Ingledew 1989), and the translocation of
elemental selenium into the soft tissue of the marine mollusk Macoma balthica has been reported (Luoma
et al. 1992). The bioavailability of elemental selenium toM balthica was assessed by feeding the
organisms 75Se-labeled sediments in which the elemental selenium was precipitated by microbial
dissimilatory reduction. A 22% absorption efficiency of particulate elemental selenium was observed. In
view of the insolubility of elemental selenium, uptake may be preceded by air oxidation, or in reducing
environments thiols may facilitate the solubilization (Amaratunga and Milne 1994). Elemental selenium
can be the dominant fraction in sediments (Zawislanski and McGrath 1998).
Selenium is reduced to hydrogen selenide, H2Se, or other selenides at relatively low redox
potentials. Hydrogen selenide by itself is not expected to exist in the aquatic environment since the
Se°/H2Se couple falls even below the H /H2 couple. Aqueous solutions of H2Se are actually unstable in air
due to its decomposition into elemental selenium and water. Under moderately reducing conditions,
heavy metals are precipitated as the selenides, which have extremely low solubilities. The following are
log Ks values of some heavy metal selenides of environmental interest: -11.5 (Mn2+), -26.0 (Fe2+), -60.8
(Cu+), -48.1 (Cu2+), -29.4 (Zn2+), -35.2 (Cd2+), and -64.5 (Hg2+). The precipitation of selenium as heavy
metal selenides can be an important factor affecting the cycling of the element in soils and natural waters.
2.0 Organoselenium
Organic selenides (conventionally treated as Se(-II) species) in variable concentrations, usually in
the form of free and combined selenomethionine and selenocysteine, are also present in natural surface
waters (Fisher and Reinfelder 1991). Dissolved organic selenides may be an important source of selenium
for phytoplankton cells, because they can account for -80% of the dissolved selenium in open ocean
surface waters, and for a significant fraction in many other environments as well (Cutter 1989; Cutter and
Cutter 1995). Dissolved organoselenium levels of 14.2%, 65% and 66% were measured in samples (one
meter depth) from Hyco Reservoir, NC; Robinson Impoundment, SC; and Catfish Lake, NC; respectively
(Cutter 1986). The Hyco Reservoir organoselenium was identified as being protein bound.
Organoselenium concentrations were found to range from 10.4% (58.7 |ig/L) to 53.7% (1.02
|ig/L) of the total selenium present in Lake Creek and Benton Lake, MT surface waters (Zhang and
Moore 1996). Organoselenium quite often is measured as the difference between total dissolved selenium
A-4
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and the sum of selenite plus selenate, and is therefore not typically characterized. Much more work is
needed in the area of specific identification and characterization of the nature of the organic selenides
present in aquatic ecosystems. Organoselenium form(s) are much more bioavailable and probably play a
very important role in selenium ecotoxic effects (e.g. Besser et al., 1993; Rosetta and Knight 1995).
3.0 Departure from Thermodynamic Equilibrium
In the highly dynamic natural waters, there is often a departure from thermodynamic equilibrium.
In the thermodynamic models, kinetic barriers to equilibrium and biological processes are not adequately
considered, and the speciation of selenium in oxidized natural waters is not accurately predicted. Selenate
is usually the predominate form in solution; however, selenite and organoselenium can both exist at
concentrations higher than predicted (Faust 1981; Luoma et al. 1997). Bioaccumulation by
microorganisms, bioproduction and release of organoselenium, and mineralization of particulate selenium
forms contribute to the disequilibrium.
4.0 Physical Distribution of Species in Surface Water
The physical distribution of various selenium species in surface waters is regulated by:
• sorption to or incorporation in suspended particulate matter (SPM), and
• complexation with inorganic and/or organic colloidal material, such as (FeO OH)n and humic
substances (dissolved organic matter, DOM).
Both sorption to SPM and complexation with colloidal matter reduces the bioavailability of the
selenium species. The average fraction of selenium associated with the suspended particulate phase
(0.45|im filtration) as determined from eleven different studies of various surface waters was found to be
16% (0-39% range) of the total selenium, i.e., an average operationally defined dissolved selenium level
of 84% (Table A-l). In the James River, VA, the dissolved inorganic and organic selenium was found to
be 77% and 70% associated with colloidal matter, respectively (Takayangi and Wong 1984). A study of
lake ecosystems in Finland (Wang et al. 1995) found that 52% of the dissolved selenium was associated
with humic substances, and in a similar speciation study of Finnish stream waters, Lahermo et al. (1998)
determined that 36% of the selenium was complexed with humic matter. Hence, in various waterbodies
physical distribution as well as chemical speciation of selenium must be considered in relationship to
bioavailability and aquatic toxicity.
Until recently, the organic selenium fraction has been routinely measured as the difference
between total dissolved selenium and the sum of selenite and selenate. Unfortunately, the calculation of
this important selenium fraction in water as the difference between the total and measurable inorganic
fractions has not permitted this fraction to be fully characterized. New techniques are currently being
A-5
-------
developed which should help the specific identification and characterization of the nature of the organic
selenides present in aquatic systems. This work is particularly important because portions of the organic
selenium fraction (e.g., selenomethionine) of total dissolved selenium in water have been shown to be
much more bioavailable than the other forms of selenium, and therefore this work is also important for
understanding the manifestation of selenium ecotoxic effects.
Table A-l. Suspended particulate and dissolved selenium as a function of total selenium in
freshwater and marine aquatic ecosystems.
Particulate So
Traction
Reference
Wsilerhodv
(% of Total)
dissolved, I'd
Cutter 1989
Carquinez, CA
20-40
0.6-0.8
Cutter 1986
Hyco Reservoir, NC
0
1
Tanizaki et al. 1992
Japanese Rivers
16
0.84
Luomaetal. 1992
San Francisco Bay, CA
22-31
0.69-0.78
Cumbie and VanHorn, 1978
Belews Lake, NC
8
0.92
GLEC 1997
Unnamed Stream, Albright, WV
4
0.96
Wang et al. 1995
Finnish Lakes
10
0.9
Lahermo et al. 1998
Finnish Streams
8
0.92
Hamilton et al. 200la,b
Adobe Creek, Fruita, CO
18
0.82
Hamilton et al. 200la,b
North Pond, Fruita, CO
0
1
Hamilton et al. 200la,b
Fish Ponds, Fruita, CO
7
0.93
Nakamoto and Hassler 1992
Merced River, CA
0
1
Nakamoto and Hassler 1992
Salt Slough, CA
4
0.96
Welsh and Maughan 1994
Cibola Lake, CA
39
0.62
Welsh and Maughan 1994
Hart Mine Marsh, Blythe, CA
6
0.94
Welsh and Maughan 1994
Colorado River, Blythe, CA
11
0.89
Welsh and Maughan 1994
Palo Verda Oxbow Lake, CA
33
0.67
Welsh and Maughan 1994
Palo Verda Outfall Drain, CA
0
1
Welsh and Maughan 1994
Pretty Water Lake, CA
21
0.79
A-6
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APPENDIX B: CONVERSIONS
B-l
-------
1.0 Conversion of Wet to Dry Tissue Weight
1.1 Methodology
Conversion factors (CF) derived from selenium measurements were calculated using
concentrations expressed as dry weights (jj.g/g dry weight). The majority of tissue and whole-body
selenium concentrations were reported as dry weights. Measurements reported as wet weight were
converted to equivalent dry weights using available percent moisture data for the relevant species and
tissue type.
Species-specific percent moisture data for muscle tissue were available for bluegill (Gillespie and
Baumann 1986; Nakamoto and Hassler 1992), rainbow trout (Seiler and Skorupa 2001), and for a
composite average of nine fish species (May et al. 2000). Species specific percent moisture data for
ovaries were available for bluegill (Gillespie and Baumann 1986; Nakamoto and Hassler 1992), fathead
minnow (GEI Associates 2008; Rickwood et al. 2008), and rainbow trout (Seiler and Skorupa 2001).
Species-specific % moisture data for whole-body tissues were available for bluegill (USGS NCBP).
Measurements reported as wet weight were converted to equivalent dry weights using available
percent moisture data for the relevant species and tissue type. If percent moisture data were unavailable
for a fish species, percent moisture data for a similar species (i.e., same genus or, if unavailable, same
family) were used. Table B-la lists percent moisture by tissue type, species, data source, and the target
species and study for which the % moisture data were used to convert from wet to dry weight. Table B-lb
is a list of 38 freshwater fish species and their percent solids and moisture. Although these data were not
needed for wet to dry weight conversion in any of the studies in this document, they are provided here as
a potential resource.
B-2
-------
% Moisture 1).
Species
Kii Source
Sliiily
% Moist
Wliolc-
hoilv
lire hv T
Muscle
ssue
()\sirv
C'omersion Appli
Species
eil to
Sliiily
Used in derivation of FCV
Rainbow trout
Seiler & Skorupa 2001
61.20
Rainbow trout
Holm et al. 2005
Rainbow trout
Seiler & Skorupa 2001
61.20
Brook trout
Holm et al. 2005
Fathead
minnow
Average of GEI Assoc. 2008;
Rickwood et al. 2008
75.30
Fathead minnow
Schultz and
Hermanutz 1990
Bluegill
Average of Gillespie &
Baumann 1986 andNakamoto
& Hassler 1992
76.00
Bluegill
Hermanutz et al.
1996
Avg of 9 spp
May et al. 2000
78.4
Striped bass
Coughlan and Velte
1989
Used in conversion of FCV in egg/ovary to whole-body Se concentrations
Bluegill
USGS NCBP
74.80
Bluegill
Hermanutz et al.
1996
Bluegill
May et al. 2000
80.09
Bluegill
Hermanutz et al.
1996
Bluegill
Average of Gillespie &
Baumann 1986 andNakamoto
& Hassler 1992
76.00
Bluegill
Hermanutz et al.
1996
Rainbow trout
May et al. 2000
77.54
Brook Trout
Holm et al. 2005
Rainbow trout
Seiler & Skorupa 2001
61.20
Brook Trout
Holm et al. 2005
Rainbow trout
May et al. 2000
77.54
Rainbow Trout
Holm et al. 2005
Rainbow trout
Seiler & Skorupa 2001
61.20
Rainbow Trout
Holm et al. 2005
Rainbow trout
May et al. 2000
77.54
Rainbow Trout
Casey & Siwik 2000
Rainbow trout
Seiler & Skorupa 2001
61.20
Rainbow Trout
Casey & Siwik 2000
B-3
-------
Table B-lb. Percent solids and moisture for whole body fish tissues by species.
Data provided by GEI Consultants (GEI2014).
Species
A\era}»c % solids
C'oiinl
Min
Max
A\» % moisture
Black bullhead
23.18
6
18.4
27
76.82
Blacknose dace
26.25
44
21.3
31.2
73.75
Bluntnose minnow
25.2
3
23.8
25.9
74.8
Brook stickleback
24.18
57
19.3
27.8
75.82
Carp
21.8
6
21.1
22.8
78.2
Central Stoneroller
25.38
174
17.2
33.7
74.62
Common carp
24.54
62
17.4
43
75.64
Creek chub
23.29
306
16.5
29.3
76.71
Fantail darter
27.71
15
19.5
72.3
72.29
Fathead minnow
23.36
298
15.3
100
76.64
Green sunfish
23.87
150
7.9
29
76.13
Greenside darter
25.55
11
21.7
27
74.45
Johnny darter
28.3
1
--
--
71.7
Largemouth bass
24.26
64
20.6
28.8
75.74
Log perch
23.05
2
22.3
23.8
76.95
Longnose dace
26.75
17
23.4
31.3
73.25
Mimic shiner
24.9
2
24
25.8
75.1
Mosquitofish
23.96
8
22.5
24
76.04
Northern hogsucker
23.93
113
17
39
76.07
Plains killifish
24.5
9
23.3
26.1
75.5
Rainbow darter
27.17
85
12
33.3
72.83
Red shiner
26.93
46
20.9
34.8
73.07
Redside shiner
24.44
8
21.8
26.9
75.56
River chub
24.8
4
22.9
27.3
75.2
River redhorse
20.8
1
--
--
79.2
Rock bass
25.05
24
21.2
29.3
74.95
Rosyface shiner
30.25
2
27.6
32.9
69.75
Rosyside shiner
24.54
5
23.1
25.7
75.46
Sand shiner
26.03
83
20.7
30.7
73.97
Sauger
23
1
--
--
77
Silver shiner
23.4
7
22.3
24.6
76.6
Smallmouth bass
25.78
12
22.7
28.1
74.22
Speckled dace
26.04
35
21
31.2
73.96
Striped shiner
22.9
64
18.2
28.8
77.1
Sunfish
23.2
1
-
-
76.8
Variegated darter
27.45
13
21.7
30.3
72.55
White sucker
22.63
246
16.5
28.4
77.37
Yellow perch
26.02
5
24
28.4
73.98
Grand total
24.85
1990
75.15
B-4
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2.0 Derivation of Tissue Conversion Factors
2.1 Methodology
EPA used a mechanistic bioaccumulation modeling approach to derive a mathematical
relationship between the concentration of selenium in water to the concentration of selenium in the eggs
and ovaries of fish. This approach characterizes selenium bioaccumulation as a series of steps
representing the phase transformation of selenium from dissolved to particulate form, and then the trophic
transfer of selenium through aquatic food webs to invertebrates and fish. The final step in this process is
the transfer of selenium into eggs and ovary tissue.
Equation 1 quantitatively models the transfer of selenium through each environmental
compartment as a series of site-specific and species-specific parameters. The parameter CF in Equation 1
represents the species-specific proportion of selenium in egg or ovary tissue relative to the average
concentration of selenium in all body tissues and is given as:
CF = C.g—(Equation 1)
^whole-body
Where:
CF = Whole-body to egg-ovary conversion factor (dimensionless ratio).
Cegg-ovary = Selenium concentration in the eggs or ovaries of fish (jj.g/g dw)
C whoie-body = Selenium concentration in the whole body of fish (|ag/g dw).
EPA derived species-specific conversion factor (CF) values using the same methods that were
used to derive species-specific TTF values from field data. To derive whole-body to egg-ovary CF values,
the EPA defined matched pairs of selenium measurements from the whole-body and from the eggs or
ovaries measured from the same individual fish or from matched composite samples. Egg-ovary
concentration was defined as a measurement from either the eggs or the ovaries. If multiple measurements
from both eggs and ovaries of the same individual or matched composite sample were available, the
average value was used. EPA first confirmed a statistical relationship between egg-ovary and whole body
selenium for each species using ordinary least squares (OLS) linear regression. If the regression resulted
in a statistically significant (P<0.05) positive slope, EPA calculated the ratio of the egg-ovary to whole
body selenium concentration for each matched pair of measurements and used the median as the CF value
for that species.
EPA derived CF values from selenium measurements in units of |_ig/g dry weight. The majority of
tissue and whole body selenium concentrations were reported as dry weights. Measurements reported as
B-5
-------
wet weight were converted to equivalent dry weights using available percent moisture data for the
relevant species and tissue type. If percent moisture data were unavailable for a fish species, percent
moisture data for a similar species (i.e., same genus or, if unavailable, same family) were used. A listing
of percent moisture concentrations by species and target tissue are provided in Table B-la.
For those species without sufficient data to directly calculate an egg-ovary to whole body CF, but
which had sufficient data to calculate a conversion factor for either egg-ovary to muscle or whole body to
muscle, EPA followed a two stage approach based on taxonomic similarity, similar to that described
above. If a fish species had species specific egg-ovary to muscle conversion factor, but no whole body
data with which to calculate an egg to whole body CF, then available data would be used to estimate a
muscle to whole body conversion factor for that species based on taxonomic relatedness. The estimated
muscle to whole body factor would be multiplied by the directly measured egg-ovary to muscle factor to
estimate an egg-ovary to whole body CF for that species. For example, rainbow trout has a species
specific egg-ovary to muscle conversion factor of 1.92, but does not have a species specific egg-ovary to
whole body CF. Using the taxonomic approach described above, the most closely related taxa to rainbow
trout with muscle to whole body conversion factors are in the class Actinopterygii. The median
conversion factor for the 8 species within that class is 1.27. The final egg-ovary to whole body CF for
rainbow trout is 2.44 (Table B-6), or 1.92 x 1.27.
The EPA developed species-specific egg-ovary to muscle and muscle to whole-body correction
factors following the procedure described for whole-body to egg-ovary conversion factors. The EPA
obtained matched pairs of selenium measurements in the whole-body and muscle filets and matched pairs
of selenium measurements in muscle filets and whole-body from published scientific literature. EPA first
confirmed a statistical relationship between the two tissue types for each species using OLS linear
regression. If the regression resulted in a significant fit with a positive slope, the EPA calculated the ratio
of each matched pair of measurements and then calculated the median ratio.
B-6
-------
2.2 CF values calculated directly from whole-body and egg-ovary selenium measurements
n
^whole-body
r
^-egg
c
^ ovary
r
v-- poo-nvarv
Ratio
Selenium concentration in all tissues (jj.g/g dw)
Selenium concentration in eggs (jj.g/g dw)
Selenium concentration in ovary tissue (jj.g/g dw)
Average selenium concentration in eggs and ovaries
C
egg-ovary
c +c ^
egg ovary
C
whole-body
Black bullhead (Ameiurus melas)
Study
Cwhole-bodv
r
e2S
r
^ovarv
r
*^egg-ovarv
Ratio
Osmundson et al. 2007
5.30
64.30
64.30
12.13
Osmundson et al. 2007
4.80
-
35.40
35.40
7.38
Osmundson et al. 2007
5.50
-
52.80
52.80
9.60
Osmundson et al. 2007
4.90
-
56.00
56.00
11.43
Osmundson et al. 2007
9.60
-
42.80
42.80
4.46
Osmundson et al. 2007
7.60
-
38.70
38.70
5.09
Osmundson et al. 2007
7.30
-
37.30
37.30
5.11
Osmundson et al. 2007
6.60
-
34.30
34.30
5.20
Osmundson et al. 2007
8.60
-
26.40
26.40
3.07
Osmundson et al. 2007
2.00
-
56.70
56.70
28.35
Osmundson et al. 2007
5.30
-
64.30
64.30
12.13
60 n
40 -
20 -
20
c
40
whole-body
Median ratio: 6.29
R2:
0.37
F:
4.67
df:
8
P:
0.046
Not used because negative slope.
60
B-7
-------
Bluegill (Lepomis macrochirus)
Study
Cwhole-bodv
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Coyle et al. 1993
0.90
1.90
2.10
2.00
2.22
Coyle et al. 1993
2.90
7.30
8.30
7.80
2.69
Coyle et al. 1993
4.90
13.00
12.50
12.75
2.60
Coyle et al. 1993
7.20
22.80
25.00
23.90
3.32
Coyle et al. 1993
16.00
41.30
41.00
41.15
2.57
Doroshov et al. 1992
1.60
2.80
-
2.80
1.75
Doroshov et al. 1992
5.50
8.30
-
8.30
1.51
Doroshov et al. 1992
9.30
19.50
-
19.50
2.10
Doroshov et al. 1992
19.30
38.40
-
38.40
1.99
Hermanutz et al. 1996
1.50
-
0.30
0.30
0.20
Hermanutz et al. 1996
18.10
-
16.70
16.70
0.92
Hermanutz et al. 1996
1.90
-
4.40
4.40
2.32
Hermanutz et al. 1996
2.80
-
8.40
8.40
3.00
Hermanutz et al. 1996
12.30
-
29.00
29.00
2.36
Hermanutz et al. 1996
9.40
-
24.50
24.50
2.61
Hermanutz et al. 1996
1.50
-
3.20
3.20
2.13
Hermanutz et al. 1996
4.90
-
10.30
10.30
2.10
Hermanutz et al. 1996
21.00
-
42.10
42.10
2.00
Hermanutz et al. 1996
24.30
-
55.00
55.00
2.26
Hermanutz et al. 1996
5.00
-
7.00
7.00
1.40
Hermanutz et al. 1996
9.50
-
26.00
26.00
2.74
Hermanutz et al. 1996
6.60
-
14.90
14.90
2.26
Hermanutz et al. 1996
1.80
-
4.40
4.40
2.44
Hermanutz et al. 1996
4.20
-
7.90
7.90
1.88
Hermanutz et al. 1996
10.30
-
16.30
16.30
1.58
Hermanutz et al. 1996
13.80
-
15.90
15.90
1.15
Osmundson et al. 2007
8.80
-
9.70
9.70
1.10
60 n
'egg-ovary
Median ratio: 2.13
R
F
df
P
0.82
110.9
25
<0.001
-whole-body
B-8
-------
Bluehead sucker (Catostomus discobolus)
Study
Cwhole-bodv
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
1.30
2.40
2.40
1.85
Osmundson et al. 2007
2.00
-
4.20
4.20
2.10
Osmundson et al. 2007
2.10
-
3.70
3.70
1.76
Osmundson et al. 2007
2.20
-
4.00
4.00
1.82
Osmundson et al. 2007
2.40
-
4.10
4.10
1.71
Osmundson et al. 2007
3.90
-
7.10
7.10
1.82
Osmundson et al. 2007
5.60
-
8.10
8.10
1.45
Median ratio
egg-ovary
whole-body
Brown trout (Salmo trutta)
Study
Cwhole-bodv
r
v^egg
c c
^ovarv ^ess-ovarv
Ratio
Formation 201
Saratoga fish hatchery
3.60
0.80
0.80
0.22
Formation 201
Saratoga fish hatchery
4.10
0.90
0.90
0.22
Formation 201
Saratoga fish hatchery
3.70
0.80
0.80
0.22
Formation 201
Saratoga fish hatchery
4.30
0.90
0.90
0.21
Formation 201
Saratoga fish hatchery
3.00
1.20
1.20
0.40
Formation 201
Saratoga fish hatchery
3.10
1.20
1.20
0.39
Formation 201
Saratoga fish hatchery
2.70
1.00
1.00
0.37
Formation 201
Saratoga fish hatchery
2.50
1.00
1.00
0.40
Formation 201
Saratoga fish hatchery
8.90
12.80
12.80
1.44
Formation 201
13.80
40.30
40.30
2.92
Formation 201
17.90
36.00
36.00
2.01
Formation 201
13.60
26.80
26.80
1.97
Formation 201
17.20
26.90
26.90
1.56
Formation 201
6.70
18.60
18.60
2.78
Formation 201
9.60
17.70
17.70
1.84
Formation 201
22.60
38.80
38.80
1.72
Formation 201
7.20
13.20
13.20
1.83
Formation 201
9.20
13.40
13.40
1.46
B-9
-------
Brown trout (Salmo trutta)
Formation 2011
13.20
Formation 2011
8.60
Formation 2011
11.30
Formation 2011
20.00
Formation 2011
8.40
Formation 2011
5.60
Formation 2011
6.70
Formation 2011
5.90
Formation 2011
6.00
Formation 2011
7.00
Formation 2011
5.60
Formation 2011
4.70
Formation 2011
7.20
Formation 2011
9.20
Formation 2011
5.50
Formation 2011
8.50
Osmundson et al. 2007
4.60
Osmundson et al. 2007
4.30
Osmundson et al. 2007
5.00
Osmundson et al. 2007
5.50
C whole-body
20.50
-
20.50
1.55
12.50
-
12.50
1.45
11.20
-
11.20
0.99
28.10
-
28.10
1.41
12.80
-
12.80
1.52
8.40
-
8.40
1.50
8.50
-
8.50
1.27
8.40
-
8.40
1.42
9.10
-
9.10
1.52
7.50
-
7.50
1.07
6.60
-
6.60
1.18
6.90
-
6.90
1.47
6.20
-
6.20
0.86
14.00
-
14.00
1.52
6.90
-
6.90
1.25
9.50
-
9.50
1.12
-
1.20
1.20
0.26
-
37.80
37.80
8.79
-
35.60
35.60
7.12
-
32.50
32.50
5.91
Median ratio: 1.45
R2: 0.47
F: 31.3
df: 36
P: <0.001
B-10
-------
Channel catfish (Ictalurus punctatus)
Study
Cwhole-bodv
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
3.40
29.50
29.50
8.68
Osmundson et al. 2007
3.30
-
21.10
21.10
6.39
Osmundson et al. 2007
2.60
-
13.70
13.70
5.27
Osmundson et al. 2007
4.00
-
30.30
30.30
7.58
30 -
20 ¦
10 -
Median ratio: 6.98
R2:
0.82
F:
9.1
df:
2
P:
0.099
Not used because P > 0.05.
10
20
-whole-body
30
Common carp (Cyprinus carpio)
Study
Cwhole-bodv
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
6.30
12.10
12.10
1.92
Osmundson et al. 2007
4.80
-
9.40
9.40
1.96
Osmundson et al. 2007
11.70
-
16.30
16.30
1.39
Osmundson et al. 2007
23.10
-
27.30
27.30
1.18
Osmundson et al. 2007
4.10
-
9.90
9.90
2.41
30
20
'egg-ovary
10
10
20
-whole-body
Median ratio: 1.92
R
F
df
P
30
0.96
584.8
3
<0.001
B-ll
-------
Creek chub (Semotilus atromaculatus)
Study
Cwhole-bodv
r
v^egg
C C
^ovarv ^ egg-ova rv
Ratio
GEI2014
2.89
6.86
6.86
2.37
GEI2014
4
9.94
9.94
2.49
GEI 2014
4.14
8.1
8.1
1.96
GEI 2014
4.46
8.98
8.98
2.01
GEI 2014
5.57
18.63
18.63
3.34
GEI 2014
6.23
22.35
22.35
3.59
GEI 2014
24.26
39.07
39.07
1.61
GEI 2014
20.49
12.38
12.38
0.60
GEI 2014
16.33
19.59
19.59
1.20
GEI 2014
14.03
23.78
23.78
1.69
GEI 2014
5.71
23.21
23.21
4.06
GEI 2014
8.17
16.03
16.03
1.96
i'gg ovary
45
40
35
30
25
20
15
10
5
0
10 15
20 25
r
^whnlp-hnih
30 35 40 45
Median ratio: 1.99
R
F
df
P
0.82
7.09
10
0.012
Desert pupfish (Cyprinoclon macularius)
Study
r
^whole-bodv
r
egg
C C
^ ovary ^ egg-ova rv
Ratio
Besser et al. 2012
0.75
1
l
1.33
Besser et al. 2012
2.5
3
3
1.20
Besser et al. 2012
3.4
4.4
4.4
1.29
Besser et al. 2012
6.7
8
8
1.19
Besser et al. 2012
12
13
13
1.08
Besser et al. 2012
24
27
27
1.13
B-12
-------
Desert pupfish (Cyprinodon macularius)
30
25
20
'15
10
o
10 15 20
r
^--whnlp-hfifiv
25
30
Median ratio: 1.20
R
F
df
P
1.00
194.3
4
<0.001
Cutthroat trout (Oncorhynchus clarkii)
Study
Cwhole-bodv
r
egg
C C
^ovarv ^egg-ovary
Ratio
Hardy 2005
0.70
1.00
1.00
1.43
Hardy 2005
2.60
3.80
3.80
1.46
Hardy 2005
2.80
5.50
5.50
1.96
Hardy 2005
6.40
18.00
18.00
2.81
Hardy 2005
1.20
1.60
1.60
1.33
Hardy 2005
4.60
7.80
7.80
1.70
Hardy 2005
5.90
6.60
6.60
1.12
Hardy 2005
9.10
5.10
5.10
0.56
Hardy 2005
11.40
5.20
5.20
0.46
Hardy 2005
5.60
16.00
16.00
2.86
Formation 2012
2.56
3.43
3.43
1.34
Formation 2012
16.3
17.6
17.6
1.08
Formation 2012
20.7
27.9
27.9
1.35
Formation 2012
19.4
29.7
29.7
1.53
Formation 2012
17
22.3
22.3
1.31
Formation 2012
16.7
14.6
14.6
0.87
Formation 2012
25.7
47.6
47.6
1.85
Formation 2012
8.17
22
22
2.69
Formation 2012
9.07
15.4
15.4
1.70
Formation 2012
8.63
11.4
11.4
1.32
Formation 2012
16.6
12.7
12.7
0.77
Formation 2012
19.4
40.1
40.1
2.07
Formation 2012
21
30
30
1.43
Formation 2012
18.6
35.6
35.6
1.91
Formation 2012
22.5
30.5
30.5
1.36
Formation 2012 Henry Lake fish hatchery
0.4
1.65
1.65
4.13
B-13
-------
Cutthroat trout (Oncorhynchus clarkii)
Formation 2012 Henry Lake fish hatchery
0.45
2.03
2.03
4.51
Formation 2012 Henry Lake fish hatchery
0.44
2.48
2.48
5.64
Formation 2012 Henry Lake fish hatchery
0.36
1.36
1.36
3.78
Formation 2012 Henry Lake fish hatchery
0.5
2.33
2.33
4.66
Formation 2012 Henry Lake fish hatchery
0.36
0.83
0.83
2.31
Formation 2012 Henry Lake fish hatchery
0.44
2.26
2.26
5.14
Formation 2012 Henry Lake fish hatchery
0.28
1.87
1.87
6.68
Formation 2012 Henry Lake fish hatchery
0.44
1.98
1.98
4.50
Formation 2012 Henry Lake fish hatchery
0.43
1.34
1.34
3.12
Formation 2012 Henry Lake fish hatchery
0.31
3.23
3.23
10.42
Formation 2012 Henry Lake fish hatchery
0.23
1.58
1.58
6.87
Formation 2012 Henry Lake fish hatchery
0.72
1.93
1.93
2.68
Formation 2012 Henry Lake fish hatchery
0.73
1.79
1.79
2.45
Formation 2012 Henry Lake fish hatchery
0.91
2.06
2.06
2.26
Formation 2012 Henry Lake fish hatchery
0.85
1.74
1.74
2.05
-egg-c
Median ratio:
1.96
R2:
0.83
F:
194.3
df:
39
P:
<0.001
-whole-body
Fathead minnow (Pimephales promelas)
Study
Cwhole-bodv
r
v^egg
C C
^ovarv ^ess-ovarv
Ratio
GEI2014
2.04
3.81
3.81
1.87
GEI2014
1.39
2.23
2.23
1.60
GEI 2014
1.85
3.31
3.31
1.79
GEI 2014
1.32
3.43
3.43
2.60
GEI 2014
1.55
3.08
3.08
1.99
GEI 2014
37.13
50.06
50.06
1.35
GEI 2014
29.54
37.77
37.77
1.28
GEI 2014
33.32
40.82
40.82
1.23
GEI 2014
28.26
32.23
32.23
1.14
GEI 2014
30.74
46.21
46.21
1.50
B-14
-------
Fathead minnow (Pimephales promelas)
GEI2014
53.17
60.84
60.84
1.14
GEI2014
48.52
39.28
39.28
0.81
GEI 2014
53.81
44.28
44.28
0.82
GEI 2014
53.2
46.21
46.21
0.87
GEI 2014
54.01
43.51
43.51
0.81
GEI 2014
12.93
23.18
23.18
1.79
GEI 2014
8.19
14.67
14.67
1.79
GEI 2014
14.25
32.04
32.04
2.25
GEI 2014
8.65
19.95
19.95
2.31
GEI 2014
16.33
38.51
38.51
2.36
GEI 2014
7.69
7.39
7.39
0.96
GEI 2014
19.05
29.69
29.69
1.56
GEI 2014
8.78
9.55
9.55
1.09
GEI 2014
14.68
36.58
36.58
2.49
GEI 2014
9.02
13.63
13.63
1.51
GEI 2014
46.17
61.99
61.99
1.34
GEI 2014
41.97
60.07
60.07
1.43
GEI 2014
34.33
42.74
42.74
1.24
GEI 2014
33.4
38.89
38.89
1.16
GEI 2014
42.53
71.24
71.24
1.68
GEI 2014
74.56
85.87
85.87
1.15
GEI 2014
67.94
65.85
65.85
0.97
GEI 2014
70.85
58.91
58.91
0.83
GEI 2014
43.93
49.67
49.67
1.13
GEI 2014
66.57
67.39
67.39
1.01
GEI 2014
20.21
58.91
58.91
2.91
GEI 2014
13.08
65.85
65.85
5.03
GEI 2014
23.02
31.38
31.38
1.36
GEI 2014
11.55
25.72
25.72
2.23
GEI 2014
32.8
48.52
48.52
1.48
GEI 2014
27.17
48.9
48.9
1.80
GEI 2014
28.54
38.04
38.04
1.33
GEI 2014
37.2
73.16
73.16
1.97
GEI 2014
32.79
44.28
44.28
1.35
GEI 2014
46.17
61.99
61.99
1.87
B-15
-------
Fathead minnow (Pimephales promelas)
100
60
40
20
%
6>
-------
Green sunfish (Lepomis cyanellus)
Study
r
^whole-bodv
r
ess
c
v o\ ;tr\
r
^ess-ovarv
Ratio
Osmundson et al. 2007
22.80
27.40
27.40
1.20
Osmundson et al. 2007
8.80
-
10.20
10.20
1.16
Osmundson et al. 2007
15.40
-
21.80
21.80
1.42
Osmundson et al. 2007
4.80
-
7.00
7.00
1.46
Osmundson et al. 2007
5.70
-
8.90
8.90
1.56
Osmundson et al. 2007
4.40
-
6.40
6.40
1.45
Osmundson et al. 2007
3.80
-
6.40
6.40
1.68
Osmundson et al. 2007
11.90
-
18.10
18.10
1.52
Osmundson et al. 2007
6.40
-
12.30
12.30
1.92
Osmundson et al. 2007
9.50
-
13.80
13.80
1.45
Osmundson et al. 2007
9.10
-
15.20
15.20
1.67
Osmundson et al. 2007
6.20
-
10.80
10.80
1.74
Osmundson et al. 2007
7.00
-
11.70
11.70
1.67
Osmundson et al. 2007
7.70
-
12.60
12.60
1.64
Osmundson et al. 2007
6.20
-
10.00
10.00
1.61
Osmundson et al. 2007
10.20
-
13.90
13.90
1.36
Osmundson et al. 2007
9.70
-
15.20
15.20
1.57
Osmundson et al. 2007
9.90
-
14.70
14.70
1.48
Osmundson et al. 2007
7.20
-
8.80
8.80
1.22
Osmundson et al. 2007
9.00
-
12.90
12.90
1.43
Osmundson et al. 2007
9.70
-
13.10
13.10
1.35
Osmundson et al. 2007
8.90
-
11.50
11.50
1.29
Osmundson et al. 2007
9.80
-
13.20
13.20
1.35
Osmundson et al. 2007
9.90
-
11.60
11.60
1.17
Osmundson et al. 2007
10.30
-
7.50
7.50
0.73
Osmundson et al. 2007
5.30
-
8.10
8.10
1.53
Osmundson et al. 2007
10.10
-
13.20
13.20
1.31
Osmundson et al. 2007
11.80
-
14.00
14.00
1.19
Osmundson et al. 2007
3.30
-
5.20
5.20
1.58
Osmundson et al. 2007
4.00
-
5.80
5.80
1.45
Osmundson et al. 2007
4.30
-
4.10
4.10
0.95
Osmundson et al. 2007
3.70
-
4.90
4.90
1.32
Osmundson et al. 2007
6.20
-
9.50
9.50
1.53
Osmundson et al. 2007
3.50
-
4.80
4.80
1.37
Osmundson et al. 2007
4.40
-
5.60
5.60
1.27
Osmundson et al. 2007
5.60
-
10.10
10.10
1.80
Osmundson et al. 2007
4.90
-
7.50
7.50
1.53
Osmundson et al. 2007
4.40
-
5.90
5.90
1.34
B-17
-------
Green sunfish (Lepomis cyanellus)
30
20
'egg-ovary
10
Median ratio: 1.45
R
F
df
P
0.87
240.0
36
<0.001
10
20
30
"whole-body
Roundtail chub (Gila robusta)
Study
Cwhole-bodv
r
V'egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
4.10
7.90
7.90
1.93
Osmundson et al. 2007
5.30
-
10.80
10.80
2.04
Osmundson et al. 2007
6.40
-
15.20
15.20
2.38
Osmundson et al. 2007
6.80
-
14.10
14.10
2.07
Osmundson et al. 2007
5.50
-
10.60
10.60
1.93
Osmundson et al. 2007
6.60
-
18.00
18.00
2.73
Osmundson et al. 2007
8.40
-
17.80
17.80
2.12
20
10 ¦
'egg-ovary
O fo
Median ratio: 2.07
R2:
0.80
F:
20.4
df:
5
P:
0.004
10
20
"whole-body
B-18
-------
Smallmouth bass (Micropterus dolomieu)
Study
Cwhole-bodv
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
4.20
6.00
6.00
1.43
Osmundson et al. 2007
5.50
-
8.00
8.00
1.45
Osmundson et al. 2007
5.40
-
6.50
6.50
1.20
Osmundson et al. 2007
7.80
-
11.00
11.00
1.41
Osmundson et al. 2007
5.10
-
7.10
7.10
1.39
Osmundson et al. 2007
4.90
-
8.80
8.80
1.80
Median ratio
egg-ovary
whole-body
White sucker (Catostomus commersonii)
Study
Cwhole-bodv
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
3.80
6.20
6.20
1.63
Osmundson et al. 2007
4.20
-
6.20
6.20
1.48
Osmundson et al. 2007
3.30
-
5.20
5.20
1.58
Osmundson et al. 2007
4.50
-
6.50
6.50
1.44
Osmundson et al. 2007
6.30
-
7.70
7.70
1.22
Osmundson et al. 2007
6.80
-
5.80
5.80
0.85
Osmundson et al. 2007
11.00
-
10.90
10.90
0.99
Osmundson et al. 2007
12.70
-
11.20
11.20
0.88
Osmundson et al. 2007
5.70
-
9.40
9.40
1.65
Osmundson et al. 2007
3.90
-
5.40
5.40
1.38
Osmundson et al. 2007
3.80
-
5.10
5.10
1.34
Osmundson et al. 2007
9.90
-
10.40
10.40
1.05
Osmundson et al. 2007
5.30
-
10.40
10.40
1.96
Osmundson et al. 2007
10.70
-
11.00
11.00
1.03
Osmundson et al. 2007
5.90
-
11.70
11.70
1.98
Osmundson et al. 2007
7.00
-
11.60
11.60
1.66
Osmundson et al. 2007
6.40
-
9.40
9.40
1.47
Osmundson et al. 2007
6.30
-
10.20
10.20
1.62
Osmundson et al. 2007
5.30
-
7.30
7.30
1.38
Osmundson et al. 2007
6.20
-
8.90
8.90
1.44
B-19
-------
White sucker (Catostomus commersonii)
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
GEI2014
GEI2014
40
30
10
0
0
10
30
40
f
^whole-body
5.60
8.80
8.70
11.40
10.70
8.40
7.00
7.50
10.30
6.70
2.10
1.80
3.20
2.30
3.10
3.00
2.80
2.50
3.40
2.80
26.9
22.9
10.50
10.50
1.88
10.20
10.20
1.16
8.10
8.10
0.93
9.50
9.50
0.83
10.70
10.70
1.00
8.30
8.30
0.99
12.00
12.00
1.71
6.10
6.10
0.81
6.10
6.10
0.59
11.30
11.30
1.69
2.60
2.60
1.24
3.60
3.60
2.00
4.40
4.40
1.38
4.40
4.40
1.91
4.80
4.80
1.55
4.30
4.30
1.43
4.10
4.10
1.46
3.80
3.80
1.52
3.60
3.60
1.06
3.80
3.80
1.36
32.7
32.7
1.22
23.3
23.3
1.02
Median ratio: 1.38
R2: 0.83
F: 200.4
df: 40
P: <0.001
B-20
-------
Table B-2. Summary of egg-ovary to whole body conversion factors (CF) from matched pairs of
whole-body and egg-ovary measurements.
(0111111011 name
Scientific name
Median ralio {( '/')
Bluegill
Lepomis macrochirus
2.13
Bluehead sucker
Catostomus discobolus
1.82
Brown trout
Salmo trutta
1.45
Common carp
Cyprinus carpio
1.92
Creek chub
Semotilus atromaculatus
1.99
Cutthroat trout
Oncorhynchus clarkii
1.96
Desert pupfish
Cyprinodon macularius
1.20
Fathead minnow
Pimephales promelas
1.40
Flannelmouth sucker
Catostomus latipinnis
1.41
Green sunfish
Lepomis cyanellus
1.45
Roundtail chub
Gila robusta
2.07
Smallmouth bass
Micropterus dolomieu
1.42
White sucker
Catostomus commersonii
1.38
B-21
-------
2.3 Muscle to egg-ovary conversion factors
Cmuscle = Selenium concentration in muscle tissue only ((.ig/g dw)
Cegg = Selenium concentration in eggs ((.ig/g dw)
Covary = Selenium concentration in ovary tissue ((.ig/g dw)
fc^+c
= Average selenium concentration in eggs and ovaries
Ct
egg-ovary
egg
ovary
Ratio
C
egg-ovdx y
C
muscle
Black bullhead (Ameiurus melas)
Study
Cmuscle
r
egg
r
^ovarv
r
*^egg-ovarv
Ratio
Osmundson et al. 2007
3.40
64.30
64.30
18.91
Osmundson et al. 2007
3.90
-
35.40
35.40
9.08
Osmundson et al. 2007
4.30
-
52.80
52.80
12.28
Osmundson et al. 2007
4.70
-
56.00
56.00
11.91
Osmundson et al. 2007
5.70
-
42.80
42.80
7.51
Osmundson et al. 2007
7.40
-
38.70
38.70
5.23
Osmundson et al. 2007
7.50
-
37.30
37.30
4.97
Osmundson et al. 2007
7.80
-
34.30
34.30
4.40
Osmundson et al. 2007
7.80
-
26.40
26.40
3.38
Osmundson et al. 2007
9.20
-
56.70
56.70
6.16
60
f 4(1
^egg-ovary
4 6
^"•muscle
Median ratio: 6.84
R2:
0.17
F:
1.65
df:
8
P:
0.250
10
Not used because P > 0.05 and negative
slope.
B-22
-------
Bluegill (Lepomis macrochirus)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Brysonetal. 1984
84.0
49.0
49.0
0.58
Brysonetal. 1985a (pt. 1)
59.0
-
30.0
30.0
0.51
Brysonetal. 1985a (pt. 1)
2.7
-
2.2
2.2
0.81
Bryson et al. 1985a (pt. 2)
25.0
-
9.1
9.1
0.36
Doroshov et al.
1992
1.5
2.8
-
2.8
1.87
Doroshov et al.
1992
5.8
8.3
-
8.3
1.43
Doroshov et al.
1992
10.4
19.5
-
19.5
1.88
Doroshov et al.
1992
23.6
38.4
-
38.4
1.63
Hermanutz et al
1996
1.6
-
2.0
2.0
1.25
Hermanutz et al
1996
8.5
-
18.8
18.8
2.21
Hermanutz et al
1996
14
-
15.5
15.5
1.11
Hermanutz et al
1996
2.1
-
0.3
0.3
0.14
Hermanutz et al
1996
20.6
-
16.7
16.7
0.81
Hermanutz et al
1996
1.9
-
4.4
4.4
2.32
Hermanutz et al
1996
3.5
-
8.4
8.4
2.40
Hermanutz et al
1996
17.6
-
29.0
29.0
1.65
Hermanutz et al
1996
12.5
-
24.5
24.5
1.96
Hermanutz et al
1996
2.3
-
3.2
3.2
1.39
Hermanutz et al
1996
6.9
-
10.3
10.3
1.49
Hermanutz et al
1996
44.9
-
42.1
42.1
0.94
Hermanutz et al
1996
39.8
-
55.0
55.0
1.38
Hermanutz et al
1996
5.3
-
7.0
7.0
1.32
Hermanutz et al
1996
12.5
-
26.0
26.0
2.08
Hermanutz et al
1996
7.8
-
14.9
14.9
1.91
Hermanutz et al
1996
3.2
-
4.4
4.4
1.38
Hermanutz et al
1996
6.1
-
7.9
7.9
1.30
Hermanutz et al
1996
18.7
-
16.3
16.3
0.87
Hermanutz et al
1996
15.1
-
15.9
15.9
1.05
Osmundson et al. 2007
12.9
-
9.7
9.7
0.75
Median ratio
egg-ovary
muscle
B-23
-------
Bluehead sucker (Catostomus discobolus)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
1.5
2.4
2.4
1.60
Osmundson et al. 2007
2.3
-
4.2
4.2
1.83
Osmundson et al. 2007
2.5
-
3.7
3.7
1.48
Osmundson et al. 2007
2.7
-
4
4
1.48
Osmundson et al. 2007
3.1
-
4.1
4.1
1.32
Osmundson et al. 2007
5.2
-
7.1
7.1
1.37
Osmundson et al. 2007
8.6
-
8.1
8.1
0.94
Median ratio
egg-ovary
muscle
Brook trout (Salvelinus fontinalis)
Study
r
^muscle
r
egg
C C
^ovarv ^ess-ovarv
Ratio
Holm et al. 2005
2.80
1.50
1.50
0.54
Holm et al. 2005
1.40
2.50
2.50
1.79
Holm et al. 2005
2.20
3.40
3.40
1.55
Holm et al. 2005
2.00
4.70
4.70
2.35
Holm et al. 2005
2.20
2.90
2.90
1.32
Holm et al. 2005
5.00
5.60
5.60
1.12
Holm et al. 2005
9.70
9.90
9.90
1.02
Holm et al. 2005
10.50
15.40
15.40
1.47
Holm et al. 2005
11.20
12.80
12.80
1.14
Holm et al. 2005
11.40
14.80
14.80
1.30
Holm et al. 2005
12.30
12.20
12.20
0.99
Holm et al. 2005
15.90
12.40
12.40
0.78
Holm et al. 2005
16.50
13.20
13.20
0.80
Holm et al. 2005
19.60
15.50
15.50
0.79
Holm et al. 2005
20.40
15.30
15.30
0.75
Holm et al. 2005
23.40
25.40
25.40
1.09
Holm et al. 2005
34.70
32.50
32.50
0.94
B-24
-------
Brook trout (Salvelinus fontinalis)
Median ratio
egg-ovary
muscle
Brown trout (Salmo trutta)
Study
Cmuscle
r
egg
r
^ovarv
r
^egg-ovary
Ratio
Osmundson et al. 2007
3.2
1.2
1.2
0.38
Osmundson et al. 2007
3.6
-
37.8
37.8
10.50
Osmundson et al. 2007
4
-
35.6
35.6
8.90
Osmundson et al. 2007
6.3
-
32.5
32.5
5.16
C 20
egg-ovary
muscle
Median ratio: 7.03
R2:
0.17
F:
0.40
df:
2
P:
0.71
Not used because P > 0.05.
B-25
-------
Channel catfish (Ictaluris punctatus)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
3.4
29.5
29.5
8.68
Osmundson et al. 2007
3.6
-
21.1
21.1
5.86
Osmundson et al. 2007
3.7
-
13.7
13.7
3.70
Osmundson et al. 2007
5.3
-
30.3
30.3
5.72
X
ovary
muscle
Median ratio: 5.79
R2:
0.20
F:
0.49
df:
2
P:
0.67
Not used because P > 0.05.
Common carp (Cyprinus carpio)
Study
Cmuscle
r
egg
r
^ovarv
r
^egg-ovarv
Ratio
Garcia-Hernandez 2000
4.6
1.8
1.8
0.39
Osmundson et al. 2007
7.8
-
12.1
12.1
1.55
Osmundson et al. 2007
8.2
-
9.4
9.4
1.15
Osmundson et al. 2007
20
-
16.3
16.3
0.82
Osmundson et al. 2007
24.2
-
27.3
27.3
1.13
Osmundson et al. 2007
6.6
-
9.9
9.9
1.50
ovary
muscle
Median ratio: 1.14
R2:
0.84
F:
21.7
df:
4
P:
0.007
B-26
-------
Cutthroat trout (Oncorhynchus clarkii)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Golder 2005
6.80
28.20
28.20
4.15
Golder 2005
4.20
-
47.80
47.80
11.38
Golder 2005
3.00
-
22.00
22.00
7.33
Golder 2005
4.90
-
9.80
9.80
2.00
Golder 2005
4.50
-
8.20
8.20
1.82
Golder 2005
4.00
-
7.00
7.00
1.75
Golder 2005
5.00
-
10.00
10.00
2.00
Golder 2005
5.00
-
10.00
10.00
2.00
Golder 2005
5.00
-
8.00
8.00
1.60
Golder 2005
8.40
-
16.20
16.20
1.93
Golder 2005
8.30
-
18.30
18.30
2.20
Golder 2005
7.00
-
14.30
14.30
2.04
Golder 2005
6.60
-
14.30
14.30
2.17
Golder 2005
8.40
-
14.70
14.70
1.75
Golder 2005
9.80
-
16.40
16.40
1.67
Golder 2005
8.50
-
15.90
15.90
1.87
Golder 2005
16.00
-
20.00
20.00
1.25
Golder 2005
7.00
-
14.00
14.00
2.00
Golder 2005
8.00
-
19.00
19.00
2.38
Golder 2005
7.00
-
14.00
14.00
2.00
Golder 2005
7.00
-
14.00
14.00
2.00
Golder 2005
9.00
-
16.00
16.00
1.78
Golder 2005
7.00
-
13.00
13.00
1.86
Golder 2005
7.00
-
14.00
14.00
2.00
Golder 2005
8.00
-
14.00
14.00
1.75
Golder 2005
9.80
-
20.20
20.20
2.06
Golder 2005
7.00
-
22.00
22.00
3.14
Golder 2005
9.00
-
16.00
16.00
1.78
Golder 2005
7.00
-
12.00
12.00
1.71
Golder 2005
8.00
-
13.00
13.00
1.63
Golder 2005
10.00
-
14.00
14.00
1.40
Kennedy et al. 2000
41.30
75.40
66.80
71.10
1.72
Kennedy et al. 2000
15.30
58.40
31.60
45.00
2.94
Kennedy et al. 2000
14.10
30.60
31.40
31.00
2.20
Kennedy et al. 2000
12.50
20.20
18.50
19.35
1.55
Kennedy et al. 2000
13.70
19.40
19.50
19.45
1.42
Kennedy et al. 2000
14.30
16.20
16.20
16.20
1.13
Kennedy et al. 2000
9.50
16.10
19.30
17.70
1.86
Kennedy et al. 2000
9.40
14.40
22.00
18.20
1.94
Kennedy et al. 2000
8.70
13.20
17.00
15.10
1.74
Kennedy et al. 2000
9.50
12.60
13.60
13.10
1.38
Kennedy et al. 2000
10.20
12.30
14.50
13.40
1.31
B-27
-------
Cutthroat trout (Oncorhynchus clarkii)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Kennedy et al. 2000
10.70
10.50
20.60
15.55
1.45
Kennedy et al. 2000
6.60
9.90
21.50
15.70
2.38
Kennedy et al. 2000
9.70
9.10
13.20
11.15
1.15
Kennedy et al. 2000
10.90
8.50
13.40
10.95
1.00
Kennedy et al. 2000
6.90
13.20
20.30
16.75
2.43
Rudolph et al. 2007
7.70
13.90
-
13.90
1.81
Rudolph et al. 2007
8.20
12.50
-
12.50
1.52
Rudolph et al. 2007
8.00
15.00
-
15.00
1.88
Rudolph et al. 2007
8.10
14.90
-
14.90
1.84
Rudolph et al. 2007
6.60
15.20
-
15.20
2.30
Rudolph et al. 2007
8.50
12.90
-
12.90
1.52
Rudolph et al. 2007
7.20
12.30
-
12.30
1.71
Rudolph et al. 2007
7.30
16.70
-
16.70
2.29
Rudolph et al. 2007
7.60
13.10
-
13.10
1.72
Rudolph et al. 2007
8.70
15.60
-
15.60
1.79
Rudolph et al. 2007
8.20
13.90
-
13.90
1.70
Rudolph et al. 2007
7.90
15.10
-
15.10
1.91
Rudolph et al. 2007
7.60
12.30
-
12.30
1.62
Rudolph et al. 2007
11.80
16.10
-
16.10
1.36
Rudolph et al. 2007
40.40
86.30
-
86.30
2.14
Rudolph et al. 2007
46.10
121.00
-
121.00
2.62
Rudolph et al. 2007
50.40
140.00
-
140.00
2.78
Rudolph et al. 2007
34.70
51.00
-
51.00
1.47
Rudolph et al. 2007
39.00
65.30
-
65.30
1.67
Rudolph et al. 2007
35.40
46.80
-
46.80
1.32
Rudolph et al. 2007
11.30
16.90
-
16.90
1.50
Rudolph et al. 2007
13.40
20.60
-
20.60
1.54
150
0
Median ratio:
1.81
100 ¦
/
R2:
0.82
r
^egg-ovary
F:
308.3
50 ¦
°y*
df:
P:
67
<0.001
50
100
150
B-28
-------
Dolly Varden (Salvelinus malma)
Study
Cmuscle
c c
^ess v o\ ;tr\
r
v ess o\ ;tr\
Ratio
Golder 2009
73.00
92.30
92.30
1.26
Golder 2009
45.90
40.70
40.70
0.89
Golder 2009
107.00
107.00
107.00
1.00
Golder 2009
97.20
102.00
102.00
1.05
Golder 2009
114.00
124.00
124.00
1.09
Golder 2009
115.00
185.00
185.00
1.61
Golder 2009
79.60
112.00
112.00
1.41
Golder 2009
9.90
7.00
7.00
0.71
Golder 2009
3.40
12.10
12.10
3.56
Golder 2009
5.30
9.60
9.60
1.81
Golder 2009
2.80
5.40
5.40
1.93
Golder 2009
4.90
10.50
10.50
2.14
Golder 2009
6.60
11.00
11.00
1.67
Golder 2009
55.70
65.80
65.80
1.18
Golder 2009
58.30
51.90
51.90
0.89
Golder 2009
39.50
60.50
60.50
1.53
Golder 2009
50.50
56.60
56.60
1.12
200 -|
O
150 ¦
Median ratio:
1.26
100 -
^egg-ovary
50 -
n .
So
y°°
R2:
F:
df:
0.90
140.3
15
/°
P:
<0. 001
0 50 100 150 200
f
^muscle
B-29
-------
Flannelmouth sucker (Catostomus latipinnis)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
3.6
4.0
4.0
1.11
Osmundson et al. 2007
3.8
-
4.1
4.1
1.08
Osmundson et al. 2007
4.1
-
5.9
5.9
1.44
Osmundson et al. 2007
4.6
-
4.3
4.3
0.93
Osmundson et al. 2007
5.2
-
5.7
5.7
1.10
Osmundson et al. 2007
6.2
-
6.2
6.2
1.00
Osmundson et al. 2007
7.3
-
6.2
6.2
0.85
egg-ovary
muscle
Median ratio: 1.08
R2: 0.58
F: 6.92
df: 5
P: 0.036
Green sunfish (Lepomis cyanellus)
Study
r
^muscle
r
egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
28.1
27.4
27.4
0.98
Osmundson et al. 2007
12.9
-
10.2
10.2
0.79
Osmundson et al. 2007
21.9
-
21.8
21.8
1.00
Osmundson et al. 2007
5
-
7
7
1.40
Osmundson et al. 2007
6.1
-
8.9
8.9
1.46
Osmundson et al. 2007
5.2
-
6.4
6.4
1.23
Osmundson et al. 2007
5.1
-
6.4
6.4
1.25
Osmundson et al. 2007
15.7
-
18.1
18.1
1.15
Osmundson et al. 2007
10.1
-
12.3
12.3
1.22
Osmundson et al. 2007
11.5
-
13.8
13.8
1.20
Osmundson et al. 2007
10.5
-
15.2
15.2
1.45
Osmundson et al. 2007
7.2
-
10.8
10.8
1.50
Osmundson et al. 2007
9.3
-
11.7
11.7
1.26
Osmundson et al. 2007
7.7
-
12.6
12.6
1.64
Osmundson et al. 2007
6
-
10
10
1.67
Osmundson et al. 2007
12
-
13.9
13.9
1.16
Osmundson et al. 2007
12.1
-
15.2
15.2
1.26
Osmundson et al. 2007
12.5
-
14.7
14.7
1.18
Osmundson et al. 2007
7.5
-
8.8
8.8
1.17
Osmundson et al. 2007
11.3
-
12.9
12.9
1.14
B-30
-------
Green sunfish (Lepomis cyanellus)
Study
-^muscle
Ratio
Osmundson et al. 2007
13.6
-
13.1
13.1
0.96
Osmundson et al. 2007
13.2
-
11.5
11.5
0.87
Osmundson et al. 2007
12.4
-
13.2
13.2
1.06
Osmundson et al. 2007
12.5
-
11.6
11.6
0.93
Osmundson et al. 2007
8.6
-
7.5
7.5
0.87
Osmundson et al. 2007
5.3
-
8.1
8.1
1.53
Osmundson et al. 2007
11.9
-
13.2
13.2
1.11
Osmundson et al. 2007
13.6
-
14
14
1.03
Osmundson et al. 2007
3.8
-
5.2
5.2
1.37
Osmundson et al. 2007
4.2
-
5.8
5.8
1.38
Osmundson et al. 2007
4.1
-
4.1
4.1
1.00
Osmundson et al. 2007
4.2
-
4.9
4.9
1.17
Osmundson et al. 2007
5.7
-
9.5
9.5
1.67
Osmundson et al. 2007
4.4
-
4.8
4.8
1.09
Osmundson et al. 2007
3.5
-
5.6
5.6
1.60
Osmundson et al. 2007
5.5
-
10.1
10.1
1.84
Osmundson et al. 2007
5
-
7.5
7.5
1.50
Osmundson et al. 2007
4.3
-
5.9
5.9
1.37
30 -I
>
Median ratio: 1.21
20 ¦
c
egg-ovary
R2: 0.89
10 ¦
F: 281.4
df: 36
0 ¦
P: <0.001
0 10 20 30
c
^muscle
B-31
-------
Largemouth bass (Micropterus salmoicles)
Study
r
^muscle
r
ess
c
*^ovarv
r
^egg-ovarv
Ratio
Carolina Power & Light 1997
8.48
14.79
14.79
1.74
Carolina Power & Light 1997
8.48
-
14.79
14.79
1.74
Carolina Power & Light 1997
7.29
-
8.35
8.35
1.15
Carolina Power & Light 1997
15
-
19
19
1.27
Carolina Power & Light 1997
15
-
15
15
1.00
Carolina Power & Light 1997
12
-
14
14
1.17
Carolina Power & Light 1997
10
-
18
18
1.80
Carolina Power & Light 1997
18
-
15
15
0.83
Carolina Power & Light 1997
18
-
15
15
0.83
Carolina Power & Light 1997
11
-
12
12
1.09
Carolina Power & Light 1997
11
-
9.4
9.4
0.85
Carolina Power & Light 1997
13
-
10
10
0.77
Carolina Power & Light 1997
11
-
11
11
1.00
20
Median ratio: 1.09
R
F
df
P
0.14
1.74
11
0.22
Not used because P>0.05
5 10 15
^muscle
20
B-32
-------
Mountain whitefish (Prosopium williamsoni)
Study
r
^muscle
r
^egg
r
*^ovarv
r
^egg-ovarv
Ratio
Golder 2005
3.60
26.90
26.90
7.47
Golder 2005
3.70
-
25.80
25.80
6.97
Golder 2005
3.10
-
20.00
20.00
6.45
Golder 2005
4.20
-
19.30
19.30
4.60
Golder 2005
3.90
-
19.20
19.20
4.92
Golder 2005
3.50
-
23.20
23.20
6.63
Golder 2005
5.20
-
38.00
38.00
7.31
Golder 2005
5.00
-
41.00
41.00
8.20
Golder 2005
5.20
-
32.00
32.00
6.15
Golder 2005
7.60
-
34.00
34.00
4.47
Golder 2005
7.20
-
32.00
32.00
4.44
Golder 2005
5.50
-
40.00
40.00
7.27
Golder 2005
7.80
-
39.70
39.70
5.09
Golder 2005
3.70
-
20.30
20.30
5.49
Golder 2005
4.70
-
22.40
22.40
4.77
Golder 2005
4.40
-
28.90
28.90
6.57
Golder 2005
5.70
-
30.10
30.10
5.28
Golder 2005
4.00
-
31.50
31.50
7.88
Golder 2005
10.00
-
35.20
35.20
3.52
Golder 2005
4.90
-
26.70
26.70
5.45
Golder 2005
7.60
-
26.80
26.80
3.53
Golder 2005
6.10
-
29.70
29.70
4.87
Golder 2005
6.80
-
41.10
41.10
6.04
Golder 2005
5.00
-
29.00
29.00
5.80
Golder 2005
6.60
-
34.50
34.50
5.23
Golder 2005
5.00
-
36.30
36.30
7.26
Golder 2005
5° -i
4.80
-
28.90
28.90
6.02
s-
Median
ratio:
5.80
p 25 ¦
W
VP o
R2:
0.33
^ egg-ova iy
F:
12.4
df:
25
n
P:
<0.001
0 25 50
r
^muscle
B-33
-------
Northern pike (Esox lucius)
Study
Cmuscle
r
v^egg
c c
^ovarv ^ess-ovarv
Ratio
Muscatello et al. 2006
0.90
3.50
3.50
3.89
Muscatello et al. 2006
1.90
2.70
2.70
1.42
Muscatello et al. 2006
2.60
3.40
3.40
1.31
Muscatello et al. 2006
1.30
3.70
3.70
2.85
Muscatello et al. 2006
1.00
2.70
2.70
2.70
Muscatello et al. 2006
17.00
43.20
43.20
2.54
Muscatello et al. 2006
16.50
24.50
24.50
1.48
Muscatello et al. 2006
16.50
26.10
26.10
1.58
Muscatello et al. 2006
2.00
3.40
3.40
1.70
Muscatello et al. 2006
2.00
4.10
4.10
2.05
Muscatello et al. 2006
1.30
4.10
4.10
3.15
Muscatello et al. 2006
2.50
4.10
4.10
1.64
Muscatello et al. 2006
1.30
3.40
3.40
2.62
Muscatello et al. 2006
47.80
48.20
48.20
1.01
60
30 -
30
p
^muscle
60
Median ratio: 1 .<¦
R2:
0.83
F:
58.9
df:
12
P:
<0.001
Rainbow trout (Oncorhynchus mykiss)
Study
C nmscle
r
v^egg
c c
^ovarv ^ess-ovarv
Ratio
Casey and Siwik 2000
4.10
11.60
11.60
2.83
Casey and Siwik 2000
3.80
10.10
10.10
2.66
Casey and Siwik 2000
2.60
0.10
0.10
0.04
Casey and Siwik 2000
3.30
4.90
4.90
1.48
Casey and Siwik 2000
2.30
3.60
3.60
1.57
Casey and Siwik 2000
2.80
5.30
5.30
1.89
Casey and Siwik 2000
2.30
3.70
3.70
1.61
Casey and Siwik 2000
2.80
6.40
6.40
2.29
Casey and Siwik 2000
3.00
5.20
5.20
1.73
Casey and Siwik 2000
4.90
6.80
6.80
1.39
Casey and Siwik 2000
1.50
3.60
3.60
2.40
Casey and Siwik 2000
2.60
6.90
6.90
2.65
B-34
-------
Rainbow trout (Oncorhynchus mykiss)
Study
C nmscle
r
v^egg
c c
^ovarv ^ess-ovarv
Ratio
Casey and Siwik 2000
4.60
6.90
6.90
1.50
Casey and Siwik 2000
4.60
6.40
6.40
1.39
Casey and Siwik 2000
3.60
5.50
5.50
1.53
Casey and Siwik 2000
2.40
10.50
10.50
4.38
Casey and Siwik 2000
3.70
7.60
7.60
2.05
Casey and Siwik 2000
2.70
4.10
4.10
1.52
Casey and Siwik 2000
0.70
1.10
1.10
1.57
Casey and Siwik 2000
0.60
0.90
0.90
1.50
Casey and Siwik 2000
0.60
1.30
1.30
2.17
Casey and Siwik 2000
28.60
56.30
56.30
1.97
Casey and Siwik 2000
30.90
56.00
56.00
1.81
Casey and Siwik 2000
32.40
71.50
71.50
2.21
Casey and Siwik 2000
28.00
61.30
61.30
2.19
Casey and Siwik 2000
31.70
54.50
54.50
1.72
Casey and Siwik 2000
29.50
56.80
56.80
1.93
Casey and Siwik 2000
30.10
57.90
57.90
1.92
Casey and Siwik 2000
29.90
64.70
64.70
2.16
Casey and Siwik 2000
32.80
46.60
46.60
1.42
Casey and Siwik 2000
31.40
56.50
56.50
1.80
Casey and Siwik 2000
32.00
67.50
67.50
2.11
Casey and Siwik 2000
35.70
59.40
59.40
1.66
Casey and Siwik 2000
24.60
48.70
48.70
1.98
Casey and Siwik 2000
30.30
69.10
69.10
2.28
Casey and Siwik 2000
25.70
43.50
43.50
1.69
Casey and Siwik 2000
35.00
58.10
58.10
1.66
Casey and Siwik 2000
33.80
59.20
59.20
1.75
Casey and Siwik 2000
28.70
55.00
55.00
1.92
Casey and Siwik 2000
25.80
49.00
49.00
1.90
Holm et al. 2005
1.70
1.00
1.00
0.59
Holm et al. 2005
1.60
3.50
3.50
2.19
Holm et al. 2005
1.30
4.60
4.60
3.54
Holm et al. 2005
4.00
12.80
12.80
3.20
Holm et al. 2005
4.30
17.10
17.10
3.98
Holm et al. 2005
8.50
17.50
17.50
2.06
Holm et al. 2005
7.40
29.70
29.70
4.01
B-35
-------
Rainbow trout (Oncorhynchus mykiss)
Ratio
muscle
ovary
egg-ovary
Median ratio
egg-ovary
muscle
Razorback sucker (Xyrauchen texanus)
Study
Cmuscle
r
v^egg
C C
^ovarv ^egg-ovarv
Ratio
Hamilton et al. 2001a
5
7.5
7.5
1.50
Hamilton et al. 2001a
4
6.1
6.1
1.53
Hamilton et al. 2001a
4.2
6.6
6.6
1.57
Hamilton et al. 2001a
4.4
6.2
6.2
1.41
Hamilton et al. 2001a
4.5
5.8
5.8
1.29
Hamilton et al. 2001a
4.3
6.8
6.8
1.58
Hamilton et al. 2001a
11.1
35.5
35.5
3.20
Hamilton et al. 2001a
12.2
43.4
43.4
3.56
Hamilton et al. 2001a
10.4
54.5
54.5
5.24
Hamilton et al. 2001a
11.3
28.2
28.2
2.50
Hamilton et al. 2001a
10.4
38
38
3.65
Hamilton et al. 2001a
17.3
41.3
41.3
2.39
Hamilton et al. 2001a
13
37.2
37.2
2.86
Hamilton et al. 2001a
16.7
40.9
40.9
2.45
Hamilton et al. 2001a
14.6
35.3
35.3
2.42
Hamilton et al. 2001a
12.1
34.3
34.3
2.83
Hamilton et al. 2001b
4.7
5
5
1.06
Hamilton et al. 2001b
5.3
6.2
6.2
1.17
Hamilton et al. 2001b
3.6
5.9
5.9
1.64
Hamilton et al. 2001b
5.3
6.5
6.5
1.23
Hamilton et al. 2001b
4.1
6.35
6.35
1.55
Hamilton et al. 2001b
4.9
6.1
6.1
1.24
Hamilton et al. 2001b
16
40.1
40.1
2.51
Hamilton et al. 2001b
18
38.4
38.4
2.13
Hamilton et al. 2001b
16
40.2
40.2
2.51
Hamilton et al. 2001b
19
43.1
43.1
2.27
B-36
-------
Razorback sucker (Xyrauchen texanus)
Study
Cmuscle
r
v^egg
c c
^ovarv ^ess-ovarv
Ratio
Hamilton et al. 2001b
14
41.9
41.9
2.99
Hamilton et al. 2001b
14
36.2
36.2
2.59
Hamilton et al. 2001b
24
56.5
56.5
2.35
Hamilton et al. 2001b
27
51.8
51.8
1.92
Hamilton et al. 2001b
24
52.6
52.6
2.19
Hamilton et al. 2001b
27
55.1
55.1
2.04
Hamilton et al. 2001b
19
53
53
2.79
Hamilton et al. 2001b
16
58.5
58.5
3.66
Waddell and May 1995 a
4.40
3.70
3.70
X
Waddell and May 1995 a
7.10
4.70
4.70
X
Waddell and May 1995 a
32.00
10.60
10.60
X
70
60
50
40 -
30 ¦
20 ¦
10 ¦
Q/lg
/
L
0
10
20
30 40
c
^DIQSCie
50
60
70
Median ratio: 2.31
R2:
0.80
F:
125.6
df:
32
P:
<0.001
Data from this study were excluded because results were atypical.
Roundtail chub (Gila robusta)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
4.3
7.9
7.9
1.84
Osmundson et al. 2007
5
-
10.8
10.8
2.16
Osmundson et al. 2007
6.2
-
15.2
15.2
2.45
Osmundson et al. 2007
6.9
-
14.1
2.04
Osmundson et al. 2007
7
-
10.6
10.6
1.51
Osmundson et al. 2007
7.3
-
18
18
2.47
Osmundson et al. 2007
9.8
-
17.8
17.8
1.82
B-37
-------
Roundtail chub (Gila robusta)
ovary
muscle
Median ratio: 2.04
R2:
F:
df:
P:
0.62
8.27
5
0.026
Smallmouth bass (Micropterus dolomieu)
Study
r
^muscle
r
ess
c
*^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
3.7
6.0
6.0
1.62
Osmundson et al. 2007
6.5
-
8.0
8.0
1.23
Osmundson et al. 2007
6.9
-
6.5
6.5
0.94
Osmundson et al. 2007
11
11
1.00
Osmundson et al. 2007
5.5
-
7.1
7.1
1.29
Osmundson et al. 2007
7.7
-
8.8
8.8
1.14
15
10
¦'egg-ovary
5 10
f
^muscle
15
Median ratio:
1.19
R2:
0.85
F:
23.5
df:
4
P:
0.006
B-38
-------
White Sturgeon (Acipenser transmontanus)
Study
Cmuscle
r
v^egg
C C
^ovarv ^ess-ovarv
Ratio
Linville 2006
1.28
2.46
2.46
2.46
Linville 2006
1.22
1.61
1.61
1.61
Linville 2006
1.48
2.68
2.68
2.68
Linville 2006
9.93
11
11
11
Linville 2006
15.3
20.5
20.5
20.5
Linville 2006
11.1
7.61
7.61
7.61
10
c
v muscle
Median ratio: 1.33
R2:
0.86
F:
24.96
df:
4
P:
0.006
White Sucker (Catostomus commersonii)
Study
r
^muscle
r
egg
c
*^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
2.9
6.2
6.2
2.14
Osmundson et al. 2007
4.8
-
6.2
6.2
1.29
Osmundson et al. 2007
3.7
-
5.2
5.2
1.41
Osmundson et al. 2007
3.7
-
6.5
6.5
1.76
Osmundson et al. 2007
8.4
-
7.7
7.7
0.92
Osmundson et al. 2007
9.4
-
5.8
5.8
0.62
Osmundson et al. 2007
15.5
-
10.9
10.9
0.70
Osmundson et al. 2007
23.6
-
11.2
11.2
0.47
Osmundson et al. 2007
9.4
-
9.4
9.4
1.00
Osmundson et al. 2007
6.1
-
5.4
5.4
0.89
Osmundson et al. 2007
4.6
-
5.1
5.1
1.11
Osmundson et al. 2007
12.3
-
10.4
10.4
0.85
Osmundson et al. 2007
9.2
-
10.4
10.4
1.13
Osmundson et al. 2007
9.4
-
11
11
1.17
Osmundson et al. 2007
9.4
-
11.7
11.7
1.24
Osmundson et al. 2007
10.5
-
11.6
11.6
1.10
Osmundson et al. 2007
11.4
-
9.4
9.4
0.82
Osmundson et al. 2007
9.6
-
10.2
10.2
1.06
Osmundson et al. 2007
9.3
-
7.3
7.3
0.78
Osmundson et al. 2007
9.8
-
8.9
8.9
0.91
Osmundson et al. 2007
10.5
-
10.5
10.5
1.00
B-39
-------
White Sucker (Catostomus commersonii)
Study
Cmuscle
r
v^egg
r
^ovarv
r
^ess-ovarv
Ratio
Osmundson et al. 2007
11.1
10.2
10.2
0.92
Osmundson et al. 2007
12.1
-
8.1
8.1
0.67
Osmundson et al. 2007
12.8
-
9.5
9.5
0.74
Osmundson et al. 2007
16.0
-
10.7
10.7
0.67
Osmundson et al. 2007
12.1
-
8.3
8.3
0.69
Osmundson et al. 2007
9.0
-
12
12
1.33
Osmundson et al. 2007
10.6
-
6.1
6.1
0.58
Osmundson et al. 2007
12.6
-
6.1
6.1
0.48
Osmundson et al. 2007
11.6
-
11.3
11.3
0.97
Osmundson et al. 2007
2.8
-
2.6
2.6
0.93
Osmundson et al. 2007
2.5
-
3.6
3.6
1.44
Osmundson et al. 2007
4.3
-
4.4
4.4
1.02
Osmundson et al. 2007
3.5
-
4.4
4.4
1.26
Osmundson et al. 2007
4.3
-
4.8
4.8
1.12
Osmundson et al. 2007
3.1
-
4.3
4.3
1.39
Osmundson et al. 2007
3.6
-
4.1
4.1
1.14
Osmundson et al. 2007
3.0
-
3.8
3.8
1.27
Osmundson et al. 2007
4.1
-
3.6
3.6
0.88
Osmundson et al. 2007
3.6
-
3.8
3.8
1.06
egg-ovary
muscle
Median ratio: 1.00
R2: 0.59
F: 53.92
df: 38
P: <0.001
B-40
-------
Table B-3. Summary of egg-ovary to muscle conversion factors.
Common name
Scientific name
Median ratio
Bluegill
Lepomis macrochirus
1.38
Bluehead sucker
Catostomus discobolus
1.48
Brook trout
Salvelinus fontinalis
1.09
Common carp
Cyprinus carpio
1.14
Cutthroat trout
Oncorhynchus clarkii
1.81
Dolly Varden
Salvelinus malma
1.26
Flannelmouth sucker
Catostomus latipinnis
1.08
Green sunfish
Lepomis cyanellus
1.21
Mountain whitefish
Prosopium williamsoni
5.80
Northern pike
Esox lucius
1.88
Rainbow trout
Oncorhynchus mykiss
1.92
Razorback sucker
Xyrauchen texanus
2.31
Roundtail chub
Gila robusta
2.04
Smallmouth bass
Micropterus dolomieu
1.19
White sturgeon
Acipenser transmontanus
1.33
White sucker
Catostomus commersonii
1.00
B-41
-------
2.4 Muscle to whole-body conversion factors
n
^ whole-body
^muscle
Ratio
Selenium concentration in all tissues ((.ig/g dw)
Selenium concentration in muscle tissue only (fj.g/g dw)
c.
x muscle
C
whole-body
Black bullhead (Ameiurus melas)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
5.30
3.40
0.64
Osmundson et al. 2007
4.80
3.90
0.81
Osmundson et al. 2007
5.50
4.30
0.78
Osmundson et al. 2007
4.90
4.70
0.96
Osmundson et al. 2007
9.60
5.70
0.59
Osmundson et al. 2007
7.60
7.40
0.97
Osmundson et al. 2007
7.30
7.50
1.03
Osmundson et al. 2007
6.60
7.80
1.18
Osmundson et al. 2007
8.60
7.80
0.91
Osmundson et a
15 1
[. 2007
2.00
9.20
4.60
10 ¦
Median ratio:
0.93
f
^muscle
5 ¦
o
°OQ O
R2:
0.00
o
F:
0.03
°o°
df:
8
n
P:
0.973
u
5 10
15 Not used because P > 0.05.
-'whole-body
Bluegill (Lepomis macrochirus)
Study
Cwhole-bodv
Cmuscle
Ratio
Doroshov et al. 1992
1.60
1.50
0.94
Doroshov et al. 1992
5.50
5.80
1.05
Doroshov et al. 1992
9.30
10.40
1.12
Doroshov et al. 1992
19.30
23.60
1.22
Hermanutz et al. 1996
1.50
2.10
1.40
Hermanutz et al. 1996
18.10
20.60
1.14
Hermanutz et al. 1996
1.90
1.90
1.00
Hermanutz et al. 1996
2.80
3.50
1.25
B-42
-------
Bluegill (Lepomis macrochirus)
Study
Cwhole-bodv
Cmuscle
Ratio
Hermanutz et al.
996
12.30
17.60
1.43
Hermanutz et al.
996
9.40
12.50
1.33
Hermanutz et al.
996
1.50
2.30
1.53
Hermanutz et al.
996
4.90
6.90
1.41
Hermanutz et al.
996
21.00
44.90
2.14
Hermanutz et al.
996
24.30
39.80
1.64
Hermanutz et al.
996
2.70
3.40
1.26
Hermanutz et al.
996
5.00
5.30
1.06
Hermanutz et al.
996
9.50
12.50
1.32
Hermanutz et al.
996
6.60
7.80
1.18
Hermanutz et al.
996
1.80
3.20
1.78
Hermanutz et al.
996
4.20
6.10
1.45
Hermanutz et al.
996
10.30
18.70
1.82
Hermanutz et al.
996
13.80
15.10
1.09
Osmundson et al.
2007
8.80
12.90
1.47
-•muscle
50
25
Median ratio: 1.32
R
F
df
P
0.89
172.2
21
<0.001
25
50
-whole-body
B-43
-------
Bluehead sucker (Catostomus discobolus)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
1.30
1.50
1.15
Osmundson et al. 2007
2.00
2.30
1.15
Osmundson et al. 2007
2.10
2.50
1.19
Osmundson et al. 2007
2.20
2.70
1.23
Osmundson et al. 2007
2.40
3.10
1.29
Osmundson et al. 2007
3.90
5.20
1.33
Osmundson et al. 2007
5.60
8.60
1.54
10 n
-muscle
Median ratio: 1.23
R
F
df
P
10
"whole-body
0.99
682.9
5
<0.001
Brown trout (Salmo trutta)
Study
whole-bodv
muscle
Ratio
Osmundson et al. 2007
4.60
3.20
0.70
Osmundson et al. 2007
4.30
3.60
0.84
Osmundson et al. 2007
5.00
4.00
0.80
Osmundson et al. 2007
5.50
6.30
1.15
4 -
Median ratio: 0.82
R2:
0.78
F:
7.2
df:
2
P:
0.122
Not used because P > 0.05.
"whole-body
B-44
-------
Channel catfish (Ictalurus punctatus)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
3.40
3.40
1.00
Osmundson et al. 2007
3.30
3.60
1.09
Osmundson et al. 2007
2.60
3.70
1.42
Osmundson et al. 2007
4.00
5.30
1.33
"muscle
%
Median ratio: 1.21
R2:
0.49
F:
2.0
df:
2
P:
0.338
Not used because P > 0.05.
"whole-body
Common carp (Cyprinus carpio)
Study
r1
whole-bodv
Cmuscle Rati O
Osmundson et al. 2007
6.30
7.80
1.24
Osmundson et al. 2007
4.80
8.20
1.71
Osmundson et al. 2007
11.70
20.00
1.71
Osmundson et al. 2007
23.10
24.20
1.05
Osmundson et al. 2007
4.10
6.60
1.61
30
20
10 ¦
O o
10
20
30
Median ratio: 1.61
R2:
0.85
F:
17.6
df:
3
P:
0.017
-whole-body
B-45
-------
Flannelmouth sucker (Catostomus latipinnis)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
3.0
3.6
1.20
Osmundson et al. 2007
2.6
3.8
1.46
Osmundson et al. 2007
3.1
4.1
1.32
Osmundson et al. 2007
3.1
4.6
1.48
Osmundson et al. 2007
3.5
5.2
1.49
Osmundson et al. 2007
4.4
6.2
1.41
Osmundson et al. 2007
4.5
7.3
1.62
J
C 5
^muscle
whole body
Median ratio: 1.46
R2:
0.91
F:
50.1
df:
5
P:
<0.001
Green sunfish (Lepomis cyanellus)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
22.80
28.10
1.23
Osmundson et al. 2007
8.80
12.90
1.47
Osmundson et al. 2007
15.40
21.90
1.42
Osmundson et al. 2007
4.80
5.00
1.04
Osmundson et al. 2007
5.70
6.10
1.07
Osmundson et al. 2007
4.40
5.20
1.18
Osmundson et al. 2007
3.80
5.10
1.34
Osmundson et al. 2007
11.90
15.70
1.32
Osmundson et al. 2007
6.40
10.10
1.58
Osmundson et al. 2007
9.50
11.50
1.21
Osmundson et al. 2007
9.10
10.50
1.15
Osmundson et al. 2007
6.20
7.20
1.16
Osmundson et al. 2007
7.00
9.30
1.33
Osmundson et al. 2007
7.70
7.70
1.00
Osmundson et al. 2007
6.20
6.00
0.97
Osmundson et al. 2007
10.20
12.00
1.18
Osmundson et al. 2007
9.70
12.10
1.25
Osmundson et al. 2007
9.90
12.50
1.26
Osmundson et al. 2007
7.20
7.50
1.04
Osmundson et al. 2007
9.00
11.30
1.26
B-46
-------
Green sunfish (Lepomis cyanellus)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
9.70
13.60
1.40
Osmundson et al. 2007
8.90
13.20
1.48
Osmundson et al. 2007
9.80
12.40
1.27
Osmundson et al. 2007
9.90
12.50
1.26
Osmundson et al. 2007
10.30
8.60
0.83
Osmundson et al. 2007
5.30
5.30
1.00
Osmundson et al. 2007
10.10
11.90
1.18
Osmundson et al. 2007
11.80
13.60
1.15
Osmundson et al. 2007
3.30
3.80
1.15
Osmundson et al. 2007
4.00
4.20
1.05
Osmundson et al. 2007
4.30
4.10
0.95
Osmundson et al. 2007
3.70
4.20
1.14
Osmundson et al. 2007
6.20
5.70
0.92
Osmundson et al. 2007
3.50
4.40
1.26
Osmundson et al. 2007
4.40
3.50
0.80
Osmundson et al. 2007
5.60
5.50
0.98
Osmundson et al. 2007
4.90
5.00
1.02
Osmundson et al. 2007
4.40
4.30
0.98
Osmundson et al. 2007
8.00
10.10
1.26
Osmundson et al. 2007
7.90
11.90
1.51
Osmundson et al. 2007
6.40
11.10
1.73
Osmundson et al. 2007
8.70
11.80
1.36
Osmundson et al. 2007
8.30
11.00
1.33
Osmundson et al. 2007
6.10
7.10
1.16
Osmundson et al. 2007
5.60
6.70
1.20
Osmundson et al. 2007
18.10
26.40
1.46
Osmundson et al. 2007
9.40
9.60
1.02
Osmundson et al. 2007
12.20
16.70
1.37
Osmundson et al. 2007
5.30
8.10
1.53
Osmundson et al. 2007
7.30
10.60
1.45
Osmundson et al. 2007
9.30
14.20
1.53
Osmundson et al. 2007
6.80
11.30
1.66
Osmundson et al. 2007
7.50
12.80
1.71
B-47
-------
Green sunfish (Lepomis cyanellus)
Ratio
whole-body
muscle
Median ratio
muscle
whole-body
Roundtail chub (Gila robusta)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
4.10
4.30
1.05
Osmundson et al. 2007
5.30
5.00
0.94
Osmundson et al. 2007
6.40
6.20
0.97
Osmundson et al. 2007
6.80
6.90
1.01
Osmundson et al. 2007
5.50
7.00
1.27
Osmundson et al. 2007
6.60
7.30
1.11
Osmundson et al. 2007
8.40
9.80
1.17
Median ratio
muscle
whole-body
B-48
-------
Smallmouth bass (Micropterus dolomieu)
Study
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
Osmundson et al. 2007
12 -i
o
0 -I 1
0 6
f
^whole-body
Cwhole-bodv
Cmuscle
Ratio
4.20
3.70
0.88
5.50
6.50
1.18
5.40
6.90
1.28
7.80
11.0
1.41
5.10
7.10
1.08
4.90
8.80
1.57
Median ratio: 1.23
R2:
0.83
F:
20.2
df:
4
P:
0.008
White sucker (Catostomus commersonii)
Study
^whole-bodv
^ muscle
Ratio
Osmundson et al. 2007
3.80
2.90
0.76
Osmundson et al. 2007
4.20
4.80
1.14
Osmundson et al. 2007
3.30
3.70
1.12
Osmundson et al. 2007
4.50
3.70
0.82
Osmundson et al. 2007
6.30
8.40
1.33
Osmundson et al. 2007
6.80
9.40
1.38
Osmundson et al. 2007
11.00
15.50
1.41
Osmundson et al. 2007
12.70
23.60
1.86
Osmundson et al. 2007
5.70
9.40
1.65
Osmundson et al. 2007
3.90
6.10
1.56
Osmundson et al. 2007
3.80
4.60
1.21
Osmundson et al. 2007
9.90
12.30
1.24
Osmundson et al. 2007
5.30
9.20
1.74
Osmundson et al. 2007
10.70
9.40
0.88
Osmundson et al. 2007
5.90
9.40
1.59
Osmundson et al. 2007
7.00
10.50
1.50
Osmundson et al. 2007
6.40
11.40
1.78
Osmundson et al. 2007
6.30
9.60
1.52
Osmundson et al. 2007
5.30
9.30
1.75
Osmundson et al. 2007
6.20
9.80
1.58
B-49
-------
White sucker (Catostomus commersonii)
Study
Cwhole-bodv
Cmuscle
Ratio
Osmundson et al. 2007
5.60
10.50
1.88
Osmundson et al. 2007
8.80
11.10
1.26
Osmundson et al. 2007
8.70
12.10
1.39
Osmundson et al. 2007
11.40
12.80
1.12
Osmundson et al. 2007
10.70
16.00
1.50
Osmundson et al. 2007
8.40
12.10
1.44
Osmundson et al. 2007
7.00
9.00
1.29
Osmundson et al. 2007
7.50
10.60
1.41
Osmundson et al. 2007
10.30
12.60
1.22
Osmundson et al. 2007
6.70
11.60
1.73
Osmundson et al. 2007
2.10
2.80
1.33
Osmundson et al. 2007
1.80
2.50
1.39
Osmundson et al. 2007
3.20
4.30
1.34
Osmundson et al. 2007
2.30
3.50
1.52
Osmundson et al. 2007
3.10
4.30
1.39
Osmundson et al. 2007
3.00
3.10
1.03
Osmundson et al. 2007
2.80
3.60
1.29
Osmundson et al. 2007
2.50
3.00
1.20
Osmundson et al. 2007
3.40
4.10
1.21
Osmundson et al. 2007
2.80
3.60
1.29
Osmundson et al. 2007
3.10
5.60
1.81
Osmundson et al. 2007
5.50
6.30
1.15
Osmundson et al. 2007
7.00
9.10
1.30
Osmundson et al. 2007
7.30
8.50
1.16
Osmundson et al. 2007
2.40
3.00
1.25
Osmundson et al. 2007
2.70
4.40
1.63
Osmundson et al. 2007
2.70
3.20
1.19
Osmundson et al. 2007
2.60
1.60
0.62
Osmundson et al. 2007
19.60
28.10
1.43
Osmundson et al. 2007
9.80
12.10
1.23
Osmundson et al. 2007
8.70
11.80
1.36
Osmundson et al. 2007
8.70
12.60
1.45
Osmundson et al. 2007
9.10
12.30
1.35
Osmundson et al. 2007
13.40
18.00
1.34
Osmundson et al. 2007
3.10
2.80
0.90
Osmundson et al. 2007
2.40
3.20
1.33
Osmundson et al. 2007
2.10
3.10
1.48
Osmundson et al. 2007
3.20
4.30
1.34
Osmundson et al. 2007
2.80
3.40
1.21
B-50
-------
White sucker (Catostomus commersonii)
Ratio
whole-body
muscle
Median ratio
muscle
whole-body
Table B-4. Muscle to whole-body correction factor.
(0111111011 name
Scientific name
Median ratio
Bluegill
Lepomis macrochirus
1.32
Bluehead sucker
Catostomus discobolus
1.23
Common carp
Cyprinus carpio
1.61
Flannelmouth sucker
Catostomus latipinnis
1.46
Green sunfish
Lepomis cyanellus
1.23
Roundtail chub
Gila robusta
1.05
Smallmouth bass
Micropterus dolomieu
1.23
White sucker
Catostomus commersonii
1.34
Table B-5. Directly calculated final egg-ovary to whole body conversion factors (CF).
Common name
Median ratio
( eax-oYtm^ ^ whote-hoch")
Median ratio
( ^ eiy>-ovar\^ ^ muscle)
Muscle to
whole-body
correction
factor
l-'inal (7
\ allies
Species
Bluegill
2.13
2.13
Bluehead sucker
1.82
1.82
Brook trout
1.09
1.27
1.38
Brown trout
1.45
1.45
Common carp
1.92
1.92
Creek chub
1.99
1.99
Cutthroat trout
1.96
1.96
B-51
-------
Common 11 :imo
Modi;tii ratio
(Ceee_„
Median ratio
( ^ exx-ovary muscle)
Muscle to
whole-body
correction
factor
1 inal(/
\ allies
Desert pupfish
1.20
1.20
Dolly Varden
1.26
1.27
1.61
Fathead minnow
1.40
1.40
Flannelmouth sucker
1.41
1.41
Green sunfish
1.45
1.45
Mountain whitefish
5.80
1.27
7.39
Northern pike
1.88
1.27
2.39
Rainbow trout
1.92
1.27
2.44
Razorback sucker
2.31
1.34
3.11
Roundtail chub
2.07
2.07
Smallmouth bass
1.42
1.42
White sturgeon
1.33
1.27
1.69
White sucker
1.38
1.38
Genus
Catostomus
1.41
Gila
2.07
Lepomis
1.79
Micropterus
1.42
Oncorhynchus
1.96
Family
Catostomidae
1.41
Centrarchidae
1.45
Cyprinidae
1.95
Salmonidae
1.71
Order
Cyprinodontiformes
1.20
Perciformes
1.45
B-52
-------
Common 11 :imo
Modi;tii ratio
( L'xx-uvurx^ whole-bath")
Median ratio
( ^ L'UX-fH'an ^-muscle)
Muscle to
whole-body
correction
factor
Tinal CI'
\ allies
Class
Actinopterygii
1.45
B-53
-------
Table B-6. All EPA-derived egg-ovary to whole body (CF), egg-ovary to muscle, and muscle to whole body conversion factors directly calculated or estimated using taxonomic classification.
(See main text for explanation of the taxonomic classification approach).
Diivii i;iluil;ili;im-(I on l;i\(iniimii il;issil'ii;ili
-------
Diri-il i;iliul;ili;isi-tl mi l;i\imnmii il;issil'ii;ili
-------
( <11111111111
11.11111-
Si'ii'lllilli' 11 ;i UK-
Diivii i;iluil;ili;isi-il on l;i\(iniimii il;issil'ii;ili
-------
Diivii i;iluil;ili
-------
Diivii i;iluil;ili
-------
3.0 Derivation of Trophic Transfer Factor Values
3.1 Methodology
Taxa specific trophic transfer factors (TTF) to quantify the degree of biomagnification across a
given trophic level were calculated from either physiological parameters measured in laboratory studies
or from field measurements of paired selenium concentrations in consumer species and their food. TTFs
from both approaches were used to calculate translated water concentrations; however, when TTF data of
similar quality are available from both approached, as was the case with bluegill, field-derived TTF data
are used.
Physiological data consisted of assimilation efficiencies (AE), measured as either a percentage or
a proportion, ingestion rates (IR), measured as grams of Se per grams of food consumed per day, and
efflux rate constant (ke), measured as 1/day. All available data were collected for a particular species, and
then the TTF for that species was calculated using the equation:
„„„ AE X IR
TTF =
ke
Where AE, IR, and Ke were estimated as the median value of all available data for that parameter for that
species.
The majority of TTF were calculated using paired whole-body Se measurements from organisms
collected at the same site in the field. TTFs for trophic level 2 organisms were determined using the
equation:
rT.L2
mm t?T 1/2 tissue
111
nTLZ
^food.
Where Cj^d equals the average Se concentration in particulate matter, defined as the average of Caigae,
C detritus? and Csediment- Of the three types of particulate matter potentially assumed by TL2 organisms (e.g.,
the majority of invertebrates), Csediment correlated relatively poorly to Cj^ue, when compared to Caigae and
Cdetritus • In order to minimize potentially erroneous TTF calculations based solely on sediment Se
concentrations, while note completely discounting the importance of organic matter in sediments as a
potential food source, Csediment was included in Cpartlcuiate calculations only when either Caigae or Cdetntus data
were also available.
B-59
-------
TTFs for trophic level 3 organisms were determined using the equation:
rTL3
tt uTL3 tissue
1 1 r — —vTo—
flLi
^food
Where Cj^d equals the average whole-body Se concentration in invertebrates collected at the same site
as their potential predator species. The majority of trophic level 3 organisms are fish species, but
damselflies and dragonflies of the order Odonata are also trophic level 3 organisms, and TTFTL3 values
were calculated for those species as well.
For all field derived data used to determine TTFs, EPA first confirmed a statistical relationship
between whole-body selenium concentrations for each species and its food using OLS linear regression. If
the regression resulted in a statistically significant (P<0.05) positive slope, EPA calculated the TTF as the
median ratio of the paired concentration data.
B-60
-------
3.2 TTF values from physiological coefficients
AE (%) = Assimilation efficiency
IR (g g"1 d"1) = Ingestion rate
ke(d_1) = Efflux rate constant
jjp _ AExIR
KR
3.2.1 Invertebrates
Baltic macoma (Macoma balthica)
Physiological Parameters
AE (%) IR(g g1 d ')
ke (d"1)
TTF Study
22.5
91.0
84.0
95.0
78.0 0.03
74.0 0.03
92.3
58.0
85.8
64.9
90.4
Median Values and TTF
84.0 0.27a 0.03
Luomaetal. 1992
Luomaetal. 1992
Luomaetal. 1992
Luomaetal. 1992
Reinfelder et al. 1997
Reinfelder et al. 1997
Schleckat et al. 2002
Schleckat et al. 2002
Schleckat et al. 2002
Schleckat et al. 2002
Schleckat et al. 2002
7.56
' Value taken from Mytilus edulis
Short-necked clam (Ruditapes philippinarum)
Physiological Parameters
AE (%) IR(g g1 d ')
ke (d_1) TTF Study
70.0
52.0
Median Values and TTF
61.0 0.27a
0.013
0.013
0.013 12.67
Zhang et al. 1990
Zhang et al. 1990
' Value taken from Mytilus edulis
B-61
-------
Quahog (Mercenaria mercenaria)
Physiological Parameters
AE (%) IR(g g1 d ') ke (d1) TTF Study
Reinfelder and Fisher
100.1 1994
92.0 0.01 Reinfelder et al. 1997
Median Values and TTF
96.1 0.27a 0.01 25.93
a Value taken from Mytilus edulis
Eastern Oyster (Crassostrea virginica)
Physiological Parameters
AE (%) IR(g g1 d ') ke (d1) TTF Study
Okazaki and Panietz
0.005 1981
Reinfelder and Fisher
105.4 1994
70.0 0.070 Reinfelder et al. 1997
Median Values and TTF
87.7 0.27a 0.038 6.31
a Value taken from Mytilus edulis
Common mussel (Mytilus edulis)
Physiological Parameters
AE (%)
IR(g g1 d"1)
ke (d"1)
TTF Study
86.0
0.02
Reinfelder et al. 1997
75.0
0.05
Reinfelder et al. 1997
60.7
Wang and Fisher 1996
48.0
Wang and Fisher 1996
13.7
Wang and Fisher 1996
55.1
Wang and Fisher 1996
55.8
Wang and Fisher 1996
71.9
Wang and Fisher 1996
71.5
Wang and Fisher 1996
27.9
Wang and Fisher 1996
84.4
Wang and Fisher 1996
81.0
Wang and Fisher 1996
79.4
Wang and Fisher 1996
B-62
-------
Physiological Parameters
AE (%) IR(g g1 dx) ke (dx) TTF Study
63.0
0.037
Wang and Fisher 1996
61.5
0.05
Wang and Fisher 1996
69.0
0.027
Wang and Fisher 1996
81.0
0.022
Wang and Fisher 1997
82.0
0.020
Wang and Fisher 1997
72.0
0.018
Wang and Fisher 1997
78.0
0.055
Wang et al. 1995
76.0
0.065
Wang et al. 1995
71.0
0.058
Wang et al. 1995
33.9
Wang et al. 1996
27.5
Wang et al. 1996
Wang et al. 1996
Wang et al. 1996
0.27 0.022
Wang et al. 1996
0.026
Wang et al. 1996
0.019
Wang et al. 1996
Median Values and TTF
71.3 0.27 0.026 7.30
Asian clam (Corbicula fluminea)
Physiological Parameters
AE (%) IR(g g1 d ')
ke (d"1)
TTF Study
55.0 0.05
0.006
Lee et al. 2006
Median Values and TTF
55.0 0.05
0.006
4.58
B-63
-------
Zebra mussel (Dreissena polymorpha)
Physiological Parameters
AE (%)
IR(g g1 d"1)
ke (d"1)
TTF Study
18.0
Roditi and Fisher 1999
24.0
Roditi and Fisher 1999
46.0
Roditi and Fisher 1999
40.0
Roditi and Fisher 1999
41.0
Roditi and Fisher 1999
7.7
Roditi and Fisher 1999
23.0
Roditi and Fisher 1999
28.0
0.40
0.026
Roditi and Fisher 1999
Roditi and Fisher 1999
Roditi and Fisher 1999
Median Values and TTF
26.0 0.40 0.026 4.00
Water flea (Daphnia magna)
Physiological Parameters
AE (%) IR(g g1 d ') ke (d1) TTF Study
0.08
Goulet et al. 2007
0.34
Goulet et al. 2007
57.9
Yu and Wang 2002b
43.0
Yu and Wang 2002b
39.8
Yu and Wang 2002b
33.0
Yu and Wang 2002b
41.4
Yu and Wang 2002b
41.5
Yu and Wang 2002b
38.0
Yu and Wang 2002b
24.5
Yu and Wang 2002b
0.101
Yu and Wang 2002b
0.12
Yu and Wang 2002b
0.131
Yu and Wang 2002b
0.134
Yu and Wang 2002b
0.108
Yu and Wang 2002b
0.112
Yu and Wang 2002b
Median Values and TTF
40.6 0.21 0.12 0.74
B-64
-------
Copepod (Temora longicornis)
Physiological Parameters
AE (%) IR(g g1 d_1) ke (d') TTF Study
55.0 0.42
0.115
Wang and Fisher 1998
Median Values and TTF
55.0 0.42
0.115
2.01
Copepod (Small, unidentified)
Physiological Parameters
AE (%) IR(g g1 d ')
ke (d"1)
TTF
Study
50.0 0.42
0.155
Schlekat et al. 2004
Median Values and TTF
50.0 0.42
0.155
1.35
Copepod (Large, unidentified)
Physiological Parameters
AE (%) IR(g g 1 d ')
ke (d"1)
TTF
Study
52.0 0.42
0.155
Schlekat et al. 2004
Median Values and TTF
50.0 0.42
0.155
1.41
Blackworm (Lumbriculus variegatus)
Physiological Parameters
AE (%) IR(g g 1 d ')
ke (d"1)
TTF
Study
0.009
Riedel and Cole 2001
0.006
Riedel and Cole 2001
24.0 0.067
0.013
Riedel and Cole 2001
9.0 0.067
0.009
Riedel and Cole 2001
Median Values and TTF
16.5 0.067
0.0086
1.29
B-65
-------
Mayfly (Centroptilum triangulifer)a
Physiological Parameters
AE (%)
IR(g g1 d"1)
ke (d"1)
TTF Study
38.0
0.72
0.25
Riedel and Cole 2001
40.0
0.72
0.19
Riedel and Cole 2001
Median Values and TTF
39.0
0.72
0.22
1.28
a - not used because field TTF data available
3.2.2 Vertebrates
Bluegill (Lepomis macrochirus)a
Physiological Parameters
AE (%)
IRfeg-1*1) Md1)
TTF Study
34.0
Besser et al.
1993
22.0
Besser et al.
1993
24.0
Besser et al.
1993
36.0
Besser et al.
1993
30.0
Besser et al.
1993
32.0
Besser et al.
1993
43.0
Besser et al.
1993
40.0
Besser et al.
1993
37.0
0.041
Besser et al.
1993
0.031
Besser et al.
1993
0.034
Besser et al.
1993
36.0
0.031
Besser et al.
1993
0.038
Besser et al.
1993
0.038
Besser et al.
1993
0.008
Whitledge and Haywood
0.042
Whitledge and Haywood
Median Values and TTF
35.0 0.025 0.036 1.156s
a Not used because of availability of acceptable field-based TTF data
B-66
-------
Fathead Minnow (Pimephales promelas)
Physiological Parameters
AE (%) IR(g g1 d ')
ke (d"1)
TTF
Study
50.0
Presser and Luoma 2010
0.050
Bertram and Brooks 1986
0.029
Bertram and Brooks 1986
0.019
Bertram and Brooks 1986
0.3
Bertram and Brooks 1986
0.014
Bertram and Brooks 1986
0.013
Bertram and Brooks 1986
0.016
Bertram and Brooks 1986
0.012
Bertram and Brooks 1986
0.026
Bertram and Brooks 1986
0.018
Bertram and Brooks 1986
0.025
Bertram and Brooks 1986
Median Values and TTF
50.0 0.050
0.0185
1.35
Striped Bass (Morone saxatilis)
Physiological Parameters
AE (%) IR(g g1 d ')
ke (d"1)
TTF
Study
33 0.17
0.09
Baines et al. 2002
42 0.5
0.08
Baines et al. 2002
0.12
Buckel and Stoner 2004
0.16
Buckel and Stoner 2004
0.11
Buckel and Stoner 2004
0.08
Buckel and Stoner 2004
Median Values and TTF
37.5 0.335
0.085
1.48
TTF calculated from only Baines et al. (2002) because it had complete data.
B-67
-------
3.3 TTF values from field data
3.3.1 Invertebrates
Caig = Selenium concentration in algae (mg/kg)
Cdet = Selenium concentration in detritus (mg/kg)
Csed = Selenium concentration in sediment (mg/kg)
Cmvert = Selenium concentration in invertebrate tissue (mg/kg)
Cpart = Average selenium concentration in particulate material ^Cal3+C<^t+Csed
Ratio =
Cpart
Scuds (Amphipoda)
Study
Site
r
ale
Cdet
r
v sed
r
v n;trt
c
^invert
Ratio
Birkner 1978
29
8.80
15.40
12.10
18.40
1.52
Birkner 1978
20
3.00
41.00
22.00
11.40
0.52
Birkner 1978
7
0.18
2.80
1.49
2.90
1.95
Birkner 1978
19
16.80
1.20
9.00
4.30
0.48
Birkner 1978
30
17.30
47.30
32.30
22.50
0.70
Birkner 1978
3
0.10
0.30
0.20
2.30
11.50
Birkner 1978
22
4.60
44.00
24.30
7.60
0.31
Birkner 1978
23
7.80
10.80
9.30
11.30
1.22
Lambing et al. 1994
S46
2.30
2.30
3.20
1.39
Saiki et al.
1993
ET6
1.03
1.15
1.09
0.44
0.40
Saiki et al.
1993
ET6
1.03
1.15
1.09
0.86
0.79
Saiki et al.
1993
GT5
4.50
14.95
9.73
4.60
0.47
Saiki et al.
1993
GT5
4.50
14.95
9.73
3.30
0.34
Saiki et al.
1993
GT4
1.39
8.40
4.90
3.40
0.69
Saiki et al.
1993
GT4
1.39
8.40
4.90
3.70
0.76
Saiki et al.
1993
SJR2
1.25
5.00
3.13
3.80
1.22
Saiki et al.
1993
SJR2
1.25
5.00
3.13
2.80
0.90
Saiki et al.
1993
SJR3
0.45
1.25
0.85
1.50
1.77
Saiki et al.
1993
SJR3
0.45
1.25
0.85
1.10
1.30
Saiki et al.
1993
SJR1
0.22
0.50
0.36
0.89
2.47
Saiki et al.
1993
SJR1
0.22
0.50
0.36
1.30
3.61
Saiki et al.
1993
ET7
0.16
0.76
0.46
1.10
2.42
Saiki et al.
1993
ET7
0.16
0.76
0.46
1.10
2.42
B-68
-------
Scuds (Amphipoda)
-Inverts
23 ¦
20 -
15 -
o
10 ¦
5 ¦
0 ¦
1
10 20
c
v-p*rtic.
O
Median ratio: 1.22
40
R
F
df
P
0.69
46.9
21
<0.001
Earthworms and Leeches (Annelida)
Study
Site
r
ale
^ (lei
f
v sc(l
c
v n;trt
c
^invert
Ratio
Lemly 1985
Badin Lake
8.20
0.91
4.56
8.10
1.78
Lemly 1985
Belews Lake
62.70
8.27
35.49
51.15
1.44
Lemly 1985
High Rock Lake
8.25
0.79
4.52
9.05
2.00
60
50
40
r _ 30
-inverts
20
10
0
10
—,—
20
Median ratio: 1.78
R
F
df
P
—l
40
1.00
2426
1
<0.001
-pirtic.
B-69
-------
Midges (Chironomidae)
Study
Site
Calg
Cdet
Csed
C^art
Cjnvert
Ratio
Birkner 1978
29
8.80
15.40
12.10
58.20
4.81
Birkner 1978
19
16.80
1.20
9.00
15.30
1.70
Birkner 1978
30
17.30
47.30
32.30
59.30
1.84
Birkner 1978
3
0.10
0.30
0.20
2.50
12.50
Birkner 1978
22
4.60
44.00
24.30
18.80
0.77
Birkner 1978
27
10.35
6.50
8.43
26.70
3.17
Birkner 1978
12
2.30
0.30
1.30
7.70
5.92
Birkner 1978
23
7.80
10.80
9.30
34.20
3.68
Grasso et al. 1995
17
1.87
0.40
1.14
2.07
1.82
Lambing et al. 1994
S46
2.30
2.30
9.70
4.22
Saiki and Lowe 1987
Kesterson Pond 11
18.15
47.95
8.56
18.15
71.00
3.91
Saiki and Lowe 1987
Kesterson Pond 2
152.7
44.65
34.82
44.65
200.0
4.48
Saiki and Lowe 1987
Kesterson Pond 2
152.7
44.65
34.82
44.65
290.0
6.49
Saiki and Lowe 1987
Kesterson Pond 8
136.5
92.00
6.05
92.00
220.0
2.39
Saiki and Lowe 1987
San Luis Drain
67.00
275.0
79.90
79.90
190.0
2.38
Saiki and Lowe 1987
San Luis Drain
67.00
275.0
79.90
79.90
284.0
3.55
Saiki and Lowe 1987
Volta Pond 26
0.42
1.01
0.29
0.42
1.74
4.18
Saiki and Lowe 1987
Volta Pond 26
0.42
1.01
0.29
0.42
1.30
3.13
Saiki and Lowe 1987
Volta Pond 7
1.39
0.39
0.89
3.00
3.37
Saiki and Lowe 1987
Volta Pond 7
1.39
0.39
0.89
1.30
1.46
Saiki et al. 1993
ET6
1.03
1.15
1.09
0.58
0.53
Saiki et al. 1993
ET6
1.03
1.15
1.09
1.00
0.92
Saiki et al. 1993
GT5
4.50
14.95
9.73
8.90
0.92
Saiki et al. 1993
GT5
4.50
14.95
9.73
7.20
0.74
Saiki et al. 1993
GT4
1.39
8.40
4.90
5.40
1.10
Saiki et al. 1993
GT4
1.39
8.40
4.90
6.90
1.41
Saiki et al. 1993
SJR2
1.25
5.00
3.13
6.00
1.92
Saiki et al. 1993
SJR2
1.25
5.00
3.13
4.10
1.31
Saiki et al. 1993
SJR3
0.45
1.25
0.85
1.50
1.77
Saiki et al. 1993
SJR3
0.45
1.25
0.85
1.60
1.89
Saiki et al. 1993
SJR1
0.22
0.50
0.36
0.47
1.31
Saiki et al. 1993
SJR1
0.22
0.50
0.36
1.00
2.78
Saiki et al. 1993
ET7
0.16
0.76
0.46
0.53
1.16
Saiki et al. 1993
ET7
0.16
0.76
0.46
0.84
1.85
B-70
-------
Midges (Chironomidae)
inverts
partic.
100
Median ratio: 1.90
R
F
df
P
0.82
144.0
32
<0.001
Beetles (Coleoptera)
Study
Site
r
ale
^ (lei
r
v sed
r
v n;trt
r
^invert
Ratio
Schuler et al. 1990
Kesterson Pond 11
53.70
11.50
32.60
77.60
2.38
Schuleretal. 1990
Kesterson Pond 11
53.70
11.50
32.60
74.10
2.27
Schuler etal. 1990
Kesterson Pond 11
53.70
11.50
32.60
110.00
3.37
Schuleretal. 1990
Kesterson Pond 2
52.50
9.30
30.90
54.00
1.75
Schuleretal. 1990
Kesterson Pond 7
87.10
5.90
46.50
89.10
1.92
Schuleretal. 1990
Kesterson Pond 7
87.10
5.90
46.50
28.80
0.62
Schuleretal. 1990
Kesterson Pond 7
87.10
5.90
46.50
43.70
0.94
-"inverts
120 -I
100 ¦
80 ¦
60 ¦
40 -
20
0
0
o
o
20
—i—
40
60
ratio:
1.92
R2:
0.20
F:
1.24
df:
5
P:
0.36
Not used because P > 0.05 and negative
slope.
'pirtic.
Water boatmen (Corixidae)
Study
Site
Calg
^ del Csed
Cpart
Cjnvert
Ratio
Birkner 1978
18
7.60
4.30
5.95
8.40
1.41
Birkner 1978
29
8.80
15.40
12.10
29.40
2.43
B-71
-------
Water boatmen (Corixidae)
Study
Site
Calg
Cdet
Csed
C^art
Cjnvert
Ratio
Birkner 1978
20
3.00
41.00
22.00
11.00
0.50
Birkner 1978
7
0.18
2.80
1.49
4.20
2.82
Birkner 1978
3
0.10
0.30
0.20
4.20
21.00
Birkner 1978
22
4.60
44.00
24.30
9.90
0.41
Birkner 1978
12
2.30
0.30
1.30
7.30
5.62
Birkner 1978
23
7.80
10.80
9.30
15.50
1.67
Lambing et al. 1994
S46
2.30
2.30
3.40
1.48
Rinellaetal. 1994
G
0.84
0.50
0.67
1.38
2.06
Rinellaetal. 1994
A
2.21
0.40
1.31
2.98
2.28
Rinellaetal. 1994
Q
1.42
0.50
0.96
2.00
2.08
Saiki and Lowe 1987
Kesterson Pond 11
18.15
47.95
8.56
18.15
24.00
1.32
Saiki and Lowe 1987
Kesterson Pond 11
18.15
47.95
8.56
18.15
16.00
0.88
Saiki and Lowe 1987
Kesterson Pond 8
136.50
92.00
6.05
92.00
20.00
0.22
Saiki and Lowe 1987
Kesterson Pond 8
136.50
92.00
6.05
92.00
24.00
0.26
Saiki and Lowe 1987
Volta Pond 26
0.42
1.01
0.29
0.42
2.15
5.17
Saiki and Lowe 1987
Volta Pond 26
0.42
1.01
0.29
0.42
0.87
2.10
Saiki and Lowe 1987
Volta Pond 7
1.39
0.39
0.89
1.76
1.98
Saiki and Lowe 1987
Volta Pond 7
1.39
0.39
0.89
1.53
1.72
Schuler etal. 1990
Kesterson Pond 11
53.70
11.50
32.60
15.90
0.49
Schuler etal. 1990
Kesterson Pond 11
53.70
11.50
32.60
64.60
1.98
Schuler etal. 1990
Kesterson Pond 11
53.70
11.50
32.60
15.10
0.46
Schuler etal. 1990
Kesterson Pond 2
52.50
9.30
30.90
20.00
0.65
Schuler etal. 1990
Kesterson Pond 2
52.50
9.30
30.90
10.00
0.32
Schuler etal. 1990
Kesterson Pond 7
87.10
5.90
46.50
23.00
0.49
Schuler etal. 1990
Kesterson Pond 7
87.10
5.90
46.50
30.90
0.66
Schuler etal. 1990
Kesterson Pond 7
87.10
5.90
46.50
6.46
0.14
Rinella and Schuler
18
0.59
0.59
2.70
4.58
1992
-"inverts
pirtic.
100
Median ratio:
1.48
R2:
0.25
F:
9.17
df:
27
P:
<0.001
B-72
-------
Crayfish (Astacidae)
Study
Site
Calg
Cdet
Csed
C^art
Cjnvert
Ratio
Birkner 1978
29
8.80
15.40
12.10
23.30
1.93
Birkner 1978
19
16.80
1.20
9.00
10.10
1.12
Birkner 1978
30
17.30
47.30
32.30
36.80
1.14
Birkner 1978
22
4.60
44.00
24.30
11.30
0.47
Birkner 1978
27
10.35
6.50
8.43
20.00
2.37
Butler et al
1993
SP2
1.60
0.50
1.05
2.60
2.48
Butler et al
1993
SP2
1.60
0.50
1.05
2.90
2.76
Butler et al
1995
AK
0.45
0.20
0.33
0.76
2.34
Butler et al
1995
AK
0.45
0.20
0.33
0.79
2.43
Butler et al
1995
DD
0.88
0.70
0.79
0.62
0.78
Butler et al
1995
DD
0.88
0.70
0.79
1.10
1.39
Butler et al
1995
HD1
0.59
0.59
0.86
1.46
Butler et al
1995
HD1
0.59
0.59
0.79
1.34
Butler et al
1995
HD2
0.45
0.20
0.32
0.96
2.98
Butler et al
1995
HD2
0.45
0.20
0.32
1.00
3.10
Butler et al
1995
ME2
1.11
1.10
1.10
1.10
1.00
Butler et al
1995
ME2
1.11
1.10
1.10
1.40
1.27
Butler et al
1995
ME4
1.04
0.50
0.77
1.30
1.69
Butler et al
1995
ME4
1.04
0.50
0.77
1.80
2.35
Butler et al
1995
ME3
0.82
0.40
0.61
1.40
2.30
Butler et al
1995
ME3
0.82
0.40
0.61
3.70
6.07
Butler et al
1995
NW
3.45
1.60
2.53
4.20
1.66
Butler et al
1995
NW
3.45
1.60
2.53
3.30
1.31
Butler et al
1995
SD
0.77
0.50
0.64
1.40
2.20
Butler et al
1995
SD
0.77
0.50
0.64
1.40
2.20
Butler et al
1995
YJ2
0.31
0.10
0.21
1.40
6.83
Butler et al
1995
YJ2
0.31
0.10
0.21
1.50
7.32
Butler et al
1997
CHK
1.19
1.19
0.90
0.76
Butler et al
1997
MN2
0.79
0.79
0.83
1.06
Butler et al
1997
MUD2
1.30
1.30
3.10
2.38
Butler et al
1997
MUD2
1.30
1.30
3.80
2.92
Butler et al
1997
TRH
1.25
1.25
0.98
0.78
Butler et al
1997
TRH
1.25
1.25
1.60
1.28
Saiki et al.
1993
ET6
1.03
1.15
1.09
0.67
0.62
Saiki et al.
1993
ET6
1.03
1.15
1.09
0.83
0.76
Saiki et al.
1993
GT5
4.50
14.95
9.73
5.20
0.53
Saiki et al.
1993
GT5
4.50
14.95
9.73
4.40
0.45
Saiki et al.
1993
GT4
1.39
8.40
4.90
3.10
0.63
Saiki et al.
1993
GT4
1.39
8.40
4.90
3.20
0.65
Saiki et al.
1993
SJR2
1.25
5.00
3.13
1.70
0.54
Saiki et al.
1993
SJR2
1.25
5.00
3.13
1.90
0.61
B-73
-------
Crayfish (Astacidae)
Study
Site
r
ale
^ del
C C
v sed v n;trt
r
^invert
Ratio
Saikietal. 1993
SJR3
0.45
1.25
0.85
0.77
0.91
Saiki et al. 1993
SJR3
0.45
1.25
0.85
1.30
1.53
Saikietal. 1993
SJR1
0.22
0.50
0.36
0.50
1.39
Saikietal. 1993
SJR1
0.22
0.50
0.36
0.74
2.06
Saikietal. 1993
ET7
0.16
0.76
0.46
0.87
1.91
Saikietal. 1993
ET7
0.16
0.76
0.46
0.85
1.87
-'inverts
40
35
30
25
20
15
10
5
0
§
10
20
^"partic.
30
40
Median ratio: 1.46
R
F
df
P
0.74
130.8
45
<0.001
True flies (Diptera)
Study
Site
Calg
^ del Csed
C^art
Cjnvert
Ratio
Schuler et al. 1990
Kesterson Pond 11
53.70
11.50
32.60
126.00
3.87
Schuler et al. 1990
Kesterson Pond 11
53.70
11.50
32.60
85.10
2.61
Schuler et al. 1990
Kesterson Pond 2
52.50
9.30
30.90
117.00
3.79
Schuler et al. 1990
Kesterson Pond 2
52.50
9.30
30.90
93.30
3.02
Schuler etal. 1990
Kesterson Pond 2
52.50
9.30
30.90
105.00
3.40
Schuler etal. 1990
Kesterson Pond 7
87.10
5.90
46.50
95.50
2.05
Schuler etal. 1990
Kesterson Pond 7
87.10
5.90
46.50
97.70
2.10
Schuler etal. 1990
Kesterson Pond 7
87.10
5.90
46.50
102.00
2.19
140 -i
120 ¦
o
o
Median ratio:
2.81
100 ¦
o-
o
80 ¦
o
R2:
0.07
c
inverts gQ .
F:
0.46
df:
6
40 •
P:
0.65
20
0
Not used because P > 0.05 and negative
slope.
20 40
Cpartic.
60
B-74
-------
Mayflies (Ephemeroptera)
Study
Site
Calg
Cdet
Csed
C' [);nl
Cjnvert
Ratio
Rinellaetal. 1994
A
2.21
0.40
1.31
9.65
7.39
Casey 2005
Deerlick Creek
1.00
0.20
0.60
6.40
10.67
Casey 2005
Luscar Creek
5.50
3.20
2.40
3.20
8.20
2.56
Casey 2005
Deerlick Creek
1.00
0.20
0.60
5.70
9.50
Casey 2005
Luscar Creek
5.50
3.20
2.40
3.20
9.70
3.03
Casey 2005
Deerlick Creek
1.00
0.20
0.60
6.80
11.33
Casey 2005
Luscar Creek
5.50
3.20
2.40
3.20
12.30
3.84
Conley et al. 2009
Plate 10A
4.40
4.40
9.70
2.20
Conley et al. 2009
Plate 20A
25.50
25.50
34.80
1.36
Conley et al. 2009
Plate 20B
17.50
17.50
56.70
3.24
Conley et al. 2009
Plate 20C
8.70
8.70
16.20
1.86
Conley et al. 2009
Plate 20D
11.30
11.30
27.50
2.43
Conley et al. 2009
Plate 5A
2.20
2.20
4.20
1.91
Conley et al. 2009
Plate 5B
2.00
2.00
5.70
2.85
Conley etal. 2011
2x-High
40.90
40.90
37.30
0.91
Conley etal. 2011
2x-Low
9.50
9.50
14.10
1.48
Conley etal. 2011
2x-Medium
19.90
19.90
21.60
1.09
Conley et al. 2013
Control
2.20
2.20
5.10
2.32
Conley et al. 2013
Selenate-high
36.80
36.80
59.80
1.63
Conley et al. 2013
Selenate-low
12.80
12.80
31.70
2.48
Conley et al. 2013
Selenite-high
36.70
36.70
78.40
2.14
Conley et al. 2013
Selenite-low
12.80
12.80
29.80
2.33
-'inverts
90
80
70
60
50
40
30
20
10
0
10
20
c
30
40
Median ratio: 2.38
R2:
0.75
F:
59.19
df:
20
P:
<0.001
particulate
B-75
-------
Snails (Gastropoda)
Study
Site
r
ale
C C
^det ^sed
r
^oart
r
^invert
Ratio
Butler etal. 1995
WC
3.30
1.50
2.40
3.70
1.54
Butler etal. 1995
WC
3.30
1.50
2.40
3.90
1.63
Butler etal. 1995
WC
3.30
1.50
2.40
2.00
0.83
Butler etal. 1997
DCP1
1.00
2.10
1.55
3.50
2.26
Butler etal. 1997
MNP2
5.40
6.70
6.05
2.00
0.33
Butler etal. 1997
CHP
4.00
2.10
3.05
19.00
6.23
Butler etal. 1997
LCHP1
0.33
1.10
0.72
0.32
0.45
'Inverts
20
15
10
-o e
o
-jQ_
2 4
r
vp«rtic.
Median ratio:
1.54
R2:
0.01
F:
0.07
df:
5
P:
0.93
Not used because P >
O
O
Lh
Zooplankton
Study
Site
Calg
Cdet
Csed
C^art
Cjnvert
Ratio
Birkner 1978
29
8.80
15.40
12.10
31.30
2.59
Birkner 1978
20
3.00
41.00
22.00
11.00
0.50
Birkner 1978
7
0.18
2.80
1.49
3.30
2.22
Birkner 1978
19
16.80
1.20
9.00
7.70
0.86
Birkner 1978
3
0.10
0.30
0.20
3.40
17.00
Birkner 1978
27
10.35
6.50
8.43
42.50
5.04
Birkner 1978
12
2.30
0.30
1.30
5.80
4.46
Birkner 1978
23
7.80
10.80
9.30
15.40
1.66
Bowie et al. 1996
Hyco Reservoir
27.0
27.0
23.0
0.85
Lambing et al. 1988
12
1.40
0.30
0.85
2.60
3.06
Saiki and Lowe 1987
Kesterson Pond 11
18.15
47.95
8.56
18.15
68.30
3.76
Saiki and Lowe 1987
Kesterson Pond 2
152.70
44.65
34.82
44.65
83.00
1.86
Saiki and Lowe 1987
Kesterson Pond 8
136.50
92.00
6.05
92.00
100.00
1.09
Saiki and Lowe 1987
Volta Pond 26
0.42
1.01
0.29
0.42
1.46
3.51
Saiki and Lowe 1987
Volta Pond 7
1.39
0.39
0.89
2.90
3.26
Saiki and Lowe 1987
Volta Wasteway
0.87
2.03
0.24
0.87
2.80
3.21
Saiki etal. 1993
ET6
1.03
1.15
1.09
1.20
1.10
Saiki etal. 1993
ET6
1.03
1.15
1.09
1.50
1.38
B-76
-------
Zooplankton
Study
Site
Calg
^ (lei Csed CDart
Cjnvert
Ratio
Saikietal. 1993
GT5
4.50
14.95
9.73
2.40
0.25
Saikietal. 1993
GT5
4.50
14.95
9.73
5.40
0.56
Saikietal. 1993
GT4
1.39
8.40
4.90
4.50
0.92
Saikietal. 1993
GT4
1.39
8.40
4.90
4.40
0.90
Saikietal. 1993
SJR2
1.25
5.00
3.13
2.60
0.83
Saikietal. 1993
SJR2
1.25
5.00
3.13
4.30
1.38
Saikietal. 1993
SJR3
0.45
1.25
0.85
1.60
1.89
Saikietal. 1993
SJR3
0.45
1.25
0.85
1.80
2.12
Saikietal. 1993
SJR1
0.22
0.50
0.36
1.40
3.89
Saikietal. 1993
SJR1
0.22
0.50
0.36
1.30
3.61
Saikietal. 1993
ET7
0.16
0.76
0.46
0.63
1.38
Saikietal. 1993
ET7
0.16
0.76
0.46
1.40
3.08
140
120
100 ¦
80
60
40
20
0
jzf
20
40
c,
60
100
Median ratio: 1.89
R
F
df
P
0.71
76.3
31
<0.001
particulate
B-77
-------
Special case of Odonates (Damsclflics and Dragonflics) consuming invertebrates
n = Number of invertebrate food species co-occurring with an Odonate
species.
CPart = Average selenium concentration in particulate material
(mg/kg): (c-?tcy+c"-)
Cfood = Median selenium concentration in all invertebrate tissues that co-
occur with an Odonate species (mg/kg)
Cdamsel = Selenium concentration in damselfly tissue (mg/kg)
Cdragon = Selenium concentration in dragonfly tissue (mg/kg)
Ratio = Cf°od cdamsel Qr cdragon
Cpart Cfood Cfood
Co-occurring potential food species of damselflies and dragonflies (Odonata)
Study
Site
Co-occurs with:
n
r
^oart
Cfood
Ratio
Saiki and Lowe 1987
Kesterson
Pond 11
dragonflies
4
18.15
47.5
2.62
Saiki and Lowe 1987
Kesterson
Pond 2
dragonflies
4
44.65
206.5
4.62
Saiki and Lowe 1987
Kesterson
Pond 2
dragonflies
4
44.65
206.5
4.62
Saiki and Lowe 1987
Kesterson
Pond 8
dragonflies
5
92.00
120
1.30
Saiki and Lowe 1987
Kesterson
Pond 8
dragonflies
5
92.00
120
1.30
Saiki and Lowe 1987
Volta Pond 26
dragonflies
4
0.42
1.52
3.65
Saiki and Lowe 1987
Volta Pond 26
dragonflies
4
0.42
1.52
3.65
Saiki and Lowe 1987
Volta Pond 7
dragonflies
5
0.89
1.53
1.72
Saiki and Lowe 1987
Volta Pond 7
dragonflies
5
0.89
1.53
1.72
Saiki and Lowe 1987
Volta
Wasteway
dragonflies
2
0.87
1.83
2.10
Schuler et al. 1990
Kesterson
Pond 11
dragonflies
10
32.60
75.85
2.33
Schuler et al. 1990
Kesterson
Pond 11
dragonflies
10
32.60
75.85
2.33
Schuler et al. 1990
Kesterson
Pond 2
dragonflies
8
30.90
93.3
3.02
Schuler etal. 1990
Kesterson
Pond 2
dragonflies
8
30.90
93.3
3.02
B-78
-------
Co-occurring potential food species of damselflies and dragonflies (Odonata)
Study
Site
Co-occurs with:
n
C^art
Cfood
Ratio
Schuler et al.
1990
Kesterson
dragonflies
11
46.50
69.2
1.49
Pond 7
Schuler et al.
1990
Kesterson
dragonflies
11
46.50
69.2
1.49
Pond 7
Birkner 1978
29
damselflies
3
12.10
29.4
2.43
Birkner 1978
20
damselflies
2
22.00
11.2
0.51
Birkner 1978
7
damselflies
2
1.49
3.55
2.39
Birkner 1978
19
damselflies
2
9.00
9.8
1.09
Birkner 1978
30
damselflies
2
32.30
40.9
1.27
Birkner 1978
3
damselflies
3
0.20
2.5
12.50
Birkner 1978
22
damselflies
3
24.30
9.9
0.41
Birkner 1978
27
damselflies
1
8.43
26.7
3.17
Birkner 1978
23
damselflies
3
9.30
15.5
1.67
Grassoetal. 1995
17
damselflies
1
1.14
2.07
1.82
250 -I
200 ¦
o
150 ¦
Median
ratio:
2.21
Cfood |0O ¦
o
R2:
0.54
50 -
o/-o
F:
28.7
Q0"
9 " o
df:
24
0 *
t ®
Oo
1 1 1
i i
P:
<0.001
0 20 40 60 80 100
r
'-particulate
Damselflies (Anisoptera)
Study
Site
Cfood
r
^damsel
Ratio
Birkner 1978
29
29.4
55
1.87
Birkner 1978
4
1.95
1.8
0.92
Birkner 1978
25
18.7
21.9
1.17
Birkner 1978
20
11.2
18.7
1.67
Birkner 1978
7
3.55
4.4
1.24
Birkner 1978
19
9.8
28.4
2.90
Birkner 1978
6
4.2
11.1
2.64
Birkner 1978
30
40.9
53.3
1.30
Birkner 1978
3
2.5
3.1
1.24
Birkner 1978
22
9.9
15.8
1.60
B-79
-------
Damselflies (Anisoptera)
Study
Site
Cfood
c
^damsel
Ratio
Birkner 1978
27
26.7
45.1
1.69
Birkner 1978
23
15.5
18.4
1.19
Birkner 1978
11
5.9
7.7
1.31
Grassoetal. 1995
17
2.07
1.75
0.85
Grassoetal. 1995
9
8.2
6.98
0.85
100 -I
80 -
Median ratio:
1.30x2.21
60 -
r
damsel
40 ¦
O
o
(damselfly food to particulate) = 2.8
R2: 0.89
F: 104.4
8
20 ¦
df:
13
P:
<0.001
20
40
'food
Dragonflies (Zygoptera)
Study
Site
Cfood
Cdragon
Ratio
Mason et al. 2000
BK
1.845
1.665
0.90
Mason et al. 2000
HCRT
4.305
2.81
0.65
Saiki and Lowe 1987
Kesterson Pond 11
47.5
53
1.12
Saiki and Lowe 1987
Kesterson Pond 2
206.5
155
0.75
Saiki and Lowe 1987
Kesterson Pond 2
206.5
171
0.83
Saiki and Lowe 1987
Kesterson Pond 8
120
95.5
0.80
Saiki and Lowe 1987
Kesterson Pond 8
120
105
0.88
Saiki and Lowe 1987
Volta Pond 26
1.52
1.4
0.92
Saiki and Lowe 1987
Volta Pond 26
1.52
1.42
0.93
Saiki and Lowe 1987
Volta Pond 7
1.53
1.2
0.78
Saiki and Lowe 1987
Volta Pond 7
1.53
1.4
0.92
Saiki and Lowe 1987
Volta Wasteway
1.83
2.5
1.37
Schuleretal. 1990
Kesterson Pond 11
75.85
63.1
0.83
Schuleretal. 1990
Kesterson Pond 11
75.85
95.5
1.26
Schuleretal. 1990
Kesterson Pond 2
93.3
110
1.18
Schuleretal. 1990
Kesterson Pond 2
93.3
65
0.70
Schuleretal. 1990
Kesterson Pond 7
69.2
61.7
0.89
Schuleretal. 1990
Kesterson Pond 7
69.2
56.2
0.81
Sorenson & Schwarzbach 1991
5
0.42
0.49
1.17
B-80
-------
Dragonflies (Zygoptera)
200
150
-"dragon
4^-
Median ratio: 0.89x2.21
(damselfly food to particulate) = 1.97
R2:
0.95
F:
343.5
df:
17
P:
<0.001
100 200
Cfood
300
3.3.2 Vertebrates
Cinvert = Selenium concentration in invertebrate tissue (jj.g/g)
Cfish = Average selenium concentration in the whole-body of fish (jj.g/g)
Ratio =
C invert
Black bullhead (Ameiurus melas)
Study
Site
Cjnvert
Cfish
Ratio
Butler etal. 1991
7
29.80
39.00
1.31
GEI2013
SWA1
2.81
2.37
0.84
GEI2013
SWA1
2.81
2.73
0.97
GEI 2013
SWA1
2.81
3.96
1.41
GEI 2013
SWA1
2.81
1.95
0.70
GEI 2013
SWA1
2.81
3.21
1.14
Mueller etal. 1991
R2
6.40
9.70
1.52
Mueller etal. 1991
R2
6.40
9.20
1.44
Mueller etal. 1991
R1
8.70
7.40
0.85
Lemly 1985
Badin Lake
5.70
2.58
0.45
Lemly 1985
Belews Lake
51.15
17.32
0.34
Lemly 1985
High Rock Lake
9.05
3.24
0.36
GEI 2014
SC-6
27.54
8.42
0.31
B-81
-------
Black bullhead (Ameiurus melas)
45
40
35
30
25
20
15
10
5
0
I O O
Median ratio:
0.85
R2:
0.44
o
F:
8.52
df:
11
P:
0.006
10 20 30 40
^-Invvrit
50
60
Black crappie (Pomoxis nigromaculatus)
Study
Site
Cjnvert
Cfish
Ratio
Butler etal. 1995
Totten Reservoir
1.07
2.50
2.35
Butler etal. 1995
Summit Reservoir
1.85
1.70
0.92
Peterson et al. 1991
Ocean Lake, west side
3.83
4.20
1.10
Peterson et al. 1991
Ocean Lake, west side
3.83
6.32
1.65
Mueller etal. 1991
Lake Meredith near
6.40
13.00
2.03
Ordway, CO
Lambing et al. 1994
Priest Butte Lakes near
14.00
39.00
2.79
Choteau
Lambing et al. 1994
Priest Butte Lakes near
14.00
41.00
2.93
Choteau
Lambing et al. 1994
Priest Butte Lakes near
14.00
47.00
3.36
Choteau
Lambing et al. 1994
Priest Butte Lakes near
15.00
40.00
2.67
Choteau
Lambing et al. 1994
Priest Butte Lakes near
15.00
57.00
3.80
Choteau
Lambing et al. 1994
Priest Butte Lakes near
15.00
63.00
4.20
Choteau
B-82
-------
Black crappie (Pomoxis nigromaculatus)
Median ratio
Blacknose dace (Rhinichthys atratulus)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
Cabin Creek, C-CC1
4.40
4.65
1.06
GEI2014
Cabin Creek, C-CC1
4.40
4.74
1.08
GEI 2014
Cabin Creek, C-CC1
4.40
4.95
1.12
GEI 2014
Cabin Creek, C-CC1
4.40
4.69
1.06
GEI 2014
Cabin Creek, C-CC1
4.40
3.98
0.90
GEI 2014
Cabin Creek, C-CC2
5.56
3.46
0.62
GEI 2014
Cabin Creek, C-CC2
5.56
3.38
0.61
GEI 2014
Cabin Creek, C-CC2
5.56
3.95
0.71
GEI 2014
Cabin Creek, C-CC2
5.56
4.36
0.78
GEI 2014
Cabin Creek, C-CC2
5.56
4.39
0.79
GEI 2014
Coal Fork, C-CF1
3.39
3.58
1.06
GEI 2014
Coal Fork, C-CF 1
3.39
3.09
0.91
GEI 2014
Coal Fork, C-CF 1
3.39
3.37
0.99
GEI 2014
Coal Fork, C-CF 1
3.39
2.64
0.78
GEI 2014
Coal Fork, C-CF 1
3.39
3.42
1.01
GEI 2014
Hazy Creek, C-HC1
8.03
3.99
0.50
GEI 2014
Hazy Creek, C-HC1
8.03
5.88
0.73
GEI 2014
Hazy Creek, C-HC1
8.03
4.46
0.56
GEI 2014
Hazy Creek, C-HC1
8.03
6.55
0.82
GEI 2014
Hazy Creek, C-HC1
8.03
3.98
0.50
GEI 2014
Laurel Fork, C-LF1
12.73
5.36
0.42
GEI 2014
Laurel Fork, C-LF1
12.73
7.99
0.63
GEI 2014
Laurel Fork, C-LF1
12.73
8.72
0.68
GEI 2014
Laurel Fork, C-LF1
12.73
5.49
0.43
GEI 2014
Tenmile Fork, C-TF1
20.00
7.62
0.38
GEI 2014
Tenmile Fork, C-TF1
20.00
10.56
0.53
B-83
-------
Blacknose dace (Rhinichthys atratulus)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
Tenmile Fork, C-TF1
20.00
8.02
0.40
GEI2014
Tenmile Fork, C-TF1
20.00
5.63
0.28
GEI 2014
Tenmile Fork, C-TF1
Jack Smith (Bear)
20.00
5.68
0.28
GEI 2014
Branch, H-JSB1
Jack Smith (Bear)
4.03
2.81
0.70
GEI 2014
Branch, H-JSB1
Jack Smith (Bear)
4.03
1.86
0.46
GEI 2014
Branch, H-JSB1
Jack Smith (Bear)
4.03
1.78
0.44
GEI 2014
Branch, H-JSB1
Jack Smith (Bear)
4.03
2.47
0.61
GEI 2014
Branch, H-JSB1
4.03
2.55
0.63
GEI 2014
Lukey Fork, H-LF1
9.09
5.32
0.59
GEI 2014
Mud River, H-MR3
3.86
8.72
2.26
GEI 2014
Mud River, H-MR6
2.49
3.80
1.53
GEI 2014
Mud River, H-MR6
Sugartree Branch, H-
2.49
2.93
1.18
GEI 2014
SB1
Sugartree Branch, H-
10.62
9.82
0.92
GEI 2014
SB1
Sugartree Branch, H-
10.62
7.29
0.69
GEI 2014
SB1
Sugartree Branch, H-
10.62
11.14
1.05
GEI 2014
SB1
Sugartree Branch, H-
10.62
4.85
0.46
GEI 2014
SB1
10.62
7.16
0.67
GEI 2014
Stanley Fork, H-SF1
21.05
18.21
0.87
20
18
16
14
12
rO"
O
o
o.
o
10
JL
o
o
Median ratio:
0.71
S--
8
R2:
0.52
o
F:
48.97
df:
45
P:
<0.001
20
25
C,„.
B-84
-------
Bluegill (Lepomis macrochirus)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1995
XT
1.07
2.30
2.16
Hermanutz et al. 1996
MSO II
16.63
24.29
1.46
Hermanutz et al. 1996
MSO III
5.55
13.77
2.48
Hermanutz et al. 1996
MSO I
21.19
18.28
0.86
Hermanutz et al. 1996
MSO I
21.19
18.13
0.86
Hermanutz et al. 1996
MSO II
17.30
20.99
1.21
Hermanutz et al. 1996
MSO II
5.05
4.88
0.97
Hermanutz et al. 1996
MSO I
0.87
1.55
1.78
Hermanutz et al. 1996
MSO II
1.70
1.55
0.91
Hermanutz et al. 1996
MSO III
1.20
1.83
1.52
Hermanutz et al. 1996
MSO III
10.00
10.32
1.03
Hermanutz et al. 1996
MSO III
3.95
4.21
1.06
Hermanutz et al. 1996
MSO II
17.30
16.76
0.97
Hermanutz et al. 1996
MSO II
5.05
3.86
0.76
Mueller etal. 1991
R1
8.70
5.20
0.60
Saikietal. 1993
ET6
0.85
2.20
2.60
Saikietal. 1993
ET6
0.85
1.40
1.66
Saikietal. 1993
GT5
4.90
6.40
1.31
Saikietal. 1993
GT5
4.90
5.00
1.02
Saikietal. 1993
GT4
4.05
4.50
1.11
Saikietal. 1993
GT4
4.05
4.30
1.06
Saikietal. 1993
SJR2
3.30
3.30
1.00
Saikietal. 1993
SJR2
3.30
2.70
0.82
Saikietal. 1993
SJR3
1.50
2.00
1.33
Saikietal. 1993
SJR3
1.50
1.90
1.27
Saikietal. 1993
SJR1
0.95
0.87
0.92
Saikietal. 1993
SJR1
0.95
1.40
1.48
Saikietal. 1993
ET7
0.86
1.20
1.40
Saikietal. 1993
ET7
0.86
1.20
1.40
Crutchfield 2000
transect 3
21.80
19.91
0.91
Crutchfield 2000
transect 3
21.80
16.72
0.77
Crutchfield 2000
transect 3
17.90
19.91
1.11
Crutchfield 2000
transect 3
20.70
16.26
0.79
Crutchfield 2000
transect 3
20.35
29.87
1.47
Crutchfield 2000
transect 3
23.40
27.59
1.18
Crutchfield 2000
transect 3
15.20
23.10
1.52
Crutchfield 2000
transect 3
16.95
28.96
1.71
Crutchfield 2000
transect 3
16.95
19.91
1.17
Crutchfield 2000
transect 3
11.95
12.69
1.06
Crutchfield 2000
transect 3
11.40
18.09
1.59
Crutchfield 2000
transect 3
9.25
4.56
0.49
Crutchfield 2000
transect 3
9.25
5.40
0.58
B-85
-------
Bluegill (Lepomis macrochirus)
Study
Site
r
^invert
Cfish
Ratio
Crutchfield 2000
transect 3
8.60
4.56
0.53
Crutchfield 2000
transect 3
8.60
4.56
0.53
Crutchfield 2000
transect 4
30.70
51.60
1.68
Crutchfield 2000
transect 4
30.00
30.78
1.03
Crutchfield 2000
transect 4
33.20
31.69
0.95
Crutchfield 2000
transect 4
48.90
37.09
0.76
Crutchfield 2000
transect 4
38.55
49.78
1.29
Crutchfield 2000
transect 4
49.30
43.40
0.88
Crutchfield 2000
transect 4
43.90
22.65
0.52
Crutchfield 2000
transect 4
33.25
32.60
0.98
Crutchfield 2000
transect 4
25.40
18.09
0.71
Crutchfield 2000
transect 4
20.90
16.26
0.78
Crutchfield 2000
transect 4
20.90
26.22
1.25
Crutchfield 2000
transect 4
15.70
12.69
0.81
Crutchfield 2000
transect 4
15.70
9.04
0.58
Crutchfield 2000
transect 4
16.45
8.13
0.49
Crutchfield 2000
transect 4
18.25
9.96
0.55
Bowie et al. 1996
Hyco Reservoir
40.00
41.00
1.03
*0
AQ -
° o
oy'
Median ratio:
1.03
:u 0
O Q
10 • .0
V
o °
14
o
-------
Bluehead sucker (Catostomus discobolus)
Study
Site
c
^invert
Cfish
Ratio
Butler et al.
1993
D1
1.20
2.80
2.33
Butler et al.
1993
B1
1.25
1.90
1.52
Butler et al.
1993
B1
1.25
2.20
1.76
Butler et al.
1995
ME2
1.25
0.83
0.66
Butler et al.
1995
ME2
1.25
1.30
1.04
Butler et al.
1993
B2
1.35
1.80
1.33
Butler et al.
1995
SD
1.40
1.50
1.07
Butler et al.
1995
SD
1.40
1.80
1.29
Butler et al.
1993
D2
1.45
1.60
1.10
Butler et al.
1993
D2
1.45
2.30
1.59
Butler et al.
1993
PI
1.50
2.20
1.47
Butler et al.
1994
C0L1
1.50
1.60
1.07
Butler et al.
1994
RB3
1.60
13.00
8.13
Butler et al.
1995
YJ2
1.65
0.96
0.58
Butler et al.
1995
YJ2
1.65
2.80
1.70
Butler et al.
1994
NFK3
2.00
1.40
0.70
Butler et al.
1997
MN2
2.20
1.20
0.55
Butler et al.
1997
MUD
2.30
1.80
0.78
Butler et al.
1997
MUD
2.30
2.30
1.00
Butler et al.
1997
CHK
2.40
1.20
0.50
Butler et al.
1997
CHK
2.40
1.60
0.67
Butler et al.
1993
U1
2.45
4.80
1.96
Butler et al.
1995
SJ1
2.50
0.94
0.38
Butler et al.
1995
SJ1
2.50
1.20
0.48
Butler et al.
1995
SJ1
2.50
1.20
0.48
Butler et al.
1995
ME3
2.55
1.70
0.67
Butler et al.
1995
ME3
2.55
1.80
0.71
Butler et al.
1997
MN3
2.70
1.50
0.56
Butler et al.
1997
MN1
2.90
1.40
0.48
Butler et al.
1993
SP1
2.95
5.10
1.73
Butler et al.
1993
SP2
3.40
7.10
2.09
Butler et al.
1997
MUD2
3.45
2.50
0.72
Butler et al.
1997
MUD2
3.45
5.20
1.51
Butler et al.
1997
MUD2
3.45
5.60
1.62
Butler et al.
1993
F2
3.90
10.00
2.56
Butler et al.
1991
4
3.90
1.80
0.46
Butler et al.
1993
F2
4.80
0.94
0.20
Butler et al.
1994
BSW1
5.00
33.00
6.60
Butler et al.
1997
WBR
5.05
1.80
0.36
Butler et al.
1997
WBR
5.05
2.80
0.55
Butler et al.
1995
NW
5.10
7.20
1.41
Butler et al.
1995
NW
5.10
9.30
1.82
B-87
-------
Bluehead sucker (Catostomus discobolus)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1994
LZA1
19.00
9.00
0.47
Butler etal. 1994
RBI
21.00
22.00
1.05
Butler etal. 1994
GUN2
28.00
3.60
0.13
Median ratio
Brook stickleback (Culaea
inconstans)
Study
Site
Cjnvert
Cfish
Ratio
GEI2013
SWA1
2.81
4.40
1.57
GEI2013
SWA1
2.81
4.59
1.64
GEI 2013
SWA1
2.81
4.66
1.66
GEI 2013
SWA1
2.81
5.00
1.78
GEI 2013
SWA1
2.81
5.21
1.86
GEI 2013
SWA1
3.64
3.69
1.02
GEI 2013
SWA1
3.64
4.16
1.14
GEI 2013
SWA1
3.64
4.21
1.16
GEI 2013
SWA1
3.64
4.62
1.27
GEI 2013
SWA1
3.64
4.78
1.31
GEI 2013
SWA1
3.64
4.98
1.37
GEI 2013
SWA1
3.64
5.06
1.39
GEI 2013
SWA1
3.64
6.28
1.73
Lambing et al. 1994
S38
4.70
17.00
3.62
Lambing et al. 1994
S37
5.30
6.10
1.15
Lambing et al. 1994
S36
6.30
5.30
0.84
GEI 2014
Dry Creek, DC-2
3
3.14
0.92
GEI 2014
Dry Creek, DC-2
3
4.03
1.18
GEI 2014
Dry Creek, DC-2
3
3.76
1.10
GEI 2014
Dry Creek, DC-2
3
5.31
1.55
GEI 2014
Dry Creek, DC-2
3
4.59
1.34
GEI 2014
Dry Creek, DC-3
7
28.89
4.02
GEI 2014
Dry Creek, DC-3
7
66.07
9.20
B-88
-------
Brook stickleback (Culaea inconstans)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
Dry Creek, DC-3
7
24.43
3.40
GEI2014
Dry Creek, DC-3
7
25.36
3.53
GEI 2014
Dry Creek, DC-3
7
40.17
5.59
GEI 2014
Dry Creek, DC-3
9
25.80
2.80
GEI 2014
Dry Creek, DC-3
9
24.14
2.62
GEI 2014
Dry Creek, DC-3
9
22.46
2.43
GEI 2014
Dry Creek, DC-3
9
19.86
2.15
GEI 2013
SW2-1
6.60
21.14
3.21
GEI 2013
SW2-1
6.60
23.21
3.52
GEI 2013
SW2-1
6.60
23.64
3.58
GEI 2013
SW2-1
6.60
25.89
3.93
GEI 2013
SW2-1
6.60
27.71
4.20
GEI 2013
SW2-1
6.60
32.97
5.00
GEI 2013
SW2-1
6.60
34.54
5.24
GEI 2013
SW2-1
6.60
37.05
5.62
GEI 2013
SW2-1
6.60
39.26
5.95
GEI 2013
SW2-1
6.60
43.38
6.58
GEI 2013
SWB
7.06
15.74
2.23
GEI 2013
SWB
7.06
17.15
2.43
GEI 2013
SW1
7.82
9.96
1.27
GEI 2013
SW1
7.82
10.38
1.33
GEI 2013
SW1
7.82
10.58
1.35
GEI 2013
SW1
7.82
11.98
1.53
GEI 2013
SW11
8.41
6.36
0.76
GEI 2013
SW11
8.41
6.45
0.77
GEI 2013
SW2-1
9.14
21.09
2.31
Lambing et al. 1994
S34
14.00
35.00
2.50
Lambing et al. 1994
Sll
14.50
22.00
1.52
Lambing et al. 1994
Sll
14.50
26.00
1.79
70
60
50
40
30
20
10
0
i
Og ° o o
o
o
o
10
^inverts
15
20
Median ratio: 1.79
R
F
df
P
0.27
18.48
50
<0.001
B-89
-------
Brook trout (Salvelinus fontinalis)
Study
Site
c
^invert
Cfish
Ratio
Hamilton and Buhl 2004
use
0.50
2.40
4.80
Mason et al. 2000
BK
1.43
1.21
0.84
Mason et al. 2000
BK
1.43
1.57
1.10
Mason et al. 2000
BK
1.43
1.90
1.33
Mason et al. 2000
HCRT
2.81
0.99
0.35
Mason et al. 2000
HCRT
2.81
1.59
0.57
Mason et al. 2000
HCRT
2.81
2.95
1.05
Butler etal. 1997
MN1
2.90
2.20
0.76
Hamilton and Buhl 2005
LGC
7.80
6.90
0.88
Hamilton and Buhl 2005
UGC
9.30
9.80
1.05
Hamilton and Buhl 2004
DVC
12.80
8.00
0.63
Hamilton and Buhl 2004
use
0.50
2.40
4.80
12 -I
10 ¦
° /
8 ¦
Cfish 6
4 ¦
o
Median ratio:
R2:
0.88
0.83
O
F:
43.6
z
A
df:
9
5
c
10
15
invert
B-90
-------
Brown bullhead (Ameiurus nebulosus)
Study
Site
c
^invert
Cfish
Ratio
Rinellaand Schuler 1992
1.20
1.90
1.58
Mason et al.
2000
HCRT
2.81
0.22
0.08
Mason et al.
2000
HCRT
2.81
1.23
0.44
Mason et al.
2000
HCRT
2.81
1.83
0.65
2 1
2 -
o
"\o
o
Median ratio:
0.55
Cfisi 1
1 -
A
R2:
F:
df:
P
0.27
0.73
2
0 58
U
)
1 2
^"•invert.
3
Not used because P > 0.05 and negative
slope
Brown trout (Salmo trutta)
Study
Site
Cjnvert
Cfish
Ratio
Butler et al.
1991
10
4.80
2.00
0.42
Butler et al.
1991
12
2.80
5.40
1.93
Butler et al.
1991
4
3.90
3.30
0.85
Butler et al.
1991
4
3.90
3.50
0.90
Butler et al.
1991
3
6.20
3.50
0.56
Butler et al.
1993
SP2
3.40
3.40
1.00
Butler et al.
1993
SP2
2.75
1.20
0.44
Butler et al.
1993
B2
1.35
2.40
1.78
Butler et al.
1993
B2
1.35
2.70
2.00
Butler et al.
1993
B2
1.35
2.70
2.00
Butler et al.
1993
B1
1.25
4.20
3.36
Butler et al.
1993
D2
1.45
3.50
2.41
Butler et al.
1993
D2
1.45
3.50
2.41
Butler et al.
1993
D2
1.45
3.20
2.21
Butler et al.
1993
PI
1.95
3.30
1.69
Butler et al.
1993
LP2
1.00
1.70
1.70
Butler et al.
1993
LP2
1.00
2.10
2.10
Butler et al.
1993
LP2
1.00
1.60
1.60
Butler et al.
1993
LP3
1.12
2.10
1.88
Butler et al.
1993
LP3
1.12
2.80
2.51
Butler et al.
1993
LP4
3.20
1.80
0.56
B-91
-------
Brown trout (Salmo trutta)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1993
R2
3.90
5.40
1.38
Butler etal. 1993
R2
3.90
6.70
1.72
Butler etal. 1993
R2
3.70
5.90
1.59
Butler etal. 1993
ST2
4.10
6.00
1.46
Butler etal. 1994
GUN2
28.00
49.45
1.77
Butler etal. 1994
GUN2
28.00
5.90
0.21
Butler etal. 1994
HCC1
21.00
21.98
1.05
Butler etal. 1994
HCC1
21.00
42.00
2.00
Butler etal. 1994
NFK3
2.00
5.00
2.50
Butler etal. 1994
SMF
4.80
21.44
4.47
Butler etal. 1994
SMF
4.80
5.26
1.10
Butler etal. 1994
SMF
4.80
8.40
1.75
Butler etal. 1994
SMF
4.80
9.40
1.96
Formation 2012
CC-1A
12.24
10.51
0.86
Formation 2012
CC-1A
12.24
9.33
0.76
Formation 2012
CC-1A
12.57
9.95
0.79
Formation 2012
CC-1A
12.24
16.85
1.38
Formation 2012
CC-1A
13.55
14.03
1.04
Formation 2012
CC-3A
5.45
10.44
1.92
Formation 2012
CC-3A
5.45
9.20
1.69
Formation 2012
CC-3A
5.48
11.25
2.05
Formation 2012
CC-3A
14.50
15.38
1.06
Formation 2012
CC-3A
14.50
19.68
1.36
Formation 2012
CC-150
4.46
5.83
1.31
Formation 2012
CC-150
4.46
8.67
1.94
Formation 2012
CC-150
4.70
5.20
1.11
Formation 2012
CC-150
7.03
10.14
1.44
Formation 2012
CC-150
14.32
7.83
0.55
Formation 2012
CC-350
3.16
6.28
1.99
Formation 2012
CC-350
3.16
8.53
2.70
Formation 2012
CC-350
4.20
5.78
1.38
Formation 2012
CC-350
11.45
11.50
1.00
Formation 2012
CC-350
11.45
7.95
0.69
Formation 2012
CC-75
3.11
4.05
1.30
Formation 2012
CC-75
3.11
5.35
1.72
Formation 2012
CC-75
3.97
3.18
0.80
Formation 2012
CC-75
4.16
10.32
2.48
Formation 2012
CC-75
4.16
6.60
1.59
Formation 2012
DC-600
8.53
8.54
1.00
Formation 2012
DC-600
8.53
6.20
0.73
Formation 2012
DC-600
8.65
5.85
0.68
Formation 2012
DC-600
7.83
12.83
1.64
B-92
-------
Brown trout (Sulmo trutta)
Study
Site
c
^invert
Cfish
Ratio
Formation 2012
DC-600
7.83
10.54
1.35
Formation 2012
HS
15.70
16.52
1.05
Formation 2012
HS
15.70
25.00
1.59
Formation 2012
HS
18.70
24.90
1.33
Formation 2012
HS
27.80
32.63
1.17
Formation 2012
HS
27.80
22.80
0.82
Formation 2012
HS-3
11.40
20.60
1.81
Formation 2012
HS-3
11.40
18.83
1.65
Formation 2012
HS-3
13.41
17.89
1.33
Formation 2012
HS-3
24.70
23.68
0.96
Formation 2012
HS-3
26.55
28.97
1.09
Formation 2012
LSV-2C
22.62
19.45
0.86
Formation 2012
LSV-2C
22.62
12.78
0.56
Formation 2012
LSV-2C
26.31
22.67
0.86
Formation 2012
LSV-2C
30.00
19.53
0.65
Formation 2012
LSV-2C
26.95
20.96
0.78
Formation 2012
LSV-4
9.54
16.20
1.70
Formation 2012
LSV-4
9.54
15.18
1.59
Formation 2012
SFTC-1
2.42
3.68
1.52
Formation 2012
SFTC-1
3.21
2.25
0.70
Formation 2012
SFTC-1
1.63
6.70
4.11
Formation 2012
SFTC-1
2.49
2.64
1.06
Hamilton and Buhl 2005
CC
6.70
9.70
1.45
McDonald and Strosher 1998
60
ER 747
4.29
4.80
1.12
50
AQ -
0
o
Median ratio:
1.38
o
* 0 e H"
o
O-"""
, °^o ^ O
R2:
F:
df:
0.64
151.8
85
o
0
P:
<0.001
0 S 10 15
20 25 JO 35
.....
B-93
-------
Bullhead (Ameiurus sp.)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1995
ME3
2.55
3.00
1.18
Butler etal. 1993
R2
3.70
3.50
0.95
Butler etal. 1993
R2
3.70
4.00
1.08
Butler etal. 1994
BSW1
5.00
4.10
0.82
fish
2
c
Median ratio: 1.01
R
F
df
P
0.77
6.58
2
0.13
Not used because P > 0.05
invert.
Channel catfish (Ictaluruspunctatus)
Study
Site
Cjnvert
Cfish
Ratio
Butler etal. 1991
7
29.80
21.36
0.72
Butler etal. 1991
7
29.80
22.05
0.74
Butler etal. 1991
7
29.80
17.27
0.58
Butler etal. 1991
7
29.80
19.62
0.66
Butler etal. 1991
7
29.80
22.76
0.76
Butler etal. 1991
7
29.80
24.33
0.82
Butler etal. 1991
7
29.80
32.40
1.09
Butler etal. 1993
LP4
3.20
1.65
0.52
Butler etal. 1993
LP4
3.20
3.30
1.03
Butler etal. 1993
R2
3.90
9.30
2.39
Butler etal. 1993
R2
3.90
1.33
0.34
Butler etal. 1993
R2
3.70
2.04
0.55
Butler etal. 1993
R2
3.70
3.00
0.81
Butler etal. 1995
SJ1
2.50
1.73
0.69
Butler etal. 1995
SJ1
2.50
4.10
1.64
Butler etal. 1995
XT
1.07
1.00
0.94
Butler etal. 1997
MN4
2.65
4.20
1.58
Butler etal. 1997
MN5
8.60
5.00
0.58
Mueller etal. 1991
R1
8.70
2.20
0.25
Roddy et al. 1991
18
3.10
1.40
0.45
Roddy et al. 1991
18
3.10
1.60
0.52
Roddy et al. 1991
18
3.10
1.70
0.55
B-94
-------
Channel catfish (Ictaluruspunctatus)
Study Site Cinvert Cflsh Ratio
Roddy et al.
1991 18
3.10
1.80
0.58
Roddy et al.
1991 18
3.10
1.90
0.61
Roddy et al.
1991 18
3.10
2.20
0.71
Roddy et al.
1991 18
3.10
1.50
0.48
Roddy et al.
1991 18
3.10
1.70
0.55
Roddy et al.
1991 18
3.10
1.80
0.58
Roddy et al.
1991 18
3.10
2.00
0.65
Roddy et al.
1991 18
3.10
2.10
0.68
Roddy et al.
1991 18
3.10
2.20
0.71
Roddy et al.
1991 18
3.10
2.30
0.74
Roddy et al.
1991 18
3.10
2.40
0.77
Roddy et al.
1991 18
•u
3.10
3.10
1.00
0
A
Median ratio: 0.74
20 -
15 ¦
0
0
R2: 0.91
F: 332.8
10 ' O
df: 32
5 ¦ 0
m a
P: <0.001
II 5 10 15 20 25 3® 35
Common carp (Cyprinus carpio)
Study
Site
c
^invert
Cflsh
Ratio
Butler et al.
1991
10
4.80
10.30
2.15
Butler et al.
1991
7
29.80
25.80
0.87
Butler et al.
1991
7
29.80
31.00
1.04
Butler et al.
1991
7
29.80
40.00
1.34
Butler et al.
1991
7
29.80
50.00
1.68
Butler et al.
1991
9
4.10
3.90
0.95
Butler et al.
1991
3
6.20
2.20
0.35
Butler et al.
1993
D2
1.45
3.70
2.55
Butler et al.
1993
F2
7.50
5.80
0.77
Butler et al.
1993
R2
4.30
5.00
1.16
Butler et al.
1993
R2
3.90
4.80
1.23
Butler et al.
1993
R2
3.70
3.30
0.89
Butler et al.
1994
GUN2
28.00
63.00
2.25
Butler et al.
1994
NFK2
3.10
4.90
1.58
B-95
-------
Common carp (Cyprinus carpio)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1994
BSW1
5.00
12.00
2.40
Butler etal. 1994
RBI
21.00
5.10
0.24
Butler etal. 1995
ME4
1.55
3.90
2.52
Butler etal. 1995
ME4
1.55
3.70
2.39
Butler etal. 1995
ME4
1.55
3.80
2.45
Butler etal. 1995
ME3
2.55
4.40
1.73
Butler etal. 1995
ME3
2.55
5.20
2.04
Butler etal. 1995
SJ1
2.50
5.30
2.12
Butler etal. 1995
SJ1
2.50
3.40
1.36
Butler etal. 1995
MN1
2.70
5.80
2.15
Butler etal. 1995
MN1
2.70
9.80
3.63
Butler etal. 1995
MN1
2.70
5.40
2.00
Butler etal. 1997
MN5
8.60
16.00
1.86
Garcia-Hernandez et al. 2000
Cienega de Santa
Clara Wetland
3.00
3.30
1.10
GEI2013
SWB
7.06
12.50
1.77
GEI2013
SWB
7.06
15.61
2.21
GEI 2013
SW11
8.41
3.14
0.37
GEI 2013
SW11
8.41
3.52
0.42
GEI 2013
SW11
8.41
3.66
0.44
GEI 2013
SW11
8.41
3.85
0.46
GEI 2013
SW11
8.41
5.77
0.69
GEI 2013
SW11
8.41
3.60
0.43
GEI 2013
SW11
8.41
3.79
0.45
GEI 2013
SW11
8.41
3.95
0.47
GEI 2013
SW11
8.41
4.14
0.49
GEI 2013
SW11
8.41
4.34
0.52
GEI 2013
SW11
8.41
3.56
0.42
GEI 2013
SW2-1
6.60
26.73
4.05
GEI 2013
SW2-1
6.60
26.74
4.05
GEI 2013
SW2-1
6.60
28.74
4.36
GEI 2013
SW2-1
6.60
29.73
4.51
GEI 2013
SW2-1
6.60
41.57
6.30
GEI 2013
SW2-1
6.60
22.96
3.48
GEI 2013
SW2-1
6.60
24.27
3.68
GEI 2013
SW2-1
6.60
25.09
3.80
GEI 2013
SW2-1
6.60
31.74
4.81
GEI 2013
SW2-1
6.60
36.81
5.58
GEI 2013
SW2-1
9.14
13.29
1.45
GEI 2013
SW2-1
9.14
13.77
1.51
GEI 2013
SW2-1
9.14
20.49
2.24
GEI 2013
SW2-1
9.14
24.84
2.72
B-96
-------
Common carp (Cyprinus carpio)
Study
Site
c
^invert
Cfish
Ratio
GEI2013
SW2-1
9.14
23.65
2.59
GEI2013
SW2-1
9.14
27.27
2.99
GEI 2013
SW4-1
3.33
3.55
1.07
GEI 2013
SW4-1
3.33
4.68
1.41
GEI 2013
SW4-1
3.33
3.91
1.18
GEI 2013
SW4-1
3.33
4.36
1.31
GEI 2013
SW4-1
3.33
4.48
1.35
GEI 2013
SW4-1
3.33
4.60
1.38
GEI 2013
SW4-1
3.33
4.78
1.44
GEI 2013
SW9
4.45
2.73
0.61
GEI 2013
SW9
4.45
2.99
0.67
GEI 2013
SW9
4.45
3.64
0.82
GEI 2013
SW9
4.45
3.80
0.85
GEI 2013
SW9
4.45
3.90
0.88
GEI 2013
SW9
4.45
4.26
0.96
GEI 2013
SW9
4.45
4.53
1.02
GEI 2013
SW9
4.45
3.70
0.83
GEI 2013
SW9
4.45
3.77
0.85
GEI 2013
SW9
4.45
4.14
0.93
GEI 2013
SW9
4.45
4.41
0.99
GEI 2013
SW9
4.45
4.50
1.01
GEI 2013
SW9
4.45
4.69
1.05
GEI 2013
SW88
3.96
3.88
0.98
GEI 2013
SW88
3.96
5.33
1.35
GEI 2013
SW88
3.96
5.49
1.39
GEI 2013
SW88
3.96
5.66
1.43
Grassoetal. 1995
9
7.59
4.70
0.62
Grassoetal. 1995
9
7.59
4.93
0.65
Grassoetal. 1995
9
7.59
5.51
0.73
Lambing et al. 1994
S34
14.00
19.00
1.36
Lambing et al. 1994
S34
14.00
32.00
2.29
Low and Mullins 1990
5
5.60
1.20
0.21
Low and Mullins 1990
7
1.60
0.30
0.19
May et al. 2008
KR
17.20
7.78
0.45
May et al. 2008
NSCL
10.70
10.80
1.01
May et al. 2008
NSK
8.81
9.33
1.06
May et al. 2008
NSP
24.00
10.30
0.43
May et al. 2008
SSAL
11.50
10.50
0.91
May et al. 2008
SSAU
8.35
7.59
0.91
May et al. 2008
sso
10.00
8.48
0.85
May et al. 2008
ssw
7.60
10.40
1.37
Mueller etal. 1991
R2
6.40
14.40
2.25
B-97
-------
Common carp (Cyprinus carpio)
Study
Site
r
^invert
Cflsh
Ratio
Mueller etal. 1991
R2
6.40
14.00
2.19
Mueller etal. 1991
R1
8.70
5.60
0.64
Mueller etal. 1991
A3
6.00
6.50
1.08
Mueller etal. 1991
A6
5.60
3.40
0.61
Mueller etal. 1991
A2
8.50
7.30
0.86
Peterson et al. 1991
7
3.83
4.24
1.11
Peterson et al. 1991
7
3.83
4.41
1.15
Peterson et al. 1991
7
3.83
4.73
1.23
Peterson et al. 1991
7
3.83
5.16
1.35
Peterson et al. 1991
7
3.83
5.21
1.36
Roddy et al. 1991
18
3.10
3.20
1.03
Roddy et al. 1991
18
3.10
3.90
1.26
Roddy et al. 1991
18
3.10
4.60
1.48
Roddy et al. 1991
18
3.10
4.70
1.52
Roddy et al. 1991
18
3.10
4.80
1.55
Roddy et al. 1991
18
3.10
5.30
1.71
Lemly 1985
Badin Lake
5.70
3.17
0.56
Lemly 1985
Belews Lake
51.15
21.29
0.42
Lemly 1985
High Rock Lake
9.05
2.45
0.27
Rinellaand Schuler 1992
Harney Lake
2.05
2.20
1.07
Rinellaand Schuler 1992
S. Malheur Lake
1.20
2.00
1.67
o
° Median ratio: 1.20
0 10 20 30 40 50 60
^inverts
Creek chub (Semotilus atromaculatus)
Study Site Cinvert Cflsh Ratio
Mason et al. 2000 HCRT 2.81 0.49 0.18
Mason et al. 2000 HCRT 2.81 1.18 0.42
Mason et al. 2000 HCRT 2.81 1.97 0.70
GEI2013 SW4-1 3.33 4.65 1.40
GEI2013 SW4-1 3.33 4.96 1.49
B-98
-------
Creek chub (Semotilus atromaculatus)
Study
Site
c
^invert
Cfish
Ratio
GEI2013
SW4-1
3.33
5.52
1.66
GEI2013
SW4-1
3.33
6.11
1.84
GEI 2013
SW4-1
3.33
6.31
1.90
GEI 2013
SW4-1
3.33
6.53
1.96
GEI 2013
SW4-1
3.33
6.67
2.01
GEI 2013
LG1
3.37
3.41
1.01
GEI 2013
LG1
3.37
3.58
1.06
GEI 2013
LG1
3.37
3.75
1.11
GEI 2013
LG1
3.37
3.78
1.12
GEI 2013
LG1
3.37
4.10
1.22
GEI 2013
LG1
3.39
3.23
0.95
GEI 2013
LG1
3.39
3.72
1.10
GEI 2013
LG1
3.39
3.74
1.10
GEI 2013
LG1
3.39
3.78
1.12
GEI 2013
LG1
3.39
3.89
1.15
GEI 2013
LG1
3.39
4.03
1.19
GEI 2013
LG1
3.39
4.12
1.22
GEI 2013
LG1
3.39
5.11
1.51
GEI 2013
LG1
3.39
5.21
1.54
GEI 2013
LG1
3.39
5.34
1.58
GEI 2013
LG1
3.56
3.28
0.92
GEI 2013
LG1
3.56
3.37
0.95
GEI 2013
LG1
3.56
3.82
1.07
GEI 2013
LG1
3.56
3.86
1.09
GEI 2013
LG1
3.56
4.02
1.13
GEI 2013
LG1
3.56
4.16
1.17
GEI 2013
LG1
3.56
4.49
1.26
GEI 2013
LG1
3.56
4.53
1.27
GEI 2013
LG1
3.56
4.63
1.30
GEI 2013
LG1
3.56
4.77
1.34
GEI 2013
CC1
3.76
5.43
1.44
GEI 2013
CC1
3.76
5.57
1.48
GEI 2013
CC1
3.76
6.51
1.73
GEI 2013
CC1
3.76
6.71
1.78
GEI 2013
CC1
3.76
7.12
1.89
GEI 2013
CC1
4.69
3.99
0.85
GEI 2013
CC1
4.69
4.06
0.87
GEI 2013
CC1
4.69
4.08
0.87
GEI 2013
CC1
4.69
4.25
0.91
GEI 2013
CC1
4.69
4.44
0.95
GEI 2013
CC1
4.69
4.48
0.96
GEI 2013
CC1
4.69
4.50
0.96
B-99
-------
Creek chub (Semotilus atromaculatus)
Study
Site
c
^invert
Cfish
Ratio
GEI2013
CC1
4.69
4.72
1.01
GEI2013
CC1
4.69
5.24
1.12
GEI 2013
CC1
4.69
5.44
1.16
GEI 2013
CC1
5.86
4.98
0.85
GEI 2013
CC1
5.86
5.39
0.92
GEI 2013
CC1
5.86
5.77
0.99
GEI 2013
CC1
5.86
6.39
1.09
GEI 2013
CC1
5.86
6.43
1.10
GEI 2013
CC1
5.86
6.50
1.11
GEI 2013
CC1
5.86
6.57
1.12
GEI 2013
CC1
5.86
7.42
1.27
GEI 2013
CC1
5.86
7.42
1.27
GEI 2013
CC1
5.86
7.47
1.28
GEI 2014
Bond Creek, BC-2
2.96
2.46
0.83
GEI 2014
Bond Creek, BC-2
2.96
3.22
1.09
GEI 2014
Bond Creek, BC-2
2.96
2.64
0.89
GEI 2014
Bond Creek, BC-2
2.96
2.96
1.00
GEI 2014
Bond Creek, BC-2
2.96
4.47
1.51
GEI 2014
Bond Creek, BC-3
3.02
3.09
1.02
GEI 2014
Bond Creek, BC-3
3.02
2.91
0.96
GEI 2014
Bond Creek, BC-3
3.02
3.45
1.14
GEI 2014
Bond Creek, BC-3
3.02
2.69
0.89
GEI 2014
Bond Creek, BC-3
3.02
3.30
1.09
GEI 2014
Bond Creek, BC-3
5.87
3.44
0.59
GEI 2014
Bond Creek, BC-3
5.87
2.62
0.45
GEI 2014
Bond Creek, BC-3
5.87
3.23
0.55
GEI 2014
Cow Camp Creek, CC-2
5.65
3.05
0.54
GEI 2014
Cow Camp Creek, CC-2
5.65
3.69
0.65
GEI 2014
Cow Camp Creek, CC-2
5.65
3.84
0.68
GEI 2014
Cow Camp Creek, CC-2
5.65
4.44
0.79
GEI 2014
Cow Camp Creek, CC-2
5.65
3.98
0.70
GEI 2014
Hazy Creek, C-HC1
8.03
6.84
0.85
GEI 2014
Hazy Creek, C-HC1
8.03
3.78
0.47
GEI 2014
Hazy Creek, C-HC1
8.03
5.81
0.72
GEI 2014
Hazy Creek, C-HC1
8.03
4.29
0.53
GEI 2014
Hazy Creek, C-HC1
8.03
3.59
0.45
GEI 2014
Laurel Fork, C-LF1
12.73
6.52
0.51
GEI 2014
Laurel Fork, C-LF1
12.73
6.81
0.54
GEI 2014
Laurel Fork, C-LF1
12.73
5.11
0.40
GEI 2014
Laurel Fork, C-LF1
12.73
5.16
0.41
GEI 2014
Laurel Fork, C-LF1
12.73
5.46
0.43
GEI 2014
Little Marsh Fork, C-LMF1
6.02
3.81
0.63
B-100
-------
Creek chub (Semotilus atromaculatus)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
Little Marsh Fork, C-LMF1
6.02
4.89
0.81
GEI2014
Little Marsh Fork, C-LMF 1
6.02
3.58
0.60
GEI 2014
Little Marsh Fork, C-LMF 1
6.02
4.81
0.80
GEI 2014
Little Marsh Fork, C-LMF 1
6.02
5.82
0.97
GEI 2014
Dry Creek, DC-1
3.37
4.62
1.37
GEI 2014
Dry Creek, DC-1
3.37
5.15
1.53
GEI 2014
Dry Creek, DC-1
3.37
6.46
1.92
GEI 2014
Dry Creek, DC-1
3.37
5.73
1.70
GEI 2014
Dry Creek, DC-1
3.37
4.59
1.36
GEI 2014
Dry Creek, DC-1
2.29
4.94
2.16
GEI 2014
Dry Creek, DC-1
2.29
4.04
1.76
GEI 2014
Dry Creek, DC-1
2.29
3.62
1.58
GEI 2014
Dry Creek, DC-1
2.29
3.84
1.68
GEI 2014
Dry Creek, DC-1
2.15
4.02
1.87
GEI 2014
Dry Creek, DC-1
2.15
3.60
1.67
GEI 2014
Dry Creek, DC-1
2.15
3.28
1.52
GEI 2014
Dry Creek, DC-1
2.15
3.03
1.41
GEI 2014
Dry Creek, DC-1
2.15
4.01
1.86
GEI 2014
Dry Creek, DC-1
1.97
3.51
1.78
GEI 2014
Dry Creek, DC-2
3.42
5.32
1.56
GEI 2014
Dry Creek, DC-2
3.42
4.62
1.35
GEI 2014
Dry Creek, DC-2
3.42
4.43
1.30
GEI 2014
Dry Creek, DC-2
3.42
4.56
1.34
GEI 2014
Dry Creek, DC-2
3.42
6.38
1.87
GEI 2014
Dry Creek, DC-2
3.42
2.96
0.87
GEI 2014
Dry Creek, DC-2
3.42
3.58
1.05
GEI 2014
Dry Creek, DC-2
3.42
3.22
0.94
GEI 2014
Dry Creek, DC-2
3.42
4.07
1.19
GEI 2014
Dry Creek, DC-2
3.42
3.28
0.96
GEI 2014
Dry Creek, DC-2
3.16
6.52
2.07
GEI 2014
Dry Creek, DC-2
3.16
4.92
1.56
GEI 2014
Dry Creek, DC-2
3.16
3.10
0.98
GEI 2014
Dry Creek, DC-2
3.16
3.14
1.00
GEI 2014
Dry Creek, DC-2
3.16
4.36
1.38
GEI 2014
Dry Creek, DC-2
3.16
3.12
0.99
GEI 2014
Dry Creek, DC-2
3.16
5.40
1.71
GEI 2014
Dry Creek, DC-2
2.93
2.85
0.97
GEI 2014
Dry Creek, DC-2
2.93
4.94
1.69
GEI 2014
Dry Creek, DC-2
2.93
5.17
1.76
GEI 2014
Dry Creek, DC-2
2.93
3.47
1.18
GEI 2014
Dry Creek, DC-2
2.93
2.49
0.85
GEI 2014
Dry Creek, DC-3
7.18
23.79
3.31
B-101
-------
Creek chub (Semotilus atromaculatus)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
Dry Creek, DC-3
7.18
16.06
2.24
GEI2014
Dry Creek, DC-3
7.18
24.43
3.40
GEI 2014
Dry Creek, DC-3
7.18
22.20
3.09
GEI 2014
Dry Creek, DC-3
7.18
26.28
3.66
GEI 2014
Dry Creek, DC-3
9.23
21.48
2.33
GEI 2014
Dry Creek, DC-3
9.23
21.24
2.30
GEI 2014
Dry Creek, DC-3
9.23
21.46
2.33
GEI 2014
Dry Creek, DC-3
9.23
22.48
2.44
GEI 2014
Dry Creek, DC-3
9.23
18.80
2.04
GEI 2014
Dry Creek, DC-3
9.23
16.87
1.83
GEI 2014
Dry Creek, DC-4
19.42
15.86
0.82
GEI 2014
Dry Creek, DC-4
19.42
12.76
0.66
GEI 2014
Dry Creek, DC-4
19.42
28.50
1.47
GEI 2014
Dry Creek, DC-4
19.42
18.14
0.93
GEI 2014
Dry Creek, DC-4
19.42
17.55
0.90
GEI 2014
Dry Creek, DC-4
18.10
34.60
1.91
GEI 2014
Dry Creek, DC-4
18.10
23.70
1.31
GEI 2014
Foidel Creek, FOC-1
3.06
8.00
2.61
GEI 2014
Foidel Creek, FOC-1
3.06
9.68
3.16
GEI 2014
Foidel Creek, FOC-1
3.06
8.86
2.89
GEI 2014
Foidel Creek, FOC-1
3.06
2.51
0.82
GEI 2014
Foidel Creek, FOC-1
3.06
2.86
0.93
GEI 2014
Foidel Creek, FOC-1
3.06
4.24
1.39
GEI 2014
Foidel Creek, FOC-1
3.06
3.27
1.07
GEI 2014
Foidel Creek, FOC-1
3.06
5.03
1.64
GEI 2014
Foidel Creek, FOC-2
2.18
2.07
0.95
GEI 2014
Foidel Creek, FOC-2
2.18
3.06
1.41
GEI 2014
Foidel Creek, FOC-2
2.18
3.82
1.76
GEI 2014
Foidel Creek, FOC-2
2.18
2.26
1.04
GEI 2014
Foidel Creek, FOC-2
2.18
2.02
0.93
GEI 2014
Foidel Creek, FOC-2
2.18
2.28
1.05
GEI 2014
Foidel Creek, FOC-2
2.18
2.44
1.12
GEI 2014
Foidel Creek, FOC-2
2.18
2.62
1.21
GEI 2014
Grassy Creek, GC-2
4.20
5.28
1.26
GEI 2014
Grassy Creek, GC-2
4.20
6.13
1.46
GEI 2014
Grassy Creek, GC-2
4.20
6.29
1.50
GEI 2014
Grassy Creek, GC-2
4.20
4.80
1.15
GEI 2014
Grassy Creek, GC-2
4.20
4.59
1.09
GEI 2014
Grassy Creek, GC-2
4.58
3.27
0.71
GEI 2014
Grassy Creek, GC-2
4.58
5.50
1.20
GEI 2014
Grassy Creek, GC-2
4.58
3.64
0.80
GEI 2014
Grassy Creek, GC-2
4.58
4.29
0.94
B-102
-------
Creek chub (Semotilus atromaculatus)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
Grassy Creek
GC-2
4.58
3.01
0.66
GEI2014
Grassy Creek
GC-2
3.96
7.48
1.89
GEI 2014
Grassy Creek
GC-2
3.96
6.12
1.55
GEI 2014
Grassy Creek
GC-2
3.96
8.61
2.18
GEI 2014
Grassy Creek
GC-2
3.96
7.09
1.79
GEI 2014
Grassy Creek
GC-2
3.96
5.06
1.28
GEI 2014
Grassy Creek
GC-2
3.96
4.95
1.25
GEI 2014
Grassy Creek
GC-2
3.96
3.85
0.97
GEI 2014
Grassy Creek
GC-2
3.96
5.32
1.34
GEI 2014
Grassy Creek
GC-2
3.96
4.04
1.02
GEI 2014
Grassy Creek
GC-2
3.96
4.25
1.08
GEI 2014
Grassy Creek
GC-2
3.97
3.48
0.88
GEI 2014
Grassy Creek
GC-2
3.97
3.86
0.97
GEI 2014
Grassy Creek
GC-2
3.97
4.08
1.03
GEI 2014
Grassy Creek
GC-2
3.97
4.58
1.15
GEI 2014
Grassy Creek
GC-2
3.97
3.53
0.89
GEI 2014
Grassy Creek
GC-3
4.54
6.07
1.34
GEI 2014
Grassy Creek
GC-3
4.54
7.25
1.60
GEI 2014
Grassy Creek
GC-3
4.54
5.25
1.16
GEI 2014
Grassy Creek
GC-3
4.54
5.65
1.25
GEI 2014
Grassy Creek
GC-3
4.54
10.75
2.37
GEI 2014
Grassy Creek
GC-3
4.55
3.30
0.73
GEI 2014
Grassy Creek
GC-3
4.55
3.98
0.88
GEI 2014
Grassy Creek
GC-3
4.55
3.46
0.76
GEI 2014
Grassy Creek
GC-3
4.55
4.14
0.91
GEI 2014
Grassy Creek
GC-3
4.55
3.81
0.84
GEI 2014
Grassy Creek
GC-3
4.34
11.05
2.55
GEI 2014
Grassy Creek
GC-3
4.34
7.22
1.66
GEI 2014
Grassy Creek
GC-3
4.34
9.61
2.22
GEI 2014
Grassy Creek
GC-3
4.34
6.03
1.39
GEI 2014
Grassy Creek
GC-3
4.34
3.95
0.91
GEI 2014
Grassy Creek
GC-3
4.34
4.82
1.11
GEI 2014
Grassy Creek
GC-3
4.34
5.18
1.19
GEI 2014
Grassy Creek
GC-3
4.34
4.46
1.03
GEI 2014
Grassy Creek
GC-3
4.34
4.21
0.97
GEI 2014
Grassy Creek
GC-3
4.35
2.97
0.68
GEI 2014
Grassy Creek
GC-3
4.35
4.16
0.96
GEI 2014
Grassy Creek
GC-3
4.35
4.29
0.99
GEI 2014
Grassy Creek
GC-3
4.35
3.69
0.85
GEI 2014
Grassy Creek
GC-3
4.35
4.73
1.09
GEI 2014
Grassy Creek
GC-4
5.10
4.30
0.84
GEI 2014
Grassy Creek
GC-4
5.10
5.17
1.01
B-103
-------
Creek chub (Semotilus atromaculatus)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
Grassy Creek, GC-4
5.10
5.46
1.07
GEI2014
Grassy Creek, GC-4
5.10
5.63
1.10
GEI 2014
Grassy Creek, GC-4
5.10
5.15
1.01
GEI 2014
Grassy Creek, GC-4
5.76
7.72
1.34
GEI 2014
Grassy Creek, GC-4
5.76
6.04
1.05
GEI 2014
Grassy Creek, GC-4
5.76
7.88
1.37
GEI 2014
Grassy Creek, GC-4
5.76
9.77
1.70
GEI 2014
Grassy Creek, GC-4
5.76
7.35
1.28
GEI 2014
Grassy Creek, GC-4
5.76
4.17
0.72
GEI 2014
Grassy Creek, GC-4
5.76
4.86
0.84
GEI 2014
Grassy Creek, GC-4
5.76
5.02
0.87
GEI 2014
Grassy Creek, GC-4
5.76
4.79
0.83
GEI 2014
Grassy Creek, GC-4
5.76
6.56
1.14
GEI 2014
Grassy Creek, GC-4
5.76
5.31
0.92
GEI 2014
Grassy Creek, GC-4 US
13.16
4.05
0.31
GEI 2014
Grassy Creek, GC-4 US
13.16
4.80
0.36
GEI 2014
Grassy Creek, GC-4 US
13.16
5.41
0.41
GEI 2014
Grassy Creek, GC-4 US
13.16
6.05
0.46
GEI 2014
Big Horse Creek, H-BHC3
5.78
3.96
0.69
GEI 2014
Big Horse Creek, H-BHC3
5.78
2.97
0.51
GEI 2014
Big Horse Creek, H-BHC3
5.78
3.84
0.66
GEI 2014
Sally Fork, H-BLB2
1.64
2.42
1.48
GEI 2014
Sally Fork, H-BLB2
1.64
1.65
1.01
GEI 2014
Sally Fork, H-BLB2
1.64
1.68
1.03
GEI 2014
Sally Fork, H-BLB2
1.64
2.02
1.23
GEI 2014
Sally Fork, H-BLB2
1.64
1.46
0.89
GEI 2014
Hubberson Gulch, HG-2
3.44
4.41
1.28
GEI 2014
Hubberson Gulch, HG-2
3.44
3.56
1.04
GEI 2014
Hubberson Gulch, HG-2
3.44
4.48
1.30
GEI 2014
Hubberson Gulch, HG-2
1.46
2.95
2.03
GEI 2014
Hubberson Gulch, HG-2
1.46
2.66
1.83
GEI 2014
Hubberson Gulch, HG-2
Jack Smith (Bear) Branch,
1.46
2.87
1.97
GEI 2014
H-JSB1
Jack Smith (Bear) Branch,
4.03
3.04
0.75
GEI 2014
H-JSB1
Jack Smith (Bear) Branch,
4.03
1.81
0.45
GEI 2014
H-JSB1
Jack Smith (Bear) Branch,
4.03
2.35
0.58
GEI 2014
H-JSB1
Jack Smith (Bear) Branch,
4.03
1.91
0.47
GEI 2014
H-JSB1
4.03
2.83
0.70
GEI 2014
Laurel Creek, H-LC1
4.57
1.29
0.28
B-104
-------
Creek chub (Semotilus atromaculatus)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
Laurel Creek, H-LC1
4.57
2.04
0.45
GEI2014
Laurel Creek, H-LC1
4.57
1.49
0.33
GEI 2014
Laurel Creek, H-LC1
4.57
1.85
0.41
GEI 2014
Laurel Creek, H-LC1
4.57
0.67
0.15
GEI 2014
Lick Creek, H-LKC1
2.59
1.83
0.71
GEI 2014
Lick Creek, H-LKC 1
2.59
1.40
0.54
GEI 2014
Lick Creek, H-LKC 1
2.59
1.41
0.54
GEI 2014
Lick Creek, H-LKC 1
2.59
1.19
0.46
GEI 2014
Lick Creek, H-LKC 1
2.59
1.22
0.47
GEI 2014
Mud River, H-MR3
3.86
4.75
1.23
GEI 2014
Mud River, H-MR3
3.86
4.60
1.19
GEI 2014
Mud River, H-MR3
3.86
5.06
1.31
GEI 2014
Mud River, H-MR3
3.86
3.32
0.86
GEI 2014
Mud River, H-MR3
3.86
4.19
1.08
GEI 2014
Mud River, H-MR5
3.58
1.51
0.42
GEI 2014
Mud River, H-MR5
3.58
1.43
0.40
GEI 2014
Mud River, H-MR5
3.58
1.98
0.55
GEI 2014
Mud River, H-MR5
3.58
3.80
1.06
GEI 2014
Mud River, H-MR5
3.58
3.44
0.96
GEI 2014
Sugartree Branch, H-SB1
10.62
7.29
0.69
GEI 2014
Sugartree Branch, H-SB 1
10.62
7.56
0.71
GEI 2014
Sugartree Branch, H-SB 1
10.62
6.20
0.58
GEI 2014
Middle Creek, MC-1
3.21
2.75
0.86
GEI 2014
Middle Creek, MC-1
3.21
4.74
1.48
GEI 2014
Middle Creek, MC-1
3.21
4.01
1.25
GEI 2014
Middle Creek, MC-1
3.21
3.94
1.23
GEI 2014
Middle Creek, MC-1
3.21
3.63
1.13
GEI 2014
Middle Creek, MC-1
3.21
1.83
0.57
GEI 2014
Middle Creek, MC-1
3.21
1.85
0.57
GEI 2014
Middle Creek, MC-1
3.21
2.50
0.78
GEI 2014
Middle Creek, MC-1
3.21
2.33
0.73
GEI 2014
Middle Creek, MC-1
3.21
2.56
0.80
GEI 2014
Middle Creek, MC-2
4.19
1.93
0.46
GEI 2014
Middle Creek, MC-2
4.19
1.89
0.45
GEI 2014
Middle Creek, MC-2
4.19
2.51
0.60
GEI 2014
Middle Creek, MC-2
4.19
1.87
0.45
GEI 2014
Middle Creek, MC-2
4.19
2.13
0.51
GEI 2014
Sage Creek, SC-3
2.29
7.33
3.20
GEI 2014
Sage Creek, SC-3
2.29
7.23
3.16
GEI 2014
Sage Creek, SC-3
2.29
7.60
3.32
GEI 2014
Sage Creek, SC-3
2.29
4.77
2.08
GEI 2014
Sage Creek, SC-3
2.29
8.70
3.80
B-105
-------
Creek chub (Semotilus atromaculatus)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
Sage Creek, SC-4
23.79
18.77
0.79
GEI2014
Sage Creek, SC-4
23.79
20.08
0.84
GEI 2014
Sage Creek, SC-4
23.79
13.05
0.55
GEI 2014
Scotchmans Gulch, SG-1A
7.16
7.41
1.04
GEI 2014
Scotchmans Gulch, SG-1A
7.16
7.65
1.07
GEI 2014
Scotchmans Gulch, SG-1A
7.16
4.47
0.62
GEI 2014
Scotchmans Gulch, SG-1A
7.16
5.83
0.81
GEI 2014
Scotchmans Gulch, SG-1A
7.16
5.37
0.75
GEI 2014
Scotchmans Gulch, SG-1A
7.16
5.69
0.80
GEI 2014
Scotchmans Gulch, SG-1A
7.16
4.31
0.60
o
Median ratio: 1.06
10 15
^inverts
o
20
25
R2:
0.41
F:
214.7
df:
303
P:
<0.001
Cutthroat trout (Oncorhynchus clarkii)
Study
Site
r
^invert
Cfish
Ratio
Hamilton and Buhl 2004
ShpC
1.90
1.80
0.95
McDonald and Strosher 1998
ER 745
2.74
5.40
1.97
Hamilton and Buhl 2005
SC
4.10
3.50
0.85
McDonald and Strosher 1998
ER 747
4.29
6.57
1.53
Hamilton and Buhl 2005
UAC
5.00
6.60
1.32
Hamilton and Buhl 2004
ACM
6.70
6.30
0.94
Hamilton and Buhl 2005
DC
8.70
11.00
1.26
McDonald and Strosher 1998
ER 746
10.70
12.71
1.19
Hamilton and Buhl 2005
BGS
10.80
12.20
1.13
Hamilton and Buhl 2004
DVC
12.80
10.20
0.80
Hamilton and Buhl 2004
UEMC
26.90
27.00
1.00
Hamilton and Buhl 2004
LEMC
75.20
52.30
0.70
Minnow 2007
BA6
3.27
6.98
2.13
Minnow 2007
AL4
3.92
4.44
1.13
Minnow 2007
MI5
4.00
5.12
1.28
B-106
-------
Cutthroat trout (Oncorhynchus clarkii)
Study
Site
c
^invert
Cfish
Ratio
Minnow 2007
EL12
4.01
7.42
1.85
Minnow 2007
EL14
4.41
4.52
1.02
Minnow 2007
F09
4.44
7.80
1.76
Minnow 2007
MI3
6.21
5.65
0.91
Minnow 2007
MI2
6.69
5.16
0.77
Minnow 2007
ELI
7.08
4.82
0.68
Minnow 2007
LI8
7.81
9.36
1.20
Minnow 2007
FO10
17.51
45.94
2.62
Minnow 2007
HA7
22.41
21.10
0.94
Minnow 2007
CL11
30.87
57.27
1.86
Orr et al. 2012
Alexander Creek
3.92
2.71
0.69
Orr et al. 2012
Elk River 1
6.23
5.61
0.90
Orr et al. 2012
Elk River 1
6.23
7.94
1.27
Orr et al. 2012
Elk River 1
7.08
5.35
0.76
Orr et al. 2012
Elk River 12
3.81
4.58
1.20
Orr et al. 2012
Elk River 12
4.01
4.89
1.22
Orr et al. 2012
Fording River 22
3.10
10.28
3.32
Orr et al. 2012
Fording River 23
7.72
7.92
1.03
Orr et al. 2012
Fording River 9
4.44
6.92
1.56
Orr et al. 2012
Line Creek 8
6.61
7.99
1.21
Orr et al. 2012
Line Creek 8
7.81
7.13
0.91
Orr et al. 2012
Michel Creek 2
8.38
5.13
0.61
Orr et al. 2012
Michel Creek 2
6.69
4.63
0.69
Orr et al. 2012
Michel Creek 3
5.42
3.51
0.65
Orr et al. 2012
Michel Creek 3
6.21
4.02
0.65
Orr et al. 2012
Michel Creek 5
4.00
4.12
1.03
Orr et al. 2012
Fording River
MP1
Barnes Lake
5.49
6.84
1.25
Orr et al. 2012
Wetland 6
3.27
3.92
1.20
Orr et al. 2012
Clode Pond 11
32.22
41.27
1.28
Orr et al. 2012
Clode Pond 11
30.87
44.70
1.45
Orr et al. 2012
Elk Lakes 14
6.40
7.14
1.12
Orr et al. 2012
Elk Lakes 14
4.41
4.35
0.99
Orr et al. 2012
Fording River
Oxbow 10
49.26
24.34
0.49
Orr et al. 2012
Fording River
Oxbow 10
17.51
34.41
1.97
Orr et al. 2012
Henretta Lake 27
9.16
6.90
0.75
Orr et al. 2012
O'Rourke Lake 1
3.63
8.05
2.22
Orr et al. 2012
Harmer Pond 7
22.41
13.08
0.58
B-107
-------
Cutthroat trout (Oncorhynchus clarkii)
Study Site
c
^invert
Cfish
Ratio
60
50
40
30
20
10
0
O
O
O
%
a-
^0'
o
20
40
^inverts
60
Median ratio: 1.12
R
F
df
P
0.66
95.81
50
<0.001
Fathead minnow (Pimephales promelas)
Study
Site
Cjnvert
Cfish
Ratio
Birkner 1978
4
1.80
2.10
1.17
Birkner 1978
22
11.30
11.00
0.97
Birkner 1978
27
34.60
79.00
2.28
Birkner 1978
23
15.50
34.50
2.23
Birkner 1978
1
1.75
2.10
1.20
Butler etal. 1991
10
4.80
8.10
1.69
Butler etal. 1991
3
6.20
9.50
1.53
Butler etal. 1993
SP2
3.40
6.00
1.76
Butler etal. 1993
SP2
3.15
8.20
2.60
Butler etal. 1993
D1
1.20
3.70
3.08
Butler etal. 1993
D1
1.20
3.80
3.17
Butler etal. 1993
U1
2.45
6.40
2.61
Butler etal. 1993
R2
3.90
6.60
1.69
Butler etal. 1993
R2
3.70
6.60
1.78
Butler etal. 1993
ST2
4.50
12.80
2.84
Butler etal. 1993
ST2
4.10
7.60
1.85
Butler etal. 1993
ST2
4.10
16.00
3.90
Butler etal. 1993
R1
4.00
11.00
2.75
Butler etal. 1993
R1
4.00
11.00
2.75
Butler etal. 1993
SB2
3.75
5.70
1.52
Butler etal. 1993
SB2
3.75
8.60
2.29
Butler etal. 1993
SB2
3.65
9.90
2.71
Butler etal. 1993
WSB2
4.75
17.10
3.60
Butler etal. 1993
WSB2
3.60
4.20
1.17
Butler etal. 1993
WSB2
3.60
10.00
2.78
B-108
-------
Fathead minnow (Pimephales promelas)
Study
Site
c
^invert
Cfish
Ratio
Butler et al.
1993
WSB2
3.00
8.10
2.70
Butler et al.
1994
CRC
7.50
20.40
2.72
Butler et al.
1994
CF1
3.60
7.90
2.19
Butler et al.
1994
GUN2
28.00
7.50
0.27
Butler et al.
1994
IW
8.35
10.00
1.20
Butler et al.
1994
TGC
4.90
11.00
2.24
Butler et al.
1994
AD
2.70
9.60
3.56
Butler et al.
1994
LSW1
3.90
73.00
18.72
Butler et al.
1994
OMD
73.00
13.00
0.18
Butler et al.
1994
PSW1
3.70
22.00
5.95
Butler et al.
1994
MKP
32.00
51.00
1.59
Butler et al.
1995
AK
0.78
2.60
3.35
Butler et al.
1995
AK
0.78
2.90
3.74
Butler et al.
1995
AK
0.78
2.80
3.61
Butler et al.
1995
DD
0.86
3.40
3.95
Butler et al.
1995
DD
0.86
3.90
4.53
Butler et al.
1995
DD
0.86
3.60
4.19
Butler et al.
1995
HD1
0.83
3.90
4.73
Butler et al.
1995
HD1
0.83
2.50
3.03
Butler et al.
1995
HD1
0.83
2.60
3.15
Butler et al.
1995
HD2
0.98
1.50
1.53
Butler et al.
1995
HD2
0.98
1.60
1.63
Butler et al.
1995
ME1
3.40
5.60
1.65
Butler et al.
1995
ME2
1.25
4.80
3.84
Butler et al.
1995
ME4
1.55
1.40
0.90
Butler et al.
1995
ME4
1.55
5.90
3.81
Butler et al.
1995
ME3
2.55
4.30
1.69
Butler et al.
1995
ME3
2.55
5.30
2.08
Butler et al.
1995
ME3
2.55
4.40
1.73
Butler et al.
1995
SD
1.40
4.90
3.50
Butler et al.
1995
SD
1.40
3.00
2.14
Butler et al.
1995
SD
1.40
4.00
2.86
Butler et al.
1995
WC
6.75
18.40
2.73
Butler et al.
1995
WC
6.75
22.90
3.39
Butler et al.
1995
WC
6.75
26.40
3.91
Butler et al.
1995
YJ2
1.65
11.00
6.67
Butler et al.
1995
YJ2
1.65
4.00
2.42
Butler et al.
1997
MNP2
4.40
11.00
2.50
Butler et al.
1997
MUD2
3.45
7.70
2.23
Butler et al.
1997
MUD2
3.45
12.00
3.48
Butler et al.
1997
MUD2
3.45
6.50
1.88
Butler et al.
1997
WCP
9.70
10.00
1.03
B-109
-------
Fathead minnow (Pimephales promelas)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1997
WCP
9.70
15.00
1.55
Butler etal. 1997
TR25
1.80
4.00
2.22
Butler etal. 1997
TR25
1.80
5.20
2.89
Butler etal. 1997
TR25
1.80
6.00
3.33
Butler etal. 1997
TRH
1.60
4.20
2.63
Butler etal. 1997
TRH
1.60
4.30
2.69
Butler etal. 1997
TRH
1.60
2.20
1.38
Butler etal. 1997
TRH
1.60
3.00
1.88
Butler etal. 1997
MN5
8.60
7.30
0.85
Butler etal. 1997
MNP1
0.70
1.70
2.43
Butler etal. 1997
MNP1
0.70
1.80
2.57
GEI2013
SWA1
3.64
4.07
1.12
GEI2013
SWA1
3.64
4.68
1.29
GEI 2013
SWA1
3.64
4.76
1.31
GEI 2013
SWA1
3.64
5.45
1.50
GEI 2013
SWA1
3.64
5.71
1.57
GEI 2013
SWA1
3.64
3.62
1.00
GEI 2013
SWA1
3.64
3.72
1.02
GEI 2013
SWA1
3.64
4.43
1.22
GEI 2013
SWA1
3.64
4.52
1.24
GEI 2013
SWA1
3.64
4.66
1.28
GEI 2013
SWA1
2.81
4.48
1.60
GEI 2013
SWA1
2.81
4.53
1.61
GEI 2013
SWA1
2.81
5.00
1.78
GEI 2013
SWA1
2.81
5.24
1.87
GEI 2013
SWA1
2.81
5.76
2.05
GEI 2013
SWA1
2.81
3.89
1.39
GEI 2013
SWA1
2.81
3.98
1.42
GEI 2013
SWA1
2.81
4.04
1.44
GEI 2013
SWA1
2.81
4.33
1.54
GEI 2013
SWA1
2.81
4.81
1.71
GEI 2013
SWB
7.06
7.38
1.05
GEI 2013
SWB
7.06
8.49
1.20
GEI 2013
SWB
7.06
8.72
1.24
GEI 2013
SWB
7.06
9.80
1.39
GEI 2013
SWB
7.06
8.61
1.22
GEI 2013
SWB
7.06
9.02
1.28
GEI 2013
SWB
7.06
9.11
1.29
GEI 2013
SWB
7.06
9.30
1.32
GEI 2013
SWB
7.06
9.53
1.35
GEI 2013
SWB
7.44
10.97
1.48
GEI 2013
SWB
7.44
11.22
1.51
B-110
-------
Fathead minnow (Pimephales promelas)
Study
Site
c
^invert
Cfish
Ratio
GEI2013
SWB
7.44
12.25
1.65
GEI2013
SWB
7.44
12.43
1.67
GEI 2013
SWB
7.44
12.46
1.68
GEI 2013
SWB
7.44
9.36
1.26
GEI 2013
SWB
7.44
9.46
1.27
GEI 2013
SWB
7.44
9.78
1.32
GEI 2013
SWB
7.44
9.87
1.33
GEI 2013
SWB
7.44
10.66
1.43
GEI 2013
SW11
8.41
5.70
0.68
GEI 2013
SW11
8.41
7.05
0.84
GEI 2013
SW11
8.41
5.38
0.64
GEI 2013
SW11
8.41
4.68
0.56
GEI 2013
SW11
8.41
5.29
0.63
GEI 2013
SW11
8.41
5.34
0.63
GEI 2013
SW11
8.41
5.38
0.64
GEI 2013
SW2-1
6.60
12.83
1.95
GEI 2013
SW2-1
6.60
14.80
2.24
GEI 2013
SW2-1
6.60
20.13
3.05
GEI 2013
SW2-1
6.60
26.75
4.06
GEI 2013
SW2-1
6.60
30.48
4.62
GEI 2013
SW2-1
6.60
12.51
1.90
GEI 2013
SW2-1
6.60
16.70
2.53
GEI 2013
SW2-1
6.60
17.21
2.61
GEI 2013
SW2-1
6.60
18.27
2.77
GEI 2013
SW2-1
6.60
20.66
3.13
GEI 2013
SW2-1
9.14
13.31
1.46
GEI 2013
SW2-1
9.14
15.63
1.71
GEI 2013
SW2-1
9.14
15.77
1.73
GEI 2013
SW2-1
9.14
16.79
1.84
GEI 2013
SW2-1
9.14
17.00
1.86
GEI 2013
SW2-1
9.14
18.21
1.99
GEI 2013
SW2-1
9.14
19.39
2.12
GEI 2013
SW2-1
9.14
22.50
2.46
GEI 2013
SW1
7.82
9.11
1.16
GEI 2013
SW1
7.82
9.15
1.17
GEI 2013
SW1
7.82
11.15
1.43
GEI 2013
SW1
7.82
11.23
1.44
GEI 2013
SW1
7.82
13.76
1.76
GEI 2013
SW1
7.82
9.82
1.26
GEI 2013
SW1
7.82
8.45
1.08
GEI 2013
SW1
7.82
8.88
1.14
GEI 2013
SW1
7.82
9.41
1.20
B-lll
-------
Fathead minnow (Pimephales promelas)
Study
Site
c
^invert
Cfish
Ratio
GEI2013
SW1
7.82
11.07
1.42
GEI2013
SW1
6.54
7.01
1.07
GEI 2013
SW1
6.54
7.86
1.20
GEI 2013
SW1
6.54
7.98
1.22
GEI 2013
SW1
6.54
8.23
1.26
GEI 2013
SW1
6.54
8.50
1.30
GEI 2013
SW1
6.54
9.48
1.45
GEI 2013
SW1
6.54
9.95
1.52
GEI 2013
SW1
6.54
10.09
1.54
GEI 2013
SW1
6.54
10.19
1.56
GEI 2013
SW4-1
3.33
5.88
1.77
GEI 2013
SW4-1
3.33
5.89
1.77
GEI 2013
SW4-1
3.33
6.07
1.83
GEI 2013
SW4-1
3.33
6.61
1.99
GEI 2013
SW4-1
3.33
6.87
2.07
GEI 2013
SW4-1
3.33
4.85
1.46
GEI 2013
SW4-1
3.33
5.25
1.58
GEI 2013
SW4-1
3.33
5.39
1.62
GEI 2013
SW4-1
3.33
6.11
1.84
GEI 2013
SW4-1
3.33
6.67
2.01
GEI 2013
SW9
4.45
5.57
1.25
GEI 2013
SW9
4.45
5.93
1.33
GEI 2013
SW9
4.45
6.14
1.38
GEI 2013
SW9
4.45
6.20
1.39
GEI 2013
SW9
4.45
6.56
1.47
GEI 2013
SW9
4.45
7.57
1.70
GEI 2013
SW88
3.96
4.73
1.20
GEI 2013
SW88
3.96
4.96
1.25
GEI 2013
SW88
3.96
5.55
1.40
GEI 2013
SW88
3.96
5.56
1.41
GEI 2013
SW88
3.96
6.32
1.60
GEI 2013
SW88
3.96
5.13
1.30
GEI 2013
SW88
3.96
5.86
1.48
GEI 2013
SW88
3.96
6.07
1.53
GEI 2013
CC1
3.76
3.79
1.01
GEI 2013
CC1
3.76
5.23
1.39
GEI 2013
CC1
3.76
7.36
1.96
GEI 2013
CC1
3.76
8.69
2.31
GEI 2013
CC1
3.76
9.07
2.41
GEI 2013
CC1
4.69
5.92
1.26
GEI 2013
CC1
4.69
7.68
1.64
GEI 2013
CC1
4.69
7.59
1.62
B-112
-------
Fathead minnow (Pimephales promelas)
Study
Site
r
^invert
Cfish
Ratio
GEI2013
CC1
4.69
6.49
1.39
GEI2013
CC1
4.69
7.14
1.52
GEI 2013
CC1
5.86
6.68
1.14
GEI 2013
CC1
5.86
7.73
1.32
GEI 2013
CC1
5.86
7.88
1.35
GEI 2013
CC1
5.86
8.45
1.44
GEI 2013
CC1
5.86
11.69
2.00
GEI 2013
CC1
5.86
9.21
1.57
GEI 2013
CC1
5.86
9.70
1.66
GEI 2013
LG1
3.56
4.81
1.35
GEI 2013
LG1
3.56
4.86
1.37
GEI 2013
LG1
3.56
5.05
1.42
GEI 2013
LG1
3.56
5.47
1.54
GEI 2013
LG1
3.56
5.56
1.56
GEI 2013
LG1
3.56
3.72
1.05
GEI 2013
LG1
3.56
4.09
1.15
GEI 2013
LG1
3.56
3.26
0.92
GEI 2013
LG1
3.56
3.35
0.94
GEI 2013
LG1
3.56
4.20
1.18
GEI 2013
LG1
3.39
3.60
1.06
GEI 2013
LG1
3.39
3.89
1.15
GEI 2013
LG1
3.39
4.27
1.26
GEI 2013
LG1
3.39
4.45
1.31
GEI 2013
LG1
3.39
5.18
1.53
GEI 2013
LG1
3.39
5.51
1.63
Grassoetal. 1995
17
1.91
6.59
3.45
Grassoetal. 1995
17
1.91
6.60
3.46
Grassoetal. 1995
17
1.91
7.30
3.82
Grassoetal. 1995
10
1.85
2.74
1.48
Grassoetal. 1995
10
1.85
2.79
1.51
Grassoetal. 1995
10
1.85
2.90
1.57
Lambing et al. 1994
S46
6.20
5.10
0.82
Lambing et al. 1994
S48
3.05
2.50
0.82
Lambing et al. 1994
Sll
14.50
11.00
0.76
Lambing et al. 1994
Sll
14.50
33.00
2.28
Lambing et al. 1994
S34
14.00
25.00
1.79
Lambing et al. 1994
S39
5.85
7.90
1.35
Lambing et al. 1994
S39
5.85
21.00
3.59
Lemly 1985
Badin Lake
5.70
1.50
0.26
Lemly 1985
Belews Lake
51.15
13.60
0.27
Lemly 1985
High Rock Lake
9.05
1.89
0.21
GEI 2014
DC-4
19.42
27.69
1.43
B-113
-------
Fathead minnow (Pimephales promelas)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
DC-4
19.42
27.88
1.44
GEI2014
DC-4
19.42
23.05
1.19
GEI 2014
DC-4
19.42
30.61
1.58
GEI 2014
DC-4
18.10
19.32
1.07
GEI 2014
DC-4
18.10
14.48
0.80
GEI 2014
DC-4
18.10
25.42
1.40
GEI 2014
FOC-2
2.18
4.13
1.90
GEI 2014
FOC-2
2.18
4.10
1.89
GEI 2014
FOC-2
2.18
5.50
2.53
GEI 2014
FOC-2
2.18
4.85
2.23
GEI 2014
FOC-2
2.18
4.65
2.14
GEI 2014
SC-1
5.85
7.95
1.36
GEI 2014
SC-1
5.85
7.62
1.30
GEI 2014
SC-1
5.85
7.88
1.35
GEI 2014
SC-1
5.85
8.46
1.45
GEI 2014
SC-1
5.85
7.29
1.25
GEI 2014
SC-1
5.85
8.94
1.53
GEI 2014
SC-1
5.85
8.28
1.42
GEI 2014
SC-1
5.85
8.62
1.47
GEI 2014
SC-1
5.85
6.17
1.05
GEI 2014
SC-1
5.85
6.09
1.04
GEI 2014
SC-1
5.85
9.23
1.58
GEI 2014
SC-1
5.85
10.00
1.71
GEI 2014
SC-1
5.85
8.12
1.39
GEI 2014
SC-1
5.85
6.71
1.15
GEI 2014
SC-1
5.85
8.34
1.43
GEI 2014
SC-1
4.94
10.22
2.07
GEI 2014
SC-1
4.94
10.86
2.20
GEI 2014
SC-1
4.94
9.82
1.99
GEI 2014
SC-1
4.94
9.45
1.91
GEI 2014
SC-1
4.94
10.30
2.09
GEI 2014
SC-2
14.33
15.86
1.11
GEI 2014
SC-2
14.33
15.08
1.05
GEI 2014
SC-2
14.33
13.33
0.93
GEI 2014
SC-2
14.33
12.04
0.84
GEI 2014
SC-2
14.33
13.82
0.96
GEI 2014
SC-2
11.44
9.64
0.84
GEI 2014
SC-2
11.44
14.94
1.31
GEI 2014
SC-2
11.44
10.91
0.95
GEI 2014
SC-2
11.44
16.06
1.40
GEI 2014
SC-2
11.44
14.60
1.28
GEI 2014
SC-2
12.75
13.81
1.08
B-114
-------
Fathead minnow (Pimephales promelas)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
SC-2
12.75
14.10
1.11
GEI2014
SC-2
12.75
10.68
0.84
GEI 2014
SC-3
11.41
11.65
1.02
GEI 2014
SC-3
11.41
10.95
0.96
GEI 2014
SC-3
11.41
10.84
0.95
GEI 2014
SC-3
11.41
13.48
1.18
GEI 2014
SC-3
8.58
7.70
0.90
GEI 2014
SC-3
8.58
6.46
0.75
GEI 2014
SC-3
8.58
6.97
0.81
GEI 2014
SC-3
8.58
10.64
1.24
GEI 2014
SC-3
8.58
7.85
0.91
GEI 2014
SC-3
5.75
13.75
2.39
GEI 2014
SC-3
5.75
11.19
1.95
GEI 2014
SC-3
5.75
12.68
2.20
GEI 2014
SC-4
7.39
6.33
0.86
GEI 2014
SC-4
7.39
14.39
1.95
GEI 2014
SC-4
5.18
2.72
0.53
GEI 2014
SC-4
5.18
11.95
2.31
GEI 2014
SC-4
5.18
7.98
1.54
GEI 2014
SC-4
5.18
6.75
1.30
GEI 2014
SC-6
39.87
72.33
1.81
GEI 2014
SC-6
39.87
76.00
1.91
GEI 2014
SC-6
39.87
64.73
1.62
GEI 2014
SC-6
39.87
54.09
1.36
GEI 2014
SC-6
39.87
64.64
1.62
GEI 2014
SC-6
34.35
76.89
2.24
GEI 2014
SC-6
34.35
89.67
2.61
GEI 2014
SC-6
34.35
63.32
1.84
GEI 2014
SC-6
34.35
88.44
2.57
GEI 2014
SC-6
34.35
44.15
1.29
GEI 2014
SC-6
27.54
51.65
1.88
GEI 2014
SC-6
27.54
35.92
1.30
GEI 2014
SC-6
27.54
25.55
0.93
GEI 2014
SC-6
27.54
54.25
1.97
GEI 2014
SC-6
27.54
48.94
1.78
GEI 2014
SC-6
27.54
204.26
7.42
GEI 2014
SC-6
27.54
143.62
5.22
GEI 2014
SC-6
27.54
192.93
7.01
GEI 2014
SC-6
27.54
171.89
6.24
GEI 2014
SC-6
27.54
171.36
6.22
GEI 2014
SC-8
22.62
43.12
1.91
GEI 2014
SC-8
22.62
43.36
1.92
B-115
-------
Fathead minnow (Pimephales promelas)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
SC-8
22.62
55.81
2.47
GEI2014
SC-8
22.62
44.60
1.97
GEI 2014
SC-8
22.62
41.67
1.84
GEI 2014
SC-9
30.36
37.18
1.22
GEI 2014
SC-9
30.36
41.32
1.36
GEI 2014
SC-9
30.36
37.20
1.23
GEI 2014
SC-9
30.36
33.25
1.10
GEI 2014
SC-9
30.36
41.94
1.38
GEI 2014
SC-8
21.77
99.40
4.57
GEI 2014
SC-8
21.77
54.47
2.50
GEI 2014
SC-8
21.77
59.07
2.71
GEI 2014
SC-8
21.77
43.70
2.01
GEI 2014
SC-8
21.77
50.18
2.31
GEI 2014
SC-9
25.06
40.82
1.63
GEI 2014
SC-9
25.06
61.80
2.47
GEI 2014
SC-9
25.06
44.74
1.79
GEI 2014
SC-9
25.06
52.97
2.11
GEI 2014
SC-8
14.15
52.46
3.71
GEI 2014
SC-8
14.15
29.43
2.08
GEI 2014
SC-8
14.15
44.58
3.15
GEI 2014
SC-8
14.15
33.44
2.36
GEI 2014
SC-8
14.15
42.86
3.03
GEI 2014
SC-8
14.15
128.33
9.07
GEI 2014
SC-8
14.15
173.33
12.25
GEI 2014
SC-8
14.15
132.34
9.35
GEI 2014
SC-8
14.15
124.90
8.83
GEI 2014
SC-8
14.15
177.97
12.58
Q
O
i O
o
W frfl
('
Median ratio: 1.57
R
F
df
P
0.35
185.7
344
<0.001
B-116
-------
Flannelmouth sucker (Catostomus latipinnis)
Study
Site
c
^invert
Cfish
Ratio
Butler et al.
1991
10
4.80
2.50
0.52
Butler et al.
1991
7
29.80
22.00
0.74
Butler et al.
1991
4
3.90
1.70
0.44
Butler et al.
1991
9
4.10
1.50
0.37
Butler et al.
1991
9
4.10
6.00
1.46
Butler et al.
1993
PI
1.95
1.50
0.77
Butler et al.
1993
PI
1.50
2.40
1.60
Butler et al.
1993
LP3
1.12
0.92
0.83
Butler et al.
1993
LP3
1.12
1.40
1.26
Butler et al.
1993
LP4
3.20
2.40
0.75
Butler et al.
1993
LP4
3.20
2.60
0.81
Butler et al.
1994
CRC
7.50
12.00
1.60
Butler et al.
1994
LZA1
19.00
17.00
0.89
Butler et al.
1994
BSW1
5.00
9.60
1.92
Butler et al.
1994
C0L1
1.50
1.90
1.27
Butler et al.
1994
COL1
1.50
0.50
0.33
Butler et al.
1994
COL1
1.50
0.60
0.40
Butler et al.
1994
COL1
1.50
0.63
0.42
Butler et al.
1994
COL1
1.50
0.92
0.61
Butler et al.
1994
COL1
1.50
1.00
0.67
Butler et al.
1994
COL1
1.50
1.60
1.07
Butler et al.
1994
COL1
1.50
1.70
1.13
Butler et al.
1994
COL1
1.50
1.80
1.20
Butler et al.
1994
COL1
1.50
1.90
1.27
Butler et al.
1994
RB3
1.60
29.00
18.13
Butler et al.
1994
RBI
21.00
4.60
0.22
Butler et al.
1994
LSW1
3.90
6.70
1.72
Butler et al.
1994
PSW1
3.70
9.40
2.54
Butler et al.
1995
AK
0.78
1.10
1.42
Butler et al.
1995
AK
0.78
0.90
1.16
Butler et al.
1995
AK
0.78
0.82
1.06
Butler et al.
1995
AK
0.78
1.10
1.42
Butler et al.
1995
HD1
0.83
2.90
3.52
Butler et al.
1995
HD2
0.98
0.49
0.50
Butler et al.
1995
HD2
0.98
0.54
0.55
Butler et al.
1995
HD2
0.98
0.62
0.63
Butler et al.
1995
HD2
0.98
0.96
0.98
Butler et al.
1995
ME2
1.25
1.60
1.28
Butler et al.
1995
ME2
1.25
1.40
1.12
Butler et al.
1995
ME2
1.25
2.00
1.60
Butler et al.
1995
ME2
1.25
2.20
1.76
Butler et al.
1995
ME4
1.55
1.50
0.97
B-117
-------
Flannelmouth sucker (Catostomus latipinnis)
Study
Site
c
^invert
Cfish
Ratio
Butler et al.
1995
ME4
1.55
1.30
0.84
Butler et al.
1995
ME4
1.55
1.90
1.23
Butler et al.
1995
ME4
1.55
2.40
1.55
Butler et al.
1995
ME4
1.55
3.00
1.94
Butler et al.
1995
ME3
2.55
1.70
0.67
Butler et al.
1995
ME3
2.55
1.70
0.67
Butler et al.
1995
ME3
2.55
2.10
0.82
Butler et al.
1995
ME3
2.55
2.40
0.94
Butler et al.
1995
ME3
2.55
3.60
1.41
Butler et al.
1995
SJ1
2.50
1.71
0.68
Butler et al.
1995
SJ1
2.50
1.50
0.60
Butler et al.
1995
SJ1
2.50
2.20
0.88
Butler et al.
1995
SJ1
2.50
0.61
0.24
Butler et al.
1995
SJ1
2.50
1.10
0.44
Butler et al.
1995
SJ1
2.50
4.20
1.68
Butler et al.
1995
YJ2
1.65
1.60
0.97
Butler et al.
1995
YJ2
1.65
2.40
1.45
Butler et al.
1995
MN1
2.70
6.50
2.41
Butler et al.
1995
MN1
2.70
1.70
0.63
Butler et al.
1995
MN1
2.70
4.80
1.78
Butler et al.
1995
MP
1.60
1.20
0.75
Butler et al.
1995
MP
1.60
1.40
0.88
Butler et al.
1997
MN3
2.70
2.30
0.85
Butler et al.
1997
MN3
2.70
2.60
0.96
Butler et al.
1997
MUD
2.30
4.10
1.78
Butler et al.
1997
MUD
2.30
2.70
1.17
Butler et al.
1997
NW2
11.40
11.00
0.96
Butler et al.
1997
MN4
2.65
5.10
1.92
Butler et al.
1997
MN4
2.65
9.60
3.62
Butler et al.
1997
MN5
8.60
8.40
0.98
Butler et al.
1997
MNQ
1.80
2.10
1.17
Butler et al.
1997
MNQ
1.80
3.20
1.78
Butler et al.
1997
MNQ
1.80
3.50
1.94
B-118
-------
Flannelmouth sucker (Catostomus latipinnis)
Study Site
c
^invert
Cfish
Ratio
3u ¦ Q
25 -
O
Median ratio:
0.98
15 -
U1 ooo c
"
R2:
F:
df:
P:
0.36
41.6
73
<0.001
•J -- •-
0 5 10 15 20 25 30 35
Gizzard shad (Dorosoma cepedianum)
Study
Site
Mueller etal. 1991
Mueller etal. 1991
Mueller etal. 1991
R2
R1
R1
Cin
Ratio
6.40
8.70
8.70
14.30
7.50
11.00
2.23
0.86
1.26
20
15
Cflsh 10
5
0
Median ratio: 1.26
R
F
df
P
0.74
2.78
1
0.39
2 4 6
^invert.
10
Not used because P > 0.05 and negative
slope.
Goldeye (Hiodon alosoides)
Study Site
r
^invert
Cfish
Ratio
Roddy etal. 1991 18
3.10
2.00
0.65
Roddy etal. 1991 18
3.10
2.10
0.68
Roddy etal. 1991 18
3.10
2.20
0.71
Roddy etal. 1991 18
3.10
2.30
0.74
Roddy etal. 1991 18
3.10
2.40
0.77
Roddy etal. 1991 18
3.10
2.70
0.87
B-119
-------
Goldeye (Hiodon alosoides)
Study
Site
c
^invert
Cfish
Ratio
Roddy et al.
1991
18
3.10
2.90
0.94
Roddy et al.
1991
18
3.10
3.40
1.10
Roddy et al.
1991
18
3.10
3.60
1.16
Roddy et al.
1991
18
3.10
4.70
1.52
5 -|
o
4 -
fish
8
—i—
2
—I
4
Median ratio: 0.82
R2:
0.0
F:
0.0
df:
8
P:
1.0
Not used because no slope and P>0.05.
--invert
Green sunfish (Lepomis cyanettus)
Study
Site
Cjnvert
Cfish
Ratio
Butler et al.
1991
10
4.80
7.90
1.65
Butler et al.
1991
7
29.80
15.20
0.51
Butler et al.
1991
7
29.80
25.10
0.84
Butler et al.
1991
3
6.20
6.40
1.03
Butler et al.
1994
LZA1
19.00
37.00
1.95
Butler et al.
1995
HD1
0.83
1.30
1.58
Butler et al.
1995
HD1
0.83
1.30
1.58
Butler et al.
1995
ME3
2.55
5.00
1.96
Butler et al.
1995
MP
1.60
1.90
1.19
Butler et al.
1997
CHI
7.50
9.50
1.27
Butler et al.
1997
MUD2
3.45
7.60
2.20
Butler et al.
1997
MUD2
3.45
7.00
2.03
Butler et al.
1997
TR25
1.80
4.40
2.44
Butler et al.
1997
TRH
1.60
3.30
2.06
GEI2013
SWA1
2.81
2.96
1.06
GEI2013
SWA1
2.81
3.21
1.14
GEI 2013
SWA1
2.81
3.24
1.16
GEI 2013
SWA1
2.81
3.69
1.32
GEI 2013
SWA1
2.81
3.88
1.38
GEI 2013
SWB
7.44
11.94
1.61
GEI 2013
SW11
8.41
4.54
0.54
B-120
-------
Green sunfish (Lepomis cyanelius)
Study
Site
r
^invert
Cfish
Ratio
GEI2013
SW11
8.41
4.84
0.58
GEI2013
SW11
8.41
5.34
0.63
GEI 2013
SW11
8.41
7.00
0.83
GEI 2013
SW11
8.41
7.13
0.85
GEI 2013
SW9
4.45
4.38
0.98
GEI 2013
SW9
4.45
5.06
1.14
GEI 2013
SW9
4.45
5.53
1.24
GEI 2013
SW9
4.45
5.80
1.30
GEI 2013
SW9
4.45
7.29
1.64
GEI 2013
SW88
3.96
7.14
1.81
GEI 2013
SW88
3.96
7.41
1.87
GEI 2013
LG1
3.39
4.11
1.21
GEI 2013
LG1
3.39
4.33
1.28
GEI 2013
LG1
3.39
5.71
1.68
Roddy etal. 1991
18
3.10
2.80
0.90
Roddy etal. 1991
18
3.10
3.80
1.23
Roddy etal. 1991
18
3.10
4.00
1.29
Roddy etal. 1991
18
3.10
5.20
1.68
Roddy etal. 1991
18
3.10
5.70
1.84
Lemly 1985
Badin Lake
5.70
2.18
0.38
Lemly 1985
Belews Lake
51.15
13.99
0.27
Lemly 1985
High Rock Lake
9.05
2.10
0.23
GEI 2014
C-BCR2
6.81
9.47
1.39
GEI 2014
C-BCR2
6.81
9.29
1.37
GEI 2014
C-BCR2
6.81
8.04
1.18
GEI 2014
C-CC1
4.40
7.23
1.64
GEI 2014
C-CC1
4.40
11.76
2.67
GEI 2014
C-CC2
5.56
4.59
0.83
GEI 2014
C-CC2
5.56
3.04
0.55
GEI 2014
C-CC2
5.56
5.34
0.96
GEI 2014
C-CF1
3.39
3.62
1.07
GEI 2014
C-CF1
3.39
2.95
0.87
GEI 2014
C-CF1
3.39
3.23
0.95
GEI 2014
C-CF1
3.39
5.55
1.64
GEI 2014
C-CLF1
9.30
3.99
0.43
GEI 2014
C-CLF1
9.30
5.23
0.56
GEI 2014
C-CLF1
9.30
4.75
0.51
GEI 2014
C-CLF1
9.30
4.87
0.52
GEI 2014
C-CLF1
9.30
3.58
0.39
GEI 2014
C-CLF2
6.85
5.76
0.84
GEI 2014
C-CLF2
6.85
5.89
0.86
GEI 2014
C-CLF2
6.85
4.78
0.70
B-121
-------
Green sunfish (Lepomis cyanelius)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
C-CLF2
6.85
5.11
0.75
GEI2014
C-CLF2
6.85
4.10
0.60
GEI 2014
C-LFWOC1
9.32
10.10
1.08
GEI 2014
C-TF1
20.00
4.15
0.21
GEI 2014
C-TF1
20.00
3.47
0.17
GEI 2014
C-TF1
20.00
4.14
0.21
GEI 2014
C-TF1
20.00
4.11
0.21
GEI 2014
C-TF1
20.00
3.41
0.17
GEI 2014
C-WOC1
6.65
12.05
1.81
GEI 2014
C-WOC1
6.65
9.60
1.44
GEI 2014
C-WOC1
6.65
8.66
1.30
GEI 2014
C-WOC1
6.65
5.81
0.87
GEI 2014
C-WOC1
6.65
7.54
1.13
GEI 2014
H-BB1
16.29
9.55
0.59
GEI 2014
H-BB1
16.29
18.27
1.12
GEI 2014
H-BB1
16.29
7.08
0.43
GEI 2014
H-BHC1
5.08
3.69
0.73
GEI 2014
H-BHC1
5.08
2.48
0.49
GEI 2014
H-BHC1
5.08
3.29
0.65
GEI 2014
H-BHC1
5.08
3.49
0.69
GEI 2014
H-BHC1
5.08
3.70
0.73
GEI 2014
H-JSB1
4.03
4.83
1.20
GEI 2014
H-JSB1
4.03
2.57
0.64
GEI 2014
H-JSB1
4.03
3.73
0.93
GEI 2014
H-LF1
9.09
3.12
0.34
GEI 2014
H-LF1
9.09
5.96
0.66
GEI 2014
H-LF1
9.09
4.30
0.47
GEI 2014
H-LF1
9.09
4.02
0.44
GEI 2014
H-LF1
9.09
5.29
0.58
GEI 2014
H-MR2
2.14
9.57
4.47
GEI 2014
H-MR2
2.14
5.55
2.59
GEI 2014
H-MR2
2.14
5.80
2.71
GEI 2014
H-MR2
2.14
5.55
2.59
GEI 2014
H-MR2
2.14
6.88
3.22
GEI 2014
H-MR3
3.86
8.09
2.10
GEI 2014
H-MR3
3.86
16.98
4.40
GEI 2014
H-MR3
3.86
6.80
1.76
GEI 2014
H-MR3
3.86
8.52
2.21
GEI 2014
H-MR3
3.86
6.62
1.72
GEI 2014
H-MR4
9.26
9.01
0.97
GEI 2014
H-MR4
9.26
8.78
0.95
GEI 2014
H-MR4
9.26
18.33
1.98
B-122
-------
Green sunfish (Lepomis cyanelius)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
H-MR4
9.26
9.84
1.06
GEI2014
H-MR4
9.26
5.94
0.64
GEI 2014
H-MR5
3.58
5.50
1.54
GEI 2014
H-MR5
3.58
3.52
0.98
GEI 2014
H-MR5
3.58
2.41
0.67
GEI 2014
H-MR5
3.58
3.09
0.86
GEI 2014
H-MR5
3.58
1.94
0.54
GEI 2014
H-MR6
2.49
36.20
14.54
GEI 2014
H-MR6
2.49
2.58
1.04
GEI 2014
H-MR6
2.49
1.94
0.78
GEI 2014
H-MR6
2.49
1.74
0.70
GEI 2014
H-MR6
2.49
2.69
1.08
GEI 2014
H-SB1
10.62
11.90
1.12
GEI 2014
H-SB1
10.62
13.39
1.26
GEI 2014
H-SB1
10.62
7.64
0.72
GEI 2014
H-SB1
10.62
13.45
1.27
GEI 2014
H-SF1
21.05
13.59
0.65
GEI 2014
H-SF1
21.05
14.22
0.68
GEI 2014
H-SF1
21.05
15.27
0.73
GEI 2014
H-SF1
21.05
14.58
0.69
GEI 2014
H-SF1
21.05
11.25
0.53
GEI 2014
H-SF2
13.95
17.74
1.27
GEI 2014
H-SF2
13.95
12.86
0.92
GEI 2014
H-SF2
13.95
12.76
0.91
GEI 2014
H-SF2
13.95
13.41
0.96
GEI 2014
H-SF2
13.95
28.23
2.02
GEI 2014
H-UB1
3.02
4.43
1.47
GEI 2014
H-UB1
3.02
4.91
1.63
GEI 2014
H-UB1
3.02
3.73
1.23
GEI 2014
H-UB1
3.02
8.00
2.65
GEI 2014
H-UB1
3.02
8.36
2.77
GEI 2014
SC-1-25
4.00
12.78
3.19
GEI 2014
SC-2
14.33
9.31
0.65
GEI 2014
SC-2
14.33
7.59
0.53
GEI 2014
SC-2
11.44
10.23
0.89
GEI 2014
SC-2-27
23.76
30.00
1.26
GEI 2014
SC-3
5.75
8.66
1.51
GEI 2014
SC-3
5.75
11.72
2.04
GEI 2014
SC-3
5.75
9.59
1.67
GEI 2014
SC-4
5.18
19.86
3.83
GEI 2014
SC-6
39.87
49.55
1.24
GEI 2014
SC-6
39.87
49.56
1.24
B-123
-------
Green sunfish (Lepomis cyanellus)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
SC-6
39.87
33.71
0.85
GEI2014
SC-6
39.87
28.73
0.72
GEI 2014
SC-6
39.87
40.64
1.02
GEI 2014
SC-6
34.35
41.51
1.21
GEI 2014
SC-6
34.35
48.02
1.40
GEI 2014
SC-6
34.35
68.66
2.00
GEI 2014
SC-6
34.35
41.27
1.20
GEI 2014
SC-6
34.35
48.76
1.42
GEI 2014
SC-6
27.54
28.17
1.02
GEI 2014
SC-6
27.54
106.88
3.88
GEI 2014
SC-6
27.54
114.55
4.16
GEI 2014
SC-6
27.54
100.41
3.65
GEI 2014
SC-6
27.54
153.64
5.58
GEI 2014
SC-6
27.54
145.62
5.29
GEI 2014
S-SC1
11.01
7.47
0.68
ISO -
1*1
U'l
8
Median ratio:
1.12
1'lfl
8
R2:
0.37
as* -,n
F:
93.17
on
df:
160
!lJ O
„ rf
P:
<0.001
j§3>
:o 30
Iowa darter (Etheostoma exile)
Study
Site
c
^invert
Cfish
Ratio
1978
7
3.75
2.10
0.56
1978
20
11.20
36.30
3.24
1978
22
11.30
23.00
2.04
1978
23
15.50
41.90
2.70
B-124
-------
Iowa darter (Etheostoma exile)
Median ratio
P: 0.055
Not used because P > 0.05
invert.
Largemouth bass (Micropterus salmoides)
Study
Site
Cjnvert
Cfish
Ratio
Butler etal. 1995
MP
Cienega de Santa
1.60
1.40
0.88
Garcia-Hernandez et al. 2000
Clara Wetland
3.00
5.10
1.70
GEI2013
SWA1
2.81
3.17
1.13
GEI2013
SW11
8.41
5.02
0.60
GEI 2013
SW11
8.41
5.77
0.69
GEI 2013
SW11
8.41
5.19
0.62
GEI 2013
SW11
8.41
6.26
0.74
GEI 2013
SW11
8.41
6.48
0.77
GEI 2013
SW11
8.41
7.22
0.86
GEI 2013
SW4-1
3.33
5.53
1.66
GEI 2013
SW4-1
3.33
5.65
1.70
GEI 2013
SW4-1
3.33
5.72
1.72
GEI 2013
SW4-1
3.33
5.80
1.74
GEI 2013
SW4-1
3.33
6.34
1.91
GEI 2013
SW4-1
3.33
7.14
2.15
GEI 2013
SW9
4.45
5.78
1.30
GEI 2013
SW9
4.45
5.79
1.30
GEI 2013
SW9
4.45
6.19
1.39
GEI 2013
SW9
4.45
6.87
1.54
GEI 2013
SW9
4.45
7.27
1.63
GEI 2013
SW9
4.45
7.36
1.65
GEI 2013
SW88
3.96
4.87
1.23
GEI 2013
SW88
3.96
5.73
1.45
GEI 2013
SW88
3.96
5.77
1.46
GEI 2013
SW88
3.96
5.93
1.50
GEI 2013
SW88
3.96
6.62
1.67
GEI 2013
SW88
3.96
6.84
1.73
B-125
-------
Largemouth bass (Micropterus salmoides)
Study
Site
r
^invert
Cfish
Ratio
GEI2013
LG1
3.39
4.29
1.27
Saikietal. 1993
ET6
0.85
1.00
1.18
Saikietal. 1993
ET6
0.85
1.40
1.66
Saikietal. 1993
GT5
4.90
6.80
1.39
Saikietal. 1993
GT5
4.90
6.90
1.41
Saikietal. 1993
GT4
4.05
4.70
1.16
Saikietal. 1993
GT4
4.05
4.00
0.99
Saikietal. 1993
SJR2
3.30
2.20
0.67
Saikietal. 1993
SJR2
3.30
2.40
0.73
Saikietal. 1993
SJR3
1.50
1.80
1.20
Saikietal. 1993
SJR3
1.50
1.70
1.13
Saikietal. 1993
SJR1
0.95
0.80
0.85
Saikietal. 1993
SJR1
0.95
1.80
1.90
Saikietal. 1993
ET7
0.86
0.86
1.00
Saikietal. 1993
ET7
0.86
1.00
1.16
Rinellaand Schuler 1992
S. Malheur Lake
1.20
0.92
0.77
Crutchfield 2000
transect 3
11.95
12.52
1.05
Crutchfield 2000
transect 3
11.40
16.67
1.46
Crutchfield 2000
transect 3
9.25
6.83
0.74
Crutchfield 2000
transect 3
9.25
6.99
0.76
Crutchfield 2000
transect 3
8.60
6.59
0.77
Crutchfield 2000
transect 3
8.60
5.69
0.66
Crutchfield 2000
transect 4
20.90
15.53
0.74
Crutchfield 2000
transect 4
20.90
19.68
0.94
Crutchfield 2000
transect 4
15.70
18.95
1.21
Crutchfield 2000
transect 4
15.70
9.43
0.60
Crutchfield 2000
transect 4
16.45
6.83
0.42
Crutchfield 2000
transect 4
18.25
9.43
0.52
GEI 2014
ARB
11.21
20.41
1.82
GEI 2014
ARB
11.21
32.75
2.92
GEI 2014
ARB
11.21
32.73
2.92
GEI 2014
ARB
11.21
29.23
2.61
GEI 2014
ARB
11.21
21.26
1.90
GEI 2014
ARE
20.40
25.35
1.24
GEI 2014
ARE
20.40
20.80
1.02
GEI 2014
ARE
20.40
22.67
1.11
GEI 2014
ARE
20.40
21.57
1.06
GEI 2014
ARE
20.40
16.05
0.79
GEI 2014
ARM
8.51
13.62
1.60
GEI 2014
ARM
8.51
10.13
1.19
GEI 2014
ARM
8.51
12.00
1.41
GEI 2014
ARM
8.51
11.40
1.34
B-126
-------
Largemouth bass (Micropterus salmoides)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
ARM
8.51
8.71
1.02
GEI2014
ARM
7.68
12.52
1.63
GEI 2014
ARM
7.68
13.59
1.77
GEI 2014
ARM
7.68
17.99
2.34
GEI 2014
ARM
7.68
13.49
1.76
GEI 2014
ARM
7.68
15.98
2.08
GEI 2014
ARN
8.06
11.16
1.39
GEI 2014
ARN
8.06
12.89
1.60
GEI 2014
ARN
8.06
16.74
2.08
GEI 2014
ARN
8.06
10.12
1.26
GEI 2014
ARN
8.06
20.08
2.49
GEI 2014
ARN
7.49
17.47
2.33
GEI 2014
ARN
7.49
13.48
1.80
GEI 2014
ARN
7.49
19.44
2.60
GEI 2014
ARN
7.49
21.87
2.92
GEI 2014
ARN
7.49
21.91
2.92
GEI 2014
ARN
7.44
30.73
4.13
GEI 2014
ARN
7.44
40.71
5.47
GEI 2014
ARN
7.44
38.75
5.21
GEI 2014
ARN
7.44
38.24
5.14
GEI 2014
SC-5
15.13
38.13
2.52
GEI 2014
SC-5
15.13
42.86
2.83
GEI 2014
SC-9
30.36
41.87
1.38
GEI 2014
SC-9
25.06
37.84
1.51
1
o
o
o
o
.,-6"
8 „
"o §>
,,0'"
0)
o
o o
o
ID 15 20
Median ratio: 1.39
R
F
df
P
0.40
61.45
91
<0.001
B-127
-------
Longnose dace (Rhinichthys cataractae)
Study
Site
c
^invert
Cfish
Ratio
Lambing et al. 1994
S33
2.40
5.30
2.21
Mueller etal. 1991
Al
2.70
2.10
0.78
GEI 2013
LG1
3.37
5.05
1.50
GEI 2013
LG1
3.37
5.57
1.65
GEI 2013
LG1
3.37
6.57
1.95
GEI 2013
LG1
3.37
6.75
2.00
GEI 2013
LG1
3.37
10.08
2.99
GEI 2013
LG1
3.39
10.69
3.15
GEI 2013
LG1
3.39
12.77
3.77
GEI 2013
LG1
3.56
8.95
2.52
GEI 2013
LG1
3.56
9.63
2.71
GEI 2013
LG1
3.56
11.41
3.21
GEI 2013
LG1
3.56
11.94
3.36
GEI 2013
LG1
Left Fork White Oak
3.56
12.04
3.39
GEI 2014
Creek, C-LFWOC1
Left Fork White Oak
9.32
8.32
0.89
GEI 2014
Creek, C-LFWOC1
Left Fork White Oak
9.32
9.47
1.02
GEI 2014
Creek, C-LFWOC1
Left Fork White Oak
9.32
7.94
0.85
GEI 2014
Creek, C-LFWOC1
Left Fork White Oak
9.32
6.67
0.72
GEI 2014
Creek, C-LFWOC1
9.32
7.19
0.77
Mueller etal. 1991
T1
5.40
16.90
3.13
Hamilton and Buhl 2005
CC
6.70
13.40
2.00
Hamilton and Buhl 2005
BGS
10.80
10.90
1.01
18
16
14
12
10
8
6
4
2
0
o 8
o
o
o
o
-e-
Median ratio: 2.00
R2:
0.01
F:
0.19
df:
20
P:
0.83
Not used because P > 0.05
10
12
B-128
-------
Longnose sucker (Catostomus catostomus)
Study
Site
c
^invert
Cfish
Ratio
Minnow 2007
FL17
3.03
1.40
0.46
Butler etal. 1994
NFK2
3.10
2.10
0.68
Butler etal. 1994
NFK2
3.10
2.50
0.81
Butler etal. 1994
NFK2
3.10
2.70
0.87
Butler etal. 1994
NFK2
3.10
2.80
0.90
Butler etal. 1994
NFK2
3.10
2.90
0.94
Butler etal. 1994
NFK2
3.10
3.00
0.97
Butler etal. 1994
NFK2
3.10
3.20
1.03
Butler etal. 1994
NFK2
3.10
3.30
1.06
Butler etal. 1994
NFK2
3.10
3.40
1.10
Butler etal. 1994
NFK2
3.10
4.00
1.29
Mueller etal. 1991
T1
5.40
3.60
0.67
Minnow 2007
FL17
21.22
7.90
0.37
Median ratio: 0.90
Mottled sculpin (Cottus bairdii)
Study
Site
c
^invert
Cfish
Ratio
Hamilton and Buhl 2004
use
0.50
5.30
10.60
Butler etal. 1993
LP2
1.00
2.20
2.20
Butler etal. 1993
LP2
1.00
3.10
3.10
Butler etal. 1993
LP3
1.12
3.90
3.50
Butler etal. 1993
LP3
1.12
4.20
3.77
Butler etal. 1993
LP3
1.12
4.90
4.39
Butler etal. 1993
PI
1.50
5.10
3.40
Butler etal. 1993
PI
1.50
6.40
4.27
Butler etal. 1993
PI
1.50
6.70
4.47
Hamilton and Buhl 2004
ShpC
1.90
4.10
2.16
Butler etal. 1993
PI
1.95
7.30
3.74
Butler etal. 1994
NFK3
2.00
5.80
2.90
B-129
-------
Mottled sculpin (Cottus bairdii)
Study
Site
c
^invert
Cflsh
Ratio
Butler etal. 1997
MN2
2.20
2.60
1.18
Butler etal. 1997
CHK
2.40
3.10
1.29
Butler etal. 1997
CHK
2.40
4.40
1.83
Lambing et al. 1994
S33
2.40
3.70
1.54
Butler etal. 1991
12
2.80
4.20
1.50
Butler etal. 1997
MN1
2.90
3.20
1.10
Butler etal. 1997
MN1
2.90
3.40
1.17
Butler etal. 1994
NFK2
3.10
6.40
2.06
Butler etal. 1991
4
3.90
2.60
0.67
Butler etal. 1991
4
3.90
4.40
1.13
Butler etal. 1991
10
4.80
5.00
1.04
Hamilton and Buhl 2005
UAC
5.00
6.20
1.24
Butler etal. 1991
3
6.20
6.50
1.05
Hamilton and Buhl 2004
ACM
6.70
8.30
1.24
Hamilton and Buhl 2005
CC
6.70
8.20
1.22
Butler etal. 1993
F2
7.50
9.90
1.32
Hamilton and Buhl 2004
LBR
7.70
5.20
0.68
Hamilton and Buhl 2005
DC
8.70
12.00
1.38
Hamilton and Buhl 2005
BGS
10.80
12.30
1.14
Hamilton and Buhl 2004
DVC
12.80
8.80
0.69
Butler etal. 1994
HCC1
21.00
5.60
0.27
Median ratio: 1.38
Mountain whitefish (Prosopium williamsoni)
Study Site Cinvert Cflsh Ratio
Low and Mullins 1990 7 1.60 1.40 0.88
McDonald and Strosher 1998 ER745 2.74 4.17 1.52
Minnow 2007 EL12 4.01 6.60 1.65
McDonald and Strosher 1998 ER747 4.29 4.93 1.15
B-130
-------
Mountain whitefish (Prosopium williamsoni)
Study
Site
r
^invert
Cfish
Ratio
Minnow 2007
MI3
6.21
9.12
1.47
Minnow 2007
MI2
6.69
10.16
1.52
Minnow 2007
ELI
7.08
9.12
1.29
Minnow 2007
F023
10.00
10.20
1.02
14 i
12 -
10 -
o .
o$*
/ o
8 "
Median ratio:
1.38
Tish g .
4 -
R2:
0.83
2 -
O
F:
30.27
A
df:
6
u
0 5
10 15
P:
<0.001
c
v invert.
Northern pike (Esox lucius)
Study
Site
Cjnvert
Cfish
Ratio
Butler et al.
1995
TT
1.07
2.96
2.78
Butler et al.
1995
TT
1.07
3.24
3.04
Butler et al.
1995
TT
1.07
1.65
1.55
Butler et al.
1995
TT
1.07
1.18
1.11
Butler et al.
1995
TT
1.07
1.90
1.78
Butler et al.
1995
TT
1.07
1.80
1.69
Butler et al.
1995
PU
0.61
0.93
1.52
Butler et al.
1995
PU
0.61
1.40
2.30
Muscatello et al. 2008
David Lake
1.39
0.78
0.56
Muscatello et al. 2008
Delta Lake
9.38
17.02
1.81
Muscatello et al. 2008
Unknown Lake
15.71
28.28
1.80
Muscatello and Janz 2009
Indigo Lake
0.36
0.75
2.08
Muscatello and Janz 2009
Vulture Lake
1.62
1.26
0.78
B-131
-------
Northern pike (Esox lucius)
25 -
Median ratio:
1.78
20 -
R2:
0.99
15 '¦
F:
982.9
10
df:
11
P:
<0.001
10
Northern plains killfish (Fun(lulus kansae)
Study
Site
c
^invert
Cfish
Ratio
Birkner 1978
3
3.10
7.70
2.48
Birkner 1978
11
5.65
5.00
0.88
Birkner 1978
23
15.50
23.10
1.49
Birkner 1978
27
34.60
31.90
0.92
Birkner 1978
30
45.05
57.40
1.27
70
60
50
40
-fish 30
20
10
0
—I 1 1 1 1
10 20 30 40 50
Median ratio: 1.27
R2:
0.93
F:
37.8
df:
3
P:
0.008
-'invert.
B-132
-------
Rainbow trout (Oncorhynchus my kiss)
Study
Site
r
^invert
Cfish
Ratio
Butler et al.
991
4
3.90
3.50
0.90
Butler et al.
993
F2
4.80
7.60
1.58
Butler et al.
993
F2
3.90
7.60
1.95
Butler et al.
993
LP2
1.00
0.78
0.78
Butler et al.
993
LP2
1.00
1.40
1.40
Butler et al.
993
LP3
1.12
1.90
1.70
Butler et al.
994
GUN2
28.00
5.40
0.19
Butler et al.
994
HCC1
21.00
16.48
0.78
Butler et al.
994
NFK3
2.00
4.70
2.35
Butler et al.
994
NFK2
3.10
21.98
7.09
Butler et al.
994
NFK2
3.10
3.60
1.16
Butler et al.
995
MP
1.60
1.88
1.18
Butler et al.
995
MP
1.60
2.30
1.44
Butler et al.
995
MP
1.60
2.50
1.56
Butler et al.
995
MP
1.60
2.10
1.31
Butler et al.
997
CHK
2.40
1.41
0.59
Butler et al.
997
CHK
2.40
2.20
0.92
Butler et al.
997
CHK
2.40
2.50
1.04
Butler et al.
997
CHK
2.40
2.80
1.17
Butler et al.
997
CHK
2.40
2.90
1.21
Butler et al.
997
MN3
2.70
2.28
0.84
Butler et al.
997
MN3
2.70
2.60
0.96
Butler et al.
997
MN3
2.70
4.90
1.81
Butler et al.
997
MN2
2.20
2.10
0.95
Butler et al.
997
MN2
2.20
2.80
1.27
Butler et al.
997
MN1
2.90
2.50
0.86
Butler et al.
997
MN1
2.90
2.60
0.90
Butler et al.
997
MN1
2.90
3.20
1.10
Butler et al.
997
WBR
5.05
5.10
1.01
Low and Mu
lins 1990
5
5.60
2.60
0.46
Casey 2005
Deerlick Creek
4.45
1.29
0.29
Casey 2005
Deerlick Creek
4.45
4.15
0.93
Casey 2005
Luscar Creek
9.95
6.88
0.69
Casey 2005
Luscar Creek
9.95
17.04
1.71
B-133
-------
Rainbow trout (Oncorhynchus mykiss)
o
0
Median ratio:
1.07
R2:
0.19
F:
7.52
J3'"
o
df:
32
P:
0.002
10 !5 20
Invert*
Red shiner (Cyprinella lutrensis)
Study
Site
r
^invert
Cfish
Ratio
Butler etal. 1991
3
6.20
7.70
1.24
Butler etal. 1994
IW
8.35
83.00
9.94
Butler etal. 1994
AD
2.70
7.30
2.70
Butler etal. 1994
LW
3.00
19.00
6.33
Butler etal. 1994
LSW1
3.90
14.00
3.59
Butler etal. 1995
ME4
1.55
5.10
3.29
Butler etal. 1995
ME3
2.55
4.60
1.80
Butler etal. 1995
ME3
2.55
4.20
1.65
Butler etal. 1995
SJ1
2.50
3.50
1.40
Butler etal. 1995
YJ2
1.65
4.50
2.73
Butler etal. 1997
MN4
2.65
4.20
1.58
Butler etal. 1997
MN5
8.60
4.40
0.51
May et al. 2008
KR
17.20
7.03
0.41
May et al. 2008
NSCL
10.70
7.36
0.69
May et al. 2008
NSCU
10.50
7.24
0.69
May et al. 2008
NSK
8.81
5.81
0.66
May et al. 2008
NSP
24.00
8.62
0.36
May et al. 2008
SSAL
11.50
9.00
0.78
May et al. 2008
SSAU
8.35
11.20
1.34
May et al. 2008
sso
10.00
7.16
0.72
May et al. 2008
ssw
7.60
10.00
1.32
Mueller etal. 1991
A3
6.00
8.10
1.35
Mueller etal. 1991
A2
8.50
7.90
0.93
Lemly 1985
Badin Lake
5.70
2.10
0.37
Lemly 1985
Belews Lake
51.15
18.25
0.36
Lemly 1985
High Rock Lake
9.05
2.18
0.24
GEI2014
ARE
20.40
49.84
2.44
B-134
-------
Red shiner (Cyprinelia lutrensis)
Study
Site
r
^invert
Cfish
Ratio
GEI2014
ARE
20.40
80.50
3.95
GEI2014
ARE
20.40
20.57
1.01
GEI 2014
ARE
20.40
33.37
1.64
GEI 2014
ARE
20.40
26.50
1.30
GEI 2014
ARN
7.44
27.50
3.70
GEI 2014
ARN
7.44
23.58
3.17
GEI 2014
ARN
7.44
21.74
2.92
GEI 2014
FC-4
18.65
21.20
1.14
GEI 2014
FC-4
18.65
32.68
1.75
GEI 2014
FC-4
18.65
25.73
1.38
GEI 2014
GC-1
9.33
10.78
1.16
GEI 2014
GC-1
9.33
9.97
1.07
GEI 2014
SC-2
12.75
10.44
0.82
GEI 2014
SC-2
12.75
10.87
0.85
GEI 2014
SC-3
5.75
12.05
2.10
GEI 2014
SC-3
5.75
12.17
2.12
GEI 2014
SC-3
5.75
9.93
1.73
GEI 2014
SC-3
5.75
9.93
1.73
GEI 2014
SC-4
7.39
12.26
1.66
GEI 2014
SC-4
7.39
11.68
1.58
GEI 2014
SC-4
7.39
14.15
1.92
GEI 2014
SC-4
5.18
9.58
1.85
GEI 2014
SC-4
5.18
8.43
1.63
GEI 2014
SC-4
5.18
10.83
2.09
GEI 2014
SC-5
15.13
17.96
1.19
GEI 2014
SC-5
15.13
34.71
2.29
GEI 2014
SC-5
15.13
34.05
2.25
GEI 2014
SC-5
15.13
37.28
2.46
GEI 2014
SC-5
15.13
32.18
2.13
GEI 2014
SC-6
39.87
53.60
1.34
GEI 2014
SC-6
39.87
37.00
0.93
GEI 2014
SC-6
39.87
35.11
0.88
GEI 2014
SC-6
39.87
51.39
1.29
GEI 2014
SC-6
39.87
42.31
1.06
GEI 2014
SC-8
22.62
29.20
1.29
GEI 2014
SC-9
25.06
22.55
0.90
GEI 2014
SC-9
25.06
18.02
0.72
GEI 2014
SC-9
25.06
25.94
1.04
GEI 2014
SC-9
25.06
18.68
0.75
GEI 2014
SC-9
25.06
14.28
0.57
GEI 2014
SC-9
25.06
31.67
1.26
GEI 2014
SC-9
25.06
20.43
0.82
B-135
-------
Red shiner (Cyprinetta lutrensis)
Study
Site
<8
cin
^flsh
Ratio
GEI2014
SC-9
25.06
22.27
0.89
GEI2014
SC-9
25.06
27.05
1.08
GEI 2014
SC-9
25.06
25.28
1.01
9(1
ft. °
-o
o
Median ratio:
1.31
SO -
«i ¦ „
30 ¦ 8
§
o
If"
8
--S
R2:
F:
df:
P:
0.28
26.57
70
<0.001
Redside shiner (Ri ch ardson ius bait eat us)
Study
Site
c
^invert
Cfish
Ratio
Hamilton and Buhl 2004
ACM
6.70
6.00
0.90
Hamilton and Buhl 2004
LBR
7.70
2.70
0.35
Hamilton and Buhl 2005
BGS
10.80
13.20
1.22
GEI 2014
Bond Creek, BC-3
3.02
3.58
1.19
GEI 2014
Bond Creek, BC-3
3.02
3.44
1.14
GEI 2014
Bond Creek, BC-3
3.02
3.44
1.14
GEI 2014
Bond Creek, BC-3
3.02
4.64
1.54
GEI 2014
Bond Creek, BC-3
3.02
3.26
1.08
GEI 2014
Bond Creek, BC-3
5.87
3.18
0.54
GEI 2014
Bond Creek, BC-3
5.87
3.37
0.57
GEI 2014
Bond Creek, BC-3
5.87
2.79
0.47
GEI 2014
Bond Creek, BC-3
3.02
3.58
1.19
B-136
-------
Redside shiner (Ri ch ardson ius bait eat us)
14
12
10
o
o
10
12
Median ratio:
1.08
R2:
0.47
F:
7.84
df:
9
P:
0.011
( .
Roundtail chub (Gila robusta)
Study
Site
Cjnvert
Cfish
Ratio
Butler et al.
1994
COL1
1.50
2.20
1.47
Butler et al.
1994
COL1
1.50
2.50
1.67
Butler et al.
1994
COL1
1.50
2.70
1.80
Butler et al.
1994
COL1
1.50
3.30
2.20
Butler et al.
1994
COL1
1.50
3.70
2.47
Butler et al.
1994
COL1
1.50
4.10
2.73
Butler et al.
1994
COL1
1.50
5.10
3.40
Butler et al.
1994
COL1
1.50
5.30
3.53
Butler et al.
1994
COL1
1.50
26.00
17.33
Butler et al.
1994
RB3
1.60
5.40
3.38
Butler et al.
1995
MP
1.60
4.20
2.63
Butler et al.
1997
MUD
2.30
4.60
2.00
Butler et al.
1994
AD
2.70
7.10
2.63
Butler et al.
1994
LW
3.00
4.50
1.50
Butler et al.
1994
NFK2
3.10
6.10
1.97
Butler et al.
1994
PSW1
3.70
7.70
2.08
Butler et al.
1994
LSW1
3.90
5.80
1.49
Butler et al.
1991
10
4.80
1.90
0.40
Butler et al.
1994
TGC
4.90
10.00
2.04
Butler et al.
1994
BSW1
5.00
8.10
1.62
Butler et al.
1993
F2
7.50
7.30
0.97
Butler et al.
1994
CRC
7.50
19.00
2.53
Butler et al.
1994
IW
8.35
8.50
1.02
Butler et al.
1997
NW2
11.40
6.90
0.61
Butler et al.
1994
RBI
21.00
5.90
0.28
Butler et al.
1994
GUN2
28.00
6.80
0.24
B-137
-------
Roundtail chub (Gila robusta)
30
25
20
Cfisi, 15
10
5
0
8
mF~
0 o
10
c.
Median ratio: 1.98
R
F
df
P
0.01
0.18
24
0.834
Not used because P > 0.05
20
30
invert.
Sand shiner (Notropis stramineus)
Study
Site
r
^invert
Cfish
Ratio
GEI2013
SW1
6.54
8.43
1.29
GEI2013
SW1
6.54
9.02
1.38
GEI 2013
SW1
6.54
9.66
1.48
GEI 2013
SW1
6.54
11.21
1.71
GEI 2013
SW1
6.54
11.85
1.81
GEI 2013
SW1
6.54
11.94
1.83
GEI 2013
SW1
6.54
13.50
2.06
GEI 2013
SW1
6.54
14.05
2.15
GEI 2013
SW1
6.54
14.14
2.16
GEI 2013
SW2-1
6.60
18.70
2.84
GEI 2013
SW2-1
6.60
19.33
2.93
GEI 2013
SW2-1
6.60
19.77
3.00
GEI 2013
SW2-1
6.60
20.39
3.09
GEI 2013
SW2-1
6.60
23.70
3.59
GEI 2013
SWB
7.06
8.27
1.17
GEI 2013
SWB
7.06
9.01
1.28
GEI 2013
SWB
7.06
9.81
1.39
GEI 2013
SWB
7.06
10.22
1.45
GEI 2013
SW1
7.82
11.33
1.45
GEI 2013
SW1
7.82
12.05
1.54
GEI 2013
SW1
7.82
12.22
1.56
GEI 2013
SW1
7.82
12.55
1.60
GEI 2013
SW1
7.82
12.65
1.62
GEI 2013
SW1
7.82
12.68
1.62
GEI 2013
SW1
7.82
14.13
1.81
GEI 2013
SW1
7.82
14.43
1.85
GEI 2013
SW1
7.82
15.87
2.03
B-138
-------
Sand shiner (Natr apis stramineus)
Study
Site
c
^invert
Cfish
Ratio
GEI2013
SW1
7.82
16.63
2.13
GEI2013
SW2-1
9.14
17.84
1.95
GEI 2013
SW2-1
9.14
18.21
1.99
GEI 2013
SW2-1
9.14
18.98
2.08
GEI 2013
SW2-1
9.14
20.12
2.20
GEI 2013
SW2-1
9.14
20.73
2.27
GEI 2014
Arkansas River, ARE
20.40
21.50
1.05
GEI 2014
Arkansas River, ARE
20.40
23.20
1.14
GEI 2014
Arkansas River, ARE
20.40
22.64
1.11
GEI 2014
Arkansas River, ARE
20.40
25.24
1.24
GEI 2014
Arkansas River, ARE
20.40
29.70
1.46
GEI 2014
Arkansas River, ARM
8.51
10.67
1.25
GEI 2014
Arkansas River, ARN
8.06
9.69
1.20
GEI 2014
Arkansas River, ARN
8.06
9.27
1.15
GEI 2014
Arkansas River, ARN
8.06
9.96
1.24
GEI 2014
Arkansas River, ARN
8.06
9.29
1.15
GEI 2014
Arkansas River, ARN
8.06
8.86
1.10
GEI 2014
Arkansas River, ARN
7.49
13.60
1.82
GEI 2014
Arkansas River, ARN
7.49
18.34
2.45
GEI 2014
Arkansas River, ARN
7.49
16.46
2.20
GEI 2014
Arkansas River, ARN
7.49
19.64
2.62
GEI 2014
Fountain Creek, FC-4
14.59
13.95
0.96
GEI 2014
Fountain Creek, FC-4
14.59
9.34
0.64
GEI 2014
Fountain Creek, FC-4
14.59
14.06
0.96
GEI 2014
Fountain Creek, FC-4
14.59
28.26
1.94
GEI 2014
Fountain Creek, FC-4
14.59
10.53
0.72
GEI 2014
Fountain Creek, FC-4
17.15
10.28
0.60
GEI 2014
Fountain Creek, FC-4
17.15
23.76
1.39
GEI 2014
Fountain Creek, FC-4
17.15
14.77
0.86
GEI 2014
Fountain Creek, FC-4
17.15
23.13
1.35
GEI 2014
Fountain Creek, FC-4
17.15
25.62
1.49
GEI 2014
Fountain Creek, FCP
6.13
17.62
2.88
GEI 2014
Fountain Creek, FCP
6.13
7.32
1.19
GEI 2014
Fountain Creek, FCP
6.13
7.14
1.17
GEI 2014
Fountain Creek, FCP
6.13
6.05
0.99
GEI 2014
Fountain Creek, FCP
6.13
7.11
1.16
GEI 2014
Fountain Creek, FCP
6.35
15.93
2.51
GEI 2014
St. Charles River, SC-4
6.29
11.92
1.90
GEI 2014
St. Charles River, SC-4
6.29
15.14
2.41
GEI 2014
St. Charles River, SC-4
6.29
8.94
1.42
GEI 2014
St. Charles River, SC-4
6.29
10.33
1.64
GEI 2014
St. Charles River, SC-4
6.29
11.58
1.84
B-139
-------
Sand shiner (Notropis stramineus)
Study Site
c
^invert
Cfish
Ratio
35
30
25
20
15
10
5
0
10 15
(¦
vin veils
20
25
Median ratio: 1.56
R
F
df
P
0.32
32.15
67
<0.001
Sculpin (Cottoidea)
Study
Site
Cjnvert
Cfish
Ratio
Mason et al. 2000
BK
1.43
1.16
0.81
Mason et al. 2000
BK
1.43
2.35
1.64
Mason et al. 2000
BK
1.43
2.64
1.84
Formation 2012
SFTC-1
1.63
9.31
5.71
Formation 2012
SFTC-1
2.42
5.68
2.35
Formation 2012
SFTC-1
2.49
5.87
2.36
Formation 2012
CC-75
3.11
5.03
1.62
Formation 2012
CC-75
3.11
5.58
1.79
Formation 2012
CC-350
3.16
6.47
2.05
Formation 2012
CC-350
3.16
7.12
2.26
Formation 2012
SFTC-1
3.21
3.75
1.17
Formation 2012
CC-75
3.97
3.77
0.95
Formation 2012
CC-75
4.16
7.08
1.70
Formation 2012
CC-75
4.16
7.19
1.73
Formation 2012
CC-350
4.20
5.28
1.26
Formation 2012
CC-150
4.46
5.04
1.13
Formation 2012
CC-150
4.46
6.01
1.35
Formation 2012
CC-150
4.70
5.14
1.09
Formation 2012
CC-3A
5.45
11.65
2.14
Formation 2012
CC-3A
5.45
14.45
2.65
Formation 2012
CC-3A
5.48
11.47
2.09
Formation 2012
CC-150
7.03
10.73
1.53
Formation 2012
DC-600
7.83
7.96
1.02
Formation 2012
DC-600
7.83
8.62
1.10
B-140
-------
Sculpin (Cottoidea)
Study
Site
c
^invert
Cfish
Ratio
Formation 2012
DC-600
8.53
7.87
0.92
Formation 2012
DC-600
8.53
8.50
1.00
Formation 2012
DC-600
8.65
7.63
0.88
Formation 2012
LSV-4
9.54
18.28
1.92
Formation 2012
LSV-4
9.54
20.01
2.10
Formation 2012
HS-3
11.40
18.57
1.63
Formation 2012
HS-3
11.40
21.85
1.92
Formation 2012
CC-350
11.45
9.53
0.83
Formation 2012
CC-350
11.45
10.03
0.88
Formation 2012
CC-1A
12.24
8.34
0.68
Formation 2012
CC-1A
12.24
9.94
0.81
Formation 2012
CC-1A
12.24
17.47
1.43
Formation 2012
CC-1A
12.57
7.78
0.62
Formation 2012
HS-3
13.41
26.63
1.99
Formation 2012
CC-1A
13.55
12.63
0.93
Formation 2012
CC-150
14.32
7.35
0.51
Formation 2012
CC-3A
14.50
20.20
1.39
Formation 2012
HS
15.70
23.23
1.48
Formation 2012
HS
15.70
23.25
1.48
Formation 2012
HS
18.70
10.95
0.59
Formation 2012
LSV-2C
22.62
11.38
0.50
Formation 2012
LSV-2C
22.62
17.47
0.77
Formation 2012
HS-3
24.70
23.93
0.97
Formation 2012
LSV-2C
26.31
18.85
0.72
Formation 2012
HS-3
26.55
23.68
0.89
Formation 2012
LSV-2C
26.95
20.32
0.75
Formation 2012
HS
27.80
35.93
1.29
Formation 2012
HS
27.80
41.30
1.49
Formation 2012
LSV-2C
30.00
25.95
0.87
Median ratio: 1.29
B-141
-------
Shorthead redhorse (Moxostoma macrolepidotum)
Study
Site
Cjnvert
Cfish
Ratio
Roddy et al.
1991
18
3.10
2.80
0.90
Roddy et al.
1991
18
3.10
2.90
0.94
Roddy et al.
1991
18
3.10
2.90
0.94
Roddy et al.
1991
18
3.10
3.10
1.00
Roddy et al.
1991
18
3.10
3.30
1.06
Roddy et al.
1991
18
3.10
3.40
1.10
Roddy et al.
1991
18
3.10
3.50
1.13
Roddy et al.
1991
18
3.10
3.60
1.16
Roddy et al.
1991
18
3.10
3.70
1.19
Roddy et al.
1991
18
3.10
3.80
1.23
Roddy et al.
1991
18
3.10
3.80
1.23
Median ratio: 1.10
R2:
0.00
F:
0.00
df:
9
P:
1.0
0 1 2 3 4 Not used because P > 0.05
(
invert.
Smallmouth bass (Micropterus dolomieu)
Study
Site
Cjnvert
Cfish
Ratio
Butler etal. 1995
SU
1.85
1.55
0.84
Butler etal. 1995
su
1.85
1.22
0.66
Butler etal. 1995
SU
1.85
0.98
0.53
Butler etal. 1995
su
1.85
1.14
0.62
Butler etal. 1995
SU
1.85
1.50
0.81
Butler etal. 1995
su
1.85
1.50
0.81
Butler etal. 1995
MP
1.60
1.90
1.19
Butler etal. 1997
MNP3
6.15
12.00
1.95
Mueller etal. 1991
R1
8.70
2.90
0.33
Mueller etal. 1991
R1
8.70
4.10
0.47
GEI2014
ARE
20.40
24.61
1.21
GEI2014
ARE
20.40
22.97
1.13
GEI 2014
ARE
20.40
13.28
0.65
B-142
-------
Smallmouth bass (Micropterus dolomieu)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
ARE
20.40
19.06
0.93
GEI2014
ARE
20.40
19.11
0.94
GEI 2014
ARM
7.10
8.25
1.16
GEI 2014
ARM
7.10
8.04
1.13
GEI 2014
ARM
7.10
7.72
1.09
GEI 2014
ARM
7.10
6.21
0.87
GEI 2014
ARM
7.10
6.51
0.92
GEI 2014
C-SC1
11.30
8.94
0.79
GEI 2014
C-SC1
11.30
7.68
0.68
Median ratio: 0.86
R2: 0.84
F: 107.1
df: 20
P: <0.001
Speckled dace (Rhinichthys osculus)
Study
Site
Cjnvert
Cfish
Ratio
Butler et al.
1991
10
4.80
4.80
1.00
Butler et al.
1991
9
4.10
5.70
1.39
Butler et al.
1991
3
6.20
6.50
1.05
Butler et al.
1993
SP2
2.75
12.00
4.36
Butler et al.
1993
B2
1.35
5.80
4.30
Butler et al.
1993
B1
1.25
4.40
3.52
Butler et al.
1993
B1
1.25
4.40
3.52
Butler et al.
1993
D1
1.20
3.50
2.92
Butler et al.
1993
D1
1.20
3.70
3.08
Butler et al.
1993
D1
1.20
3.40
2.83
Butler et al.
1993
D2
1.45
4.90
3.38
Butler et al.
1993
D2
1.45
6.80
4.69
Butler et al.
1993
D2
1.45
6.50
4.48
Butler et al.
1993
F2
3.90
8.90
2.28
Butler et al.
1993
PI
1.95
5.50
2.82
Butler et al.
1993
SP1
2.95
7.30
2.47
Cn„ 15
5 \ ^ „
8
0
o
o
%
0 5 10 15 20 25
B-143
-------
Speckled dace (Rhinichthys osculus)
Study
Site
r
^invert
Cfish
Ratio
Butler et al.
1993
SP1
2.95
8.90
3.02
Butler et al.
1993
SP1
2.95
7.00
2.37
Butler et al.
1993
U1
2.45
3.60
1.47
Butler et al.
1993
U1
2.45
6.90
2.82
Butler et al.
1993
U1
2.45
7.30
2.98
Butler et al.
1993
U1
2.45
9.20
3.76
Butler et al.
1993
U1
2.45
9.40
3.84
Butler et al.
1993
U1
2.45
9.80
4.00
Butler et al.
1993
LP3
1.12
6.00
5.38
Butler et al.
1993
LP4
3.20
8.70
2.72
Butler et al.
1993
R2
4.30
17.10
3.98
Butler et al.
1993
R2
3.90
6.00
1.54
Butler et al.
1993
ST2
4.50
15.70
3.49
Butler et al.
1993
ST2
4.10
8.50
2.07
Butler et al.
1993
ST2
4.10
10.70
2.61
Butler et al.
1993
ST2
3.35
9.30
2.78
Butler et al.
1993
R1
4.00
8.50
2.13
Butler et al.
1993
ST1
2.25
6.80
3.02
Butler et al.
1993
SB2
3.60
12.10
3.36
Butler et al.
1993
SB2
3.75
7.80
2.08
Butler et al.
1993
SB2
3.75
10.80
2.88
Butler et al.
1993
SB1
2.15
10.00
4.65
Butler et al.
1993
SB1
2.15
9.50
4.42
Butler et al.
1993
SB1
2.15
7.80
3.63
Butler et al.
1993
WSB2
4.75
15.60
3.28
Butler et al.
1993
WSB2
3.60
11.70
3.25
Butler et al.
1993
WSB2
3.00
6.20
2.07
Butler et al.
1993
WSB2
3.00
7.60
2.53
Butler et al.
1994
CRC
7.50
13.00
1.73
Butler et al.
1994
CF1
3.60
6.10
1.69
Butler et al.
1994
GUN2
28.00
8.90
0.32
Butler et al.
1994
IW
8.35
10.00
1.20
Butler et al.
1994
LZA1
19.00
28.00
1.47
Butler et al.
1994
NFK3
2.00
7.10
3.55
Butler et al.
1994
NFK2
3.10
6.90
2.23
Butler et al.
1994
NFK2
3.10
4.80
1.55
Butler et al.
1994
NFK2
3.10
5.40
1.74
Butler et al.
1994
NFK2
3.10
5.70
1.84
Butler et al.
1994
NFK2
3.10
6.10
1.97
Butler et al.
1994
NFK2
3.10
6.20
2.00
Butler et al.
1994
NFK2
3.10
6.30
2.03
Butler et al.
1994
NFK2
3.10
6.40
2.06
B-144
-------
Speckled dace (Rhinichthys osculus)
Study
Site
r
^invert
Cfish
Ratio
Butler et al.
1994
NFK2
3.10
6.70
2.16
Butler et al.
1994
NFK2
3.10
7.40
2.39
Butler et al.
1994
NFK2
3.10
8.70
2.81
Butler et al.
1994
TGC
4.90
12.00
2.45
Butler et al.
1994
BSW1
5.00
15.00
3.00
Butler et al.
1994
C0L1
1.50
2.30
1.53
Butler et al.
1994
COL1
1.50
5.00
3.33
Butler et al.
1994
COL1
1.50
7.30
4.87
Butler et al.
1994
COL1
1.50
7.40
4.93
Butler et al.
1994
COL1
1.50
8.40
5.60
Butler et al.
1994
COL1
1.50
8.60
5.73
Butler et al.
1994
COL1
1.50
9.30
6.20
Butler et al.
1994
COL1
1.50
9.60
6.40
Butler et al.
1994
COL1
1.50
11.00
7.33
Butler et al.
1994
RB3
1.60
93.00
58.13
Butler et al.
1994
SMF
4.80
7.80
1.63
Butler et al.
1994
LW
3.00
62.00
20.67
Butler et al.
1994
LSW1
3.90
83.00
21.28
Butler et al.
1994
PSW1
3.70
13.00
3.51
Butler et al.
1995
AK
0.78
4.30
5.55
Butler et al.
1995
AK
0.78
3.10
4.00
Butler et al.
1995
AK
0.78
4.00
5.16
Butler et al.
1995
DD
0.86
5.60
6.51
Butler et al.
1995
DD
0.86
4.40
5.12
Butler et al.
1995
DD
0.86
6.00
6.98
Butler et al.
1995
HD1
0.83
2.80
3.39
Butler et al.
1995
HD1
0.83
3.20
3.88
Butler et al.
1995
HD1
0.83
5.30
6.42
Butler et al.
1995
ME1
3.40
6.40
1.88
Butler et al.
1995
ME2
1.25
6.10
4.88
Butler et al.
1995
ME3
2.55
2.80
1.10
Butler et al.
1995
ME3
2.55
7.00
2.75
Butler et al.
1995
ME3
2.55
5.50
2.16
Butler et al.
1995
NW
5.10
8.70
1.71
Butler et al.
1995
SJ1
2.50
4.30
1.72
Butler et al.
1995
SJ1
2.50
5.10
2.04
Butler et al.
1995
SJ1
2.50
2.90
1.16
Butler et al.
1995
YJ2
1.65
6.50
3.94
Butler et al.
1995
YJ2
1.65
6.30
3.82
Butler et al.
1995
YJ2
1.65
7.10
4.30
Butler et al.
1995
MN1
2.70
5.50
2.04
Butler et al.
1997
CHK
2.40
5.20
2.17
B-145
-------
Speckled dace (Rhinichthys osculus)
Study
Site
c
^invert
Cflsh
Ratio
Butler et al.
1997
CHK
2.40
3.80
1.58
Butler et al.
1997
MN3
2.70
6.00
2.22
Butler et al.
1997
MN3
2.70
4.30
1.59
Butler et al.
1997
MN2
2.20
2.70
1.23
Butler et al.
1997
MN2
2.20
3.60
1.64
Butler et al.
1997
MN1
2.90
3.70
1.28
Butler et al.
1997
MUD
2.30
7.20
3.13
Butler et al.
1997
MUD
2.30
6.10
2.65
Butler et al.
1997
NW2
11.40
11.00
0.96
Butler et al.
1997
WBR
5.05
9.70
1.92
Butler et al.
1997
WBR
5.05
5.50
1.09
Butler et al.
1997
MN4
2.65
7.90
2.98
Butler et al.
1997
MN5
8.60
14.00
1.63
Butler et al.
1997
MNQ
1.80
5.90
3.28
Hamilton and Buhl 2004
DVC
12.80
7.50
0.59
Hamilton and Buhl 2004
use
0.50
6.90
13.80
Hamilton and Buhl 2004
ACM
6.70
8.50
1.27
Hamilton and Buhl 2004
LBR
7.70
5.60
0.73
Hamilton and Buhl 2005
LiB
5.40
5.80
1.07
Hamilton and Buhl 2005
SLC
9.70
15.20
1.57
70 •
Median ratio:
2.76
(W °
SfJ
R2:
0.01
40 -
F:
1.76
30 •
O
df:
118
_
oPQ —
— —
P:
0.177
Not used because P > 0.05
Sucker (Catostomidae)
Study Site Cinvert Cflsh Ratio
Butler etal. 1995 HD2 0.98 0.68 0.69
Butler etal. 1995 HD2 0.98 0.76 0.78
Butler etal. 1993 D1 1.20 2.30 1.92
Rinella and Schuler 1992 Malheur Lake 1.20 1.60 1.33
B-146
-------
Sucker (Catostomidae)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1993
B2
1.35
1.80
1.33
Butler etal. 1995
YJ2
1.65
2.20
1.33
Butler etal. 1993
PI
1.95
1.50
0.77
Butler etal. 1993
U1
2.45
2.30
0.94
Butler etal. 1993
U1
2.45
3.60
1.47
Butler etal. 1991
12
2.80
2.10
0.75
Butler etal. 1994
NFK2
3.10
35.00
11.29
Butler etal. 1993
SB2
3.60
5.10
1.42
Butler etal. 1993
R2
3.90
5.00
1.28
Butler etal. 1993
R2
4.30
2.20
0.51
Butler etal. 1993
ST2
4.50
10.00
2.22
Butler etal. 1993
WSB2
4.75
11.80
2.48
Butler etal. 1993
F2
7.50
4.20
0.56
Wish
O so
Median ratio: 1.33
R
F
df
P
0.07
1.10
15
0.360
Not used because P > 0.05
-'Invert.
Sunfish (Centrarchidae)
Study
Site
Cjnvert
Cfish
Ratio
Welsh and Maughan 1994
outfall drain
1.15
2.30
2.00
Welsh and Maughan 1994
Pretty Water
1.16
1.80
1.56
Welsh and Maughan 1994
Hart Mine Marsh
1.20
2.40
2.00
Welsh and Maughan 1994
outfall drain
1.30
2.10
1.62
Welsh and Maughan 1994
outfall drain
1.30
2.80
2.15
Welsh and Maughan 1994
Pretty Water
1.50
1.60
1.07
Welsh and Maughan 1994
Old Channel
1.50
2.00
1.33
Welsh and Maughan 1994
Pretty Water
1.50
2.30
1.53
Welsh and Maughan 1994
Cibola Lake
1.85
5.90
3.19
Welsh and Maughan 1994
Cibola Lake
1.90
5.30
2.79
Welsh and Maughan 1994
Cibola Lake
1.90
7.60
4.00
Welsh and Maughan 1994
Oxbow Lake
3.60
11.00
3.06
B-147
-------
Sunfish (Centrarchidae)
9.14
8.10
Median ratio:
2.00
R2:
0.38
F:
6.66
df:
11
P:
0.013
GEI2013
-fish
12 1
10 -
8
6
4
2
0
SW2-1
2 4 6
Cjnvert.
10
0.89
Tui chub (Gila bicolor)
Study
Site
Cjnvert
Cfish
Ratio
Sorenson & Schwarzbach 1991
5
0.49
1.20
2.45
Sorenson & Schwarzbach 1991
4
0.76
1.00
1.32
Rinellaand Schuler 1992
Harney Lake
2.05
3.10
1.51
4 1
3 -
3 -
Median ratio:
1.51
2 -
C
*--fisb 2 -
R2:
0.94
1 -
F:
15.9
1 -
df:
1
P:
0.175
U "1
1 1
2 2 3
Not used because P >
0.05
c
^ invert.
Walleye (Sander vitreus)
Study
Site
Cjnvert
Cfish
Ratio
Butler et al.
1995
XT
1.07
1.86
1.75
Butler et al.
1995
XT
1.07
1.62
1.52
Butler et al.
1995
XT
1.07
1.70
1.60
Butler et al.
1995
XT
1.07
1.70
1.60
Butler et al.
1995
XT
1.07
2.00
1.88
B-148
-------
Walleye (Sander vitreus)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1995
XT
1.07
1.60
1.50
Butler etal. 1995
PU
0.61
1.72
2.82
Butler etal. 1995
PU
0.61
1.05
1.73
Butler etal. 1995
PU
0.61
0.81
1.33
Butler etal. 1995
PU
0.61
1.00
1.64
Butler etal. 1995
PU
0.61
0.89
1.46
Mueller etal. 1991
R1
8.70
2.40
0.28
Peterson et al. 1991
7
3.83
4.27
1.11
Peterson et al. 1991
7
3.83
4.79
1.25
Peterson et al. 1991
7
3.83
6.76
1.77
Peterson et al. 1991
7
3.83
8.35
2.18
9 •
8
6 -
O
o
Median ratio: 1.60
5 •
CfKi, ^
o
o
R2: 0.28
3 •
F: 5.46
o
df: 14
2 erf
1 8
P: 0.018
0
0 2
4
8 10
Western niosquitofish (Gambusia affinis)
Study
Site
Cjnvert
Cfish
Ratio
GEI2013
SWA1
3.64
2.91
0.80
GEI2013
SWA1
2.81
3.01
1.07
GEI 2013
SWA1
2.81
3.49
1.24
GEI 2013
SWA1
2.81
3.66
1.30
GEI 2013
SWA1
2.81
3.89
1.39
GEI 2013
SWA1
2.81
4.27
1.52
Lemly 1985
Badin Lake
5.70
3.35
0.59
Lemly 1985
Belews Lake
51.15
27.20
0.53
Lemly 1985
High Rock Lake
9.05
3.54
0.39
Saiki and Lowe 1987
Kesterson Pond 11
60.65
130.00
2.14
Saiki and Lowe 1987
Kesterson Pond 11
60.65
104.00
1.71
Saiki and Lowe 1987
Kesterson Pond 2
177.00
224.00
1.27
Saiki and Lowe 1987
Kesterson Pond 2
177.00
247.00
1.40
Saiki and Lowe 1987
Kesterson Pond 8
102.50
164.00
1.60
B-149
-------
Western niosquitofish (Gambusia affinis)
Study
Site
r
^invert
Cflsh
Ratio
Saiki and Lowe 1987
Kesterson Pond 8
102.50
223.00
2.18
Saiki and Lowe 1987
San Luis Drain
190.00
149.00
0.78
Saiki and Lowe 1987
San Luis Drain
190.00
332.00
1.75
Saiki and Lowe 1987
Volta Pond 26
1.42
1.28
0.90
Saiki and Lowe 1987
Volta Pond 26
1.42
1.24
0.87
Saiki and Lowe 1987
Volta Wasteway
2.23
1.35
0.61
Saiki and Lowe 1987
Volta Wasteway
2.23
1.36
0.61
Saiki et al.
1993
ET6
0.85
1.00
1.18
Saiki et al.
1993
ET6
0.85
1.30
1.54
Saiki et al.
1993
GT5
4.90
16.00
3.27
Saiki et al.
1993
GT5
4.90
11.00
2.24
Saiki et al.
1993
GT4
4.05
4.50
1.11
Saiki et al.
1993
GT4
4.05
4.90
1.21
Saiki et al.
1993
SJR2
3.30
4.50
1.36
Saiki et al.
1993
SJR2
3.30
2.20
0.67
Saiki et al.
1993
SJR3
1.50
1.70
1.13
Saiki et al.
1993
SJR3
1.50
2.00
1.33
Saiki et al.
1993
SJR1
0.95
0.95
1.01
Saiki et al.
1993
SJR1
0.95
1.30
1.38
Saiki et al.
1993
ET7
0.86
0.90
1.05
Saiki et al.
1993
ET7
0.86
1.00
1.16
3%
3
25D
2ms
Jb
o
O
O
50 100
c,
o
Median ratio: 1.21
R
F
df
P
0.89
263.3
33
<0.001
White sucker (Catostomus commersonii)
Study Site Cinvert Cflsh Ratio
Butler etal. 1993 LP3 1.12 2.50 2.24
Butler etal. 1993 B1 1.25 2.60 2.08
Butler etal. 1993 D2 1.45 1.90 1.31
Butler etal. 1993 D2 1.45 2.50 1.72
B-150
-------
White sucker (Catostomus commersonii)
Study
Site
c
^invert
Cfish
Ratio
Butler etal. 1993
PI
1.50
1.70
1.13
Butler etal. 1993
PI
1.50
1.80
1.20
Butler etal. 1995
MP
1.60
1.40
0.88
Butler etal. 1995
SU
1.85
1.20
0.65
GEI2014
Arkansas River
ARB
11.21
14.90
1.33
GEI2014
Arkansas River
ARB
11.21
20.39
1.82
GEI 2014
Arkansas River
ARB
11.21
13.82
1.23
GEI 2014
Arkansas River
ARB
11.21
8.36
0.75
GEI 2014
Arkansas River
ARB
11.21
10.88
0.97
GEI 2014
Arkansas River
ARB
11.21
21.55
1.92
GEI 2014
Arkansas River
ARB
11.21
18.70
1.67
GEI 2014
Arkansas River
ARB
11.21
24.53
2.19
GEI 2014
Arkansas River
ARB
11.21
15.02
1.34
GEI 2014
Arkansas River
ARB
11.21
28.29
2.52
GEI 2014
Arkansas River
ARE
20.4
18.21
0.89
GEI 2014
Arkansas River
ARE
20.4
19.54
0.96
GEI 2014
Arkansas River
ARE
20.4
15.27
0.75
GEI 2014
Arkansas River
ARE
20.4
11.37
0.56
GEI 2014
Arkansas River
ARE
20.4
17.86
0.88
GEI 2014
Arkansas River
ARE
20.4
10.62
0.52
GEI 2014
Arkansas River
ARE
20.4
17.51
0.86
GEI 2014
Arkansas River
ARE
20.4
24.66
1.21
GEI 2014
Arkansas River
ARE
20.4
18.92
0.93
GEI 2014
Arkansas River
ARE
20.4
21.70
1.06
GEI 2014
Arkansas River
ARM
8.51
10.13
1.19
GEI 2014
Arkansas River
ARM
8.51
9.24
1.09
GEI 2014
Arkansas River
ARM
8.51
8.30
0.97
GEI 2014
Arkansas River
ARM
8.51
10.09
1.19
GEI 2014
Arkansas River
ARM
7.68
16.18
2.11
GEI 2014
Arkansas River
ARM
7.68
13.21
1.72
GEI 2014
Arkansas River
ARM
7.68
11.96
1.56
GEI 2014
Arkansas River
ARM
7.68
8.58
1.12
GEI 2014
Arkansas River
ARM
7.68
9.73
1.27
GEI 2014
Arkansas River
ARM
7.1
8.19
1.15
GEI 2014
Arkansas River
ARM
7.1
7.96
1.12
GEI 2014
Arkansas River
ARN
7.49
9.15
1.22
GEI 2014
Arkansas River
ARN
7.49
8.61
1.15
GEI 2014
Arkansas River
ARN
7.49
7.06
0.94
GEI 2014
Arkansas River
ARN
7.49
11.57
1.54
GEI 2014
Arkansas River
ARN
7.49
11.56
1.54
GEI 2014
Arkansas River
ARN
7.44
21.20
2.85
GEI 2014
Arkansas River
ARN
7.44
23.28
3.13
B-151
-------
White sucker (Catostomus commersonii)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
Arkansas River, ARN
7.44
20.85
2.80
GEI2014
Arkansas River, ARN
7.44
25.91
3.48
GEI 2014
Bond Creek, BC-2
2.96
3.06
1.03
GEI 2014
Bond Creek, BC-2
2.96
3.54
1.19
GEI 2014
Bond Creek, BC-2
2.96
3.04
1.03
GEI 2014
Bond Creek, BC-3
3.02
2.76
0.91
GEI 2014
Bond Creek, BC-3
3.02
2.85
0.94
GEI 2014
Bond Creek, BC-3
3.02
2.47
0.82
GEI 2014
Bond Creek, BC-3
3.02
2.03
0.67
GEI 2014
Bond Creek, BC-3
3.02
2.23
0.74
GEI 2014
Cow Camp Creek, CC-2
5.65
4.46
0.79
GEI 2014
Cow Camp Creek, CC-2
5.65
4.45
0.79
GEI 2014
Cow Camp Creek, CC-2
5.65
6.19
1.09
GEI 2014
Cow Camp Creek, CC-2
5.65
4.71
0.83
GEI 2014
Cow Camp Creek, CC-2
5.65
5.38
0.95
GEI 2014
Seng Creek, C-SC1
11.302
20.32
1.80
GEI 2014
Dry Creek, DC-4
19.42
26.07
1.34
GEI 2014
Dry Creek, DC-4
19.42
22.55
1.16
GEI 2014
Dry Creek, DC-4
19.42
14.29
0.74
GEI 2014
Dry Creek, DC-4
19.42
14.25
0.73
GEI 2014
Dry Creek, DC-4
19.42
14.67
0.76
GEI 2014
Dry Creek, DC-4
18.1
29.83
1.65
GEI 2014
Dry Creek, DC-4
18.1
30.65
1.69
GEI 2014
Dry Creek, DC-4
18.1
20.87
1.15
GEI 2014
Dry Creek, DC-4
18.1
12.06
0.67
GEI 2014
Fountain Creek, FC-4
18.65
24.54
1.32
GEI 2014
Fountain Creek, FCP
6.13
5.33
0.87
GEI 2014
Fountain Creek, FCP
6.13
5.88
0.96
GEI 2014
Fountain Creek, FCP
6.13
5.88
0.96
GEI 2014
Fountain Creek, FCP
6.13
5.75
0.94
GEI 2014
Fountain Creek, FCP
6.13
4.37
0.71
GEI 2014
Fountain Creek, FCP
5.38
8.50
1.58
GEI 2014
Fountain Creek, FCP
5.38
5.94
1.10
GEI 2014
Fountain Creek, FCP
5.38
5.97
1.11
GEI 2014
Fountain Creek, FCP
5.38
5.76
1.07
GEI 2014
Fountain Creek, FCP
5.38
5.61
1.04
GEI 2014
Fountain Creek, FCP
6.35
15.82
2.49
GEI 2014
Fountain Creek, FCP
6.35
5.68
0.90
GEI 2014
Fountain Creek, FCP
6.35
10.17
1.60
GEI 2014
Fountain Creek, FCP
6.35
12.34
1.94
GEI 2014
Fountain Creek, FCP
6.35
10.64
1.68
GEI 2014
Foidel Creek, FOC-2
2.175
1.74
0.80
B-152
-------
White sucker (Catostomus commersonii)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
Foidel Creek, FOC-2
2.175
1.25
0.57
GEI2014
Foidel Creek, FOC-2
2.175
1.76
0.81
GEI 2014
Foidel Creek, FOC-2
2.175
2.11
0.97
GEI 2014
Foidel Creek, FOC-2
2.175
1.64
0.76
GEI 2014
Foidel Creek, FOC-2
2.175
2.11
0.97
GEI 2014
Foidel Creek, FOC-2
2.175
2.29
1.05
GEI 2014
Grassy Creek, GC-2
4.195
4.45
1.06
GEI 2014
Grassy Creek, GC-2
4.195
4.42
1.05
GEI 2014
Grassy Creek, GC-2
4.195
2.51
0.60
GEI 2014
Grassy Creek, GC-3
4.535
2.78
0.61
GEI 2014
Grassy Creek, GC-3
4.535
2.76
0.61
GEI 2014
Grassy Creek, GC-3
4.535
2.84
0.63
GEI 2014
Grassy Creek, GC-3
4.535
4.37
0.96
GEI 2014
Grassy Creek, GC-3
4.535
2.89
0.64
GEI 2014
Grassy Creek, GC-3
4.545
4.29
0.94
GEI 2014
Grassy Creek, GC-3
4.545
3.16
0.69
GEI 2014
Grassy Creek, GC-3
4.545
2.76
0.61
GEI 2014
Grassy Creek, GC-3
4.34
4.12
0.95
GEI 2014
Grassy Creek, GC-3
4.35
3.96
0.91
GEI 2014
Grassy Creek, GC-4
5.1
0.93
0.18
GEI 2014
Grassy Creek, GC-4
5.1
1.40
0.27
GEI 2014
Grassy Creek, GC-4
5.1
4.12
0.81
GEI 2014
Grassy Creek, GC-4
5.76
7.04
1.22
GEI 2014
Grassy Creek, GC-4
5.76
7.42
1.29
GEI 2014
Grassy Creek, GC-4
5.76
4.22
0.73
GEI 2014
Grassy Creek, GC-4
5.76
4.75
0.82
GEI 2014
Grassy Creek, GC-4 US
13.16
6.32
0.48
GEI 2014
Grassy Creek, GC-4 US
13.16
4.74
0.36
GEI 2014
Grassy Creek, GC-4 US
13.16
4.98
0.38
GEI 2014
Grassy Creek, GC-4 US
13.16
4.75
0.36
GEI 2014
Grassy Creek, GC-4 US
13.16
4.88
0.37
GEI 2014
Middle Creek, MC-1
3.21
2.03
0.63
GEI 2014
Middle Creek, MC-1
3.21
2.18
0.68
GEI 2014
Middle Creek, MC-1
3.21
1.79
0.56
GEI 2014
Middle Creek, MC-1
3.21
2.28
0.71
GEI 2014
Middle Creek, MC-1
3.21
2.54
0.79
GEI 2014
Middle Creek, MC-2
4.19
2.58
0.62
GEI 2014
Middle Creek, MC-2
4.19
1.90
0.45
GEI 2014
Middle Creek, MC-2
4.19
1.86
0.44
GEI 2014
Middle Creek, MC-2
4.19
1.90
0.45
GEI 2014
Middle Creek, MC-2
4.19
2.10
0.50
GEI 2014
St. Charles River, SC-3
5.75
7.74
1.35
B-153
-------
White sucker (Catostomus commersonii)
Study
Site
c
^invert
Cfish
Ratio
GEI2014
St. Charles River, SC-3
5.75
12.34
2.15
St. Charles River at US
GEI2014
Hwy 50, SC-5
15.13
46.76
3.09
St. Charles River at US
GEI 2014
Hwy 50, SC-5
15.13
38.23
2.53
St. Charles River at US
GEI 2014
Hwy 50, SC-5
15.13
46.59
3.08
St. Charles River at US
GEI 2014
Hwy 50, SC-5
15.13
60.66
4.01
St. Charles River at US
GEI 2014
Hwy 50, SC-5
15.13
43.70
2.89
GEI 2014
St. Charles River, SC-9
25.06
35.97
1.44
GEI 2014
St. Charles River, SC-9
25.06
38.53
1.54
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
7.62
1.76
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
8.20
1.89
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
6.10
1.41
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
22.44
5.18
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
4.29
0.99
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
4.79
1.11
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
47.18
10.88
St. Charles River at 1-25,
GEI 2014
SC-I
4.335
4.88
1.12
GEI 2014
Wildhorse Creek, WHC
56.14
5.43
0.10
GEI 2014
Wildhorse Creek, WHC
34.24
36.23
1.06
GEI 2014
Wildhorse Creek, WHC
34.24
10.22
0.30
GEI 2014
Wildhorse Creek, WHC
34.24
52.16
1.52
GEI 2014
Wildhorse Creek, WHC
34.24
40.81
1.19
GEI 2014
Wildhorse Creek, WHC
34.24
26.45
0.77
GEI 2014
Wildhorse Creek, WHC
62.34
61.90
0.99
GEI 2014
Wildhorse Creek, WHC
62.34
15.88
0.25
GEI 2014
Wildhorse Creek, WHC
62.34
27.40
0.44
GEI 2014
Wildhorse Creek, WHC
62.34
23.10
0.37
Muscatello and Janz 2009
Indigo Lake
0.36
0.99
2.75
Muscatello and Janz 2009
Vulture Lake
1.62
3.37
2.08
Grassoetal. 1995
17
1.91
2.84
1.49
Grassoetal. 1995
17
1.91
3.19
1.67
Grassoetal. 1995
17
1.91
3.44
1.80
Grassoetal. 1995
17
1.91
3.64
1.91
B-154
-------
White sucker (Catostomus commersonii)
Study
Site
c
^invert
Cfish
Ratio
Grassoetal. 1995
17
1.91
4.00
2.09
Grassoetal. 1995
17
1.91
4.01
2.10
Butler etal. 1994
NFK3
2.00
3.90
1.95
Butler etal. 1993
ST1
2.25
4.90
2.18
Lambing et al. 1994
S33
2.40
3.50
1.46
Mueller etal. 1991
Al
2.70
4.20
1.56
GEI2013
SWA1
2.81
2.83
1.01
GEI2013
SWA1
2.81
3.89
1.39
GEI 2013
SWA1
2.81
4.18
1.49
Mason et al. 2000
HCRT
2.81
0.81
0.29
Mason et al. 2000
HCRT
2.81
1.43
0.51
Mason et al. 2000
HCRT
2.81
1.43
0.51
Butler etal. 1993
WSB2
3.00
3.90
1.30
Butler etal. 1993
SP2
3.15
3.50
1.11
Butler etal. 1993
LP4
3.20
2.80
0.88
GEI 2013
SW4-1
3.33
3.01
0.91
GEI 2013
SW4-1
3.33
3.45
1.04
GEI 2013
SW4-1
3.33
3.50
1.05
GEI 2013
SW4-1
3.33
3.62
1.09
GEI 2013
SW4-1
3.33
4.04
1.22
GEI 2013
SW4-1
3.33
4.08
1.23
GEI 2013
SW4-1
3.33
4.13
1.24
GEI 2013
SW4-1
3.33
4.17
1.25
GEI 2013
SW4-1
3.33
4.34
1.31
GEI 2013
SW4-1
3.33
4.78
1.44
Butler etal. 1993
ST2
3.35
7.00
2.09
GEI 2013
LG1
3.37
3.54
1.05
GEI 2013
LG1
3.37
3.55
1.05
GEI 2013
LG1
3.37
3.90
1.16
GEI 2013
LG1
3.37
3.95
1.17
GEI 2013
LG1
3.37
4.48
1.33
GEI 2013
LG1
3.39
3.00
0.88
GEI 2013
LG1
3.56
2.72
0.77
GEI 2013
LG1
3.56
2.80
0.79
GEI 2013
LG1
3.56
2.89
0.81
GEI 2013
LG1
3.56
2.99
0.84
GEI 2013
LG1
3.56
3.04
0.86
GEI 2013
LG1
3.56
3.08
0.87
GEI 2013
LG1
3.56
3.13
0.88
GEI 2013
LG1
3.56
3.18
0.89
GEI 2013
LG1
3.56
3.25
0.91
GEI 2013
LG1
3.56
3.27
0.92
B-155
-------
White sucker (Catostomus commersonii)
Study
Site
r
^invert
Cfish
Ratio
Butler et al.
1993
WSB2
3.60
4.30
1.19
Butler et al.
1993
WSB2
3.60
6.30
1.75
GEI2013
SWA1
3.64
2.83
0.78
GEI2013
SWA1
3.64
3.39
0.93
GEI 2013
SWA1
3.64
3.47
0.95
GEI 2013
SWA1
3.64
3.55
0.98
GEI 2013
SWA1
3.64
3.63
1.00
GEI 2013
SWA1
3.64
3.75
1.03
Butler et al.
1993
SB2
3.65
4.30
1.18
Butler et al.
1993
R2
3.70
4.20
1.14
Butler et al.
1993
SB2
3.75
4.80
1.28
GEI 2013
CC1
3.76
5.99
1.59
GEI 2013
CC1
3.76
6.56
1.74
GEI 2013
CC1
3.76
7.21
1.92
GEI 2013
CC1
3.76
7.42
1.97
GEI 2013
CC1
3.76
7.62
2.03
Peterson et al. 1991
7
3.83
3.30
0.86
Peterson et al. 1991
7
3.83
4.64
1.21
Butler et al.
1993
R2
3.90
5.40
1.38
Butler et al.
1991
4
3.90
5.30
1.36
GEI 2013
SW88
3.96
4.63
1.17
GEI 2013
SW88
3.96
4.75
1.20
Butler et al.
1993
R1
4.00
9.50
2.38
Butler et al.
1993
ST2
4.10
8.30
2.02
GEI 2013
SW9
4.45
4.07
0.91
GEI 2013
SW9
4.45
4.18
0.94
GEI 2013
SW9
4.45
4.19
0.94
GEI 2013
SW9
4.45
4.20
0.94
GEI 2013
SW9
4.45
4.40
0.99
GEI 2013
SW9
4.45
5.18
1.16
GEI 2013
CC1
4.69
4.51
0.96
GEI 2013
CC1
4.69
4.57
0.98
GEI 2013
CC1
4.69
4.94
1.05
GEI 2013
CC1
4.69
5.02
1.07
GEI 2013
CC1
4.69
5.81
1.24
GEI 2013
CC1
4.69
6.01
1.28
GEI 2013
CC1
4.69
6.43
1.37
GEI 2013
CC1
4.69
7.25
1.55
GEI 2013
CC1
4.69
8.00
1.71
GEI 2013
CC1
4.69
8.52
1.82
Butler et al.
1993
F2
4.80
5.20
1.08
GEI 2013
CC1
5.86
5.00
0.85
B-156
-------
White sucker (Catostomus commersonii)
Study
Site
c
^invert
Cfish
Ratio
GEI2013
CC1
5.86
5.37
0.92
GEI2013
CC1
5.86
5.59
0.95
GEI 2013
CC1
5.86
5.71
0.98
GEI 2013
CC1
5.86
5.90
1.01
GEI 2013
CC1
5.86
6.61
1.13
GEI 2013
CC1
5.86
6.79
1.16
GEI 2013
CC1
5.86
6.82
1.16
GEI 2013
CC1
5.86
7.29
1.25
GEI 2013
CC1
5.86
7.48
1.28
Butler etal. 1991
3
6.20
1.80
0.29
GEI 2013
SWB
7.06
7.18
1.02
GEI 2013
SWB
7.06
7.36
1.04
GEI 2013
SWB
7.06
7.98
1.13
GEI 2013
SWB
7.06
8.03
1.14
GEI 2013
SWB
7.06
9.65
1.37
GEI 2013
SWB
7.06
12.76
1.81
GEI 2013
SWB
7.06
12.85
1.82
GEI 2013
SWB
7.06
13.16
1.86
GEI 2013
SWB
7.44
8.21
1.10
GEI 2013
SWB
7.44
8.77
1.18
GEI 2013
SWB
7.44
8.85
1.19
GEI 2013
SWB
7.44
9.87
1.33
GEI 2013
SWB
7.44
10.97
1.48
GEI 2013
SWB
7.44
13.59
1.83
GEI 2013
SWB
7.44
15.75
2.12
GEI 2013
SWB
7.44
16.40
2.21
Butler etal. 1994
IW
8.35
9.70
1.16
Mueller etal. 1991
R1
8.70
3.40
0.39
GEI 2013
SW2-1
9.14
16.54
1.81
GEI 2013
SW2-1
9.14
18.14
1.99
GEI 2013
SW2-1
9.14
18.54
2.03
GEI 2013
SW2-1
9.14
19.16
2.10
GEI 2013
SW2-1
9.14
21.29
2.33
Lambing et al. 1994
S34
14.00
25.30
1.81
Lambing et al. 1994
S34
14.00
28.00
2.00
Lambing et al. 1994
S34
14.00
29.00
2.07
Butler etal. 1994
HCC1
21.00
3.00
0.14
Butler etal. 1994
GUN2
28.00
20.00
0.71
Butler etal. 1991
7
29.80
7.90
0.27
B-157
-------
White sucker (Catostomus commersonii)
Study Site
c
^invert
Cfish
Ratio
o
o
30
60
Median ratio:
1.11
R2:
0.38
F:
174.4
df:
284
P:
<0.001
Yellow perch (Perca flavescens)
Study
Site
r
^invert
Cfish
Ratio
Butler etal. 1995
PU
0.61
1.10
1.80
Butler etal. 1995
XT
1.07
1.60
1.50
Butler etal. 1995
XT
1.07
1.70
1.60
Butler etal. 1995
MP
1.60
2.00
1.25
Butler etal. 1995
MP
1.60
2.20
1.38
Butler etal. 1995
MP
1.60
2.70
1.69
Belize et al. 2006
Halfway
1.74
2.72
1.56
Belize et al. 2006
Geneva
2.29
3.30
1.44
Belize et al. 2006
Bethel
2.61
3.09
1.19
Belize et al. 2006
McFarlane
3.79
5.40
1.42
Peterson et al. 1991
7
3.83
7.33
1.91
Belize et al. 2006
Long
4.42
6.28
1.42
Belize et al. 2006
Ramsey
4.97
7.64
1.54
Belize et al. 2006
Windy
6.32
6.06
0.96
Belize et al. 2006
Nelson
6.79
10.68
1.57
GEI2013
SW11
8.41
4.54
0.54
GEI2013
SW11
8.41
5.49
0.65
GEI 2013
SW11
8.41
5.50
0.65
GEI 2013
SW11
8.41
5.58
0.66
GEI 2013
SW11
8.41
5.68
0.68
Lambing et al. 1994
S34
14.00
67.00
4.79
B-158
-------
Yellow perch (Perca flavescens)
Median ratio
B-159
-------
Table B-7. Final vertebrate Trophic Transfer Factor (TTF) values, including estimated values using taxonomic classification.
( (iiniiKiii iiiiino
Scientific 11:11110
Order
l-'iiinih
(¦CIIIIS
III"
I I I-' source
alligator gar
Atractosteus spatula
Lepistosteiformes
Lepisosteidae
Atractosteus
1.21
All fish
black bullhead
Ameiurus melas
Siluriformes
Ictaluridae
Ameiurus
0.85
Exact match
black crappie
Pomoxis nigromaculatus
Perciformes
Centrarchidae
Pomoxis
2.67
Exact match
black redhorse
Moxostoma duquesnei
Cypriniformes
Catostomidae
Moxostoma
1.01
Family Catostomidae
blacknose dace
Rhinichthys atratulus
Cypriniformes
Cyprinidae
Rhinichthys
0.71
Exact match
blue catfish
Ictalurus furcatus
Siluriformes
Ictaluridae
Ictalurus
0.68
Genus Ictalurus
bluegill
Lepomis macrochirus
Perciformes
Centrarchidae
Lepomis
1.03
Exact match
bluehead sucker
Catostomus discobolus
Cypriniformes
Catostomidae
Catostomus
1.04
Exact match
brassy minnow
Hybognathus hankinsoni
Cypriniformes
Cyprinidae
Hybognathus
1.20
Family Cyprinidae
brook stickleback
Culaea inconstans
Gasterosteiformes
Gasterosteidae
Culaea
1.79
Exact match
brook trout
Salvelinus fontinalis
Salmo niformes
Salmonidae
Salvelinus
0.88
Exact match
brown bullhead
Ameiurus nebulosus
Siluriformes
Ictaluridae
Ameiurus
0.85
Genus Ameiurus
brown trout
Salmo trutta
Salmo niformes
Salmonidae
Salmo
1.38
Exact match
bullhead
Siluriformes
Ictaluridae
0.77
Family Ictaluridae
burbot
Lota lota
lota
Gadiformes
Lotidae
1.21
All fish
chain pickerel
Esox niger
Esociformes
Esocidae
Esox
1.78
Genus Esox
channel catfish
Ictalurus punctatus
Siluriformes
Ictaluridae
Ictalurus
0.68
Exact match
common carp
Cyprinus carpio
Cypriniformes
Cyprinidae
Cyprinus
1.20
Exact match
common snook
Centropomus undecimalis
Perciformes
Centropomidae
Centropomus
1.41
Order Perciformes
crappie
Pomoxis sp.
Perciformes
Centrarchidae
Pomoxis
2.67
Genus Pomoxis
creek chub
Semotilus atromaculatus
Cypriniformes
Cyprinidae
Semotilus
1.06
Exact match
cutthroat trout
Oncorhynchus clarkii
Salmo niformes
Salmonidae
Oncorhynchus
1.12
Exact match
fltvi 0 r
desert pupfish
Cyprinodon macularius
Cyprinodontiformes
Cyprinodontidae
Cyprinodon
1.24
UIUCI
Cyprinodontiformes
dolly varden
Salvelinus malma
Salmo niformes
Salmonidae
Salvelinus
0.88
Genus Salvelinus
fathead minnow
Pimephales promelas
Cypriniformes
Cyprinidae
Pimephales
1.57
Exact match
flannelmouth sucker
Catostomus latipinnis
Cypriniformes
Catostomidae
Catostomus
0.98
Exact match
flathead catfish
Pylodictis olivaris
Siluriformes
Ictaluridae
Pylodictus
0.77
Family Ictaluridae
flathead chub
Platygobio gracilis
Cypriniformes
Cyprinidae
Platygobio
1.20
Family Cyprinidae
freshwater drum
Aplodinotus grunniens
Perciformes
Sciaenidae
Aplodinotus
1.41
Order Perciformes
gizzard shad
Dorosoma cepedianum
Clupeiformes
Clupeidae
Dorosoma
1.21
All fish
goldeye
Hiodon alosoides
Hiodontiformes
Hiodontidae
Hiodon
1.21
All fish
green sunfish
Lepomis cyanellus
Perciformes
Centrarchidae
Lepomis
1.12
Exact match
iowa darter
Etheostoma exile
Perciformes
Percidae
Etheostoma
1.51
Family Percidae
kokanee salmon
Oncorhynchus nerka
Salmo niformes
Salmonidae
Oncorhynchus
1.10
Genus Oncorhynchus
largemouth bass
Micropterus salmoides
Perciformes
Centrarchidae
Micropterus
1.39
Exact match
largescale sucker
Catostomus macrocheilus
Cypriniformes
Catostomidae
Catostomus
1.01
Genus Catostomus
longnose dace
Rhinichthys cataractae
Cypriniformes
Cyprinidae
Rhinichthys
0.71
Genus Rhinichthys
B-160
-------
( (iiniiKiii iiiiino
Scientific 11:11110
Order
l;uilil\
(¦ciiiis
III"
I I I-' source diilii
longnose sucker
Catostomus catostomus
Cypriniformes
Catostomidae
Catostomus
0.90
Exact match
mottled sculpin
Cottus bairdi
Scorpaeniformes
Cottidae
Cottus
1.38
Exact match
mountain whitefish
Prosopium williamsoni
Salmoniformes
Salmonidae
Prosopium
1.38
Exact match
nine spine stickleback
Pungitius pungitius
pungitius
Gasterosteiformes
Gasterosteidae
1.79
Family Gasterosteidae
northern pike
Esox lucius
Esociformes
Esocidae
Esox
1.78
Exact match
northern pikeminnow
Ptychocheilus oregonensis
Cypriniformes
Cyprinidae
Ptychocheilus
1.20
Family Cyprinidae
northern plains killifish
Fundulus kansae
Cyprinodontiformes
Fundulidae
Fundulus
1.27
Exact match
northern redbelly dace
Chrosomus eos
Cypriniformes
Cyprinidae
Chrosomus
1.20
Family Cyprinidae
northern squawfish
Ptychocheilus oregonensis
Cypriniformes
Cyprinidae
Ptychocheilus
1.20
Family Cyprinidae
quillback
Carpiodes cyprinus
Cypriniformes
Catostomidae
Carpiodes
1.01
Family Catostomidae
rainbow trout
Oncorhynchus mykiss
Salmoniformes
Salmonidae
Oncorhynchus
1.07
Exact match
razorback sucker
Xyrauchen texanus
Cypriniformes
Catostomidae
Xyrauchen
1.01
Family Catostomidae
red shiner
Cyprinella lutrensis
Cypriniformes
Cyprinidae
Cyprinella
1.31
Family Cyprinidae
redbreast sunfish
Lepomis auritus
Perciformes
Centrarchidae
Lepomis
1.07
Genus Lepomis
redear sunfish
Lepomis microlophus
Perciformes
Centrarchidae
Lepomis
1.07
Genus Lepomis
redside shiner
Richardsonius balteatus
Cypriniformes
Cyprinidae
Richardsonius
1.08
Exact match
river carpsucker
Carpiodes carpio
Cypriniformes
Catostomidae
Carpiodes
1.01
Family Catostomidae
river redhorse
Moxostoma carinatum
Cypriniformes
Catostomidae
Moxostoma
1.01
Family Catostomidae
rock bass
Ambloplites rupestris
Perciformes
Centrarchidae
Ambloplites
1.12
Family Centrarchidae
roundtail chub
Gila robusta
Cypriniformes
Cyprinidae
Gila
1.20
Family Cyprinidae
sacramento perch
Archoplites interruptus
Perciformes
Centrarchidae
Archoplites
1.12
Family Centrarchidae
sacramento pikeminnow
Ptychocheilus grandis
Cypriniformes
Cyprinidae
Ptychocheilus
1.20
Family Cyprinidae
sailfin molly
Poecilia latipinna
Cyprinodontiformes
Poeciliidae
Poecilia
1.21
Family Poeciliidae
sand shiner
Notropis stramineus
Cypriniformes
Cyprinidae
Notropis
1.56
Exact match
sauger
Sander canadensis
Perciformes
Percidae
Sander
1.60
Genus Sander
sculpin
Cottus sp.
Scorpaeniformes
Cottidae
Cottus
1.29
Exact match
shadow bass
Ambloplites ariommus
Perciformes
Centrarchidae
Ambloplites
1.12
Family Centrarchidae
shorthead redhorse
Moxostoma macrolepidotum
Cypriniformes
Catostomidae
Moxostoma
1.01
Family Catostomidae
silver carp
Hypophthalmichthys molitrix
Cypriniformes
Cyprinidae
Hypophthalmichthys
1.20
Family Cyprinidae
smallmouth bass
Micropterus dolomieu
Perciformes
Centrarchidae
Micropterus
0.86
Exact match
smallmouth buffalo
Ictiobus bubalus
Cypriniformes
Catostomidae
Ictiobus
1.01
Family Catostomidae
speckled dace
Rhinichthys osculus
Cypriniformes
Cyprinidae
Rhinichthys
0.71
Genus Rhinichthys
spottail shiner
Notropis hudsonius
hudsonius
Cypriniformes
Cyprinidae
1.56
Genus Notropis
spotted bass
Micropterus punctulatus
Perciformes
Centrarchidae
Micropterus
1.12
Genus Micropterus
spotted gar
Lepisosteus oculatus
Lepistosteiformes
Lepisosteidae
Lepisosteus
1.21
All fish
stonecat
Noturus flavus
Siluriformes
Ictaluridae
Noturus
0.77
Family Ictaluridae
striped bass
Morone saxatilis
Perciformes
Moronidae
Morone
1.48
Exact match
striped mullet
Mugil cephalus
Mugiliformes
Mugilidae
Mugil
1.21
All fish
B-161
-------
( (iiniiKiii iiiiino
Scientific 11:11110
Order
l-'iiinih
(¦ciiiis
III"
I I I-' source diilii
sucker
Cypriniformes
Catostomidae
1.01
Family Catostomidae
tilapia
Perciformes
Cichlidae
1.41
Order Perciformes
trout species
Oncorhynchus sp.
Salmoniformes
Salmonidae
Oncorhynchus
1.10
Genus Oncorhynchus
tui chub
Gila bicolor
Cypriniformes
Cyprinidae
Gila
1.20
Family Cyprinidae
utah sucker
Catostomus ardens
Cypriniformes
Catostomidae
Catostomus
1.01
Genus Catostomus
walleye
Sander vitreus
Perciformes
Percidae
Sander
1.60
Exact match
western mosquitofish
Gambusia affinis
Cyprinodontiformes
Poeciliidae
Gambusia
1.21
Exact match
white bass
Morone chrysops
Perciformes
Moronidae
Morone
1.48
Genus Morone
white crappie
Pomoxis annularis
Perciformes
Centrarchidae
Pomoxis
2.67
Genus Pomoxis
white sturgeon
Acipenser transmontanus
Acipenseriformes
Acipenseridae
Acipenser
1.21
All fish
white sucker
Catostomus commersonii
Cypriniformes
Catostomidae
Catostomus
1.11
Exact match
wiper
Morone chrysops x Moron saxatilis
Perciformes
Moronidae
Morone
1.48
Genus Morone
yellow perch
Perca Jlavescens
Perciformes
Percidae
Perca
1.42
Exact match
B-162
-------
4.0 Food Web Models Used to Calculate Composite TTFs to Translate the Egg-Ovary FCV to Water-Column Values
Table B-8. Food web models used to calculate composite TTFs to translate the egg-ovary FCV to a water-column value at aquatic sites where sufficient data was available to calculate an enrichment factor (EF).
Ki-li-mi
Sili-
Sili-
T;ir»i-l
I'ish
I'ish pri-\ :is di-si rihi-d in \;iiuri-Si-r\i- I'ish piv\ spp
r H2 in
1° 11.2
1°
r 11.2
2° 11.2
">o
2°
2° 11.2
3° 11.2
3°
3°
3° 11.2 4° 11.2 4° 4° 4° 11.2
1°
r 11 .3
r Ti.3
r r ti.3
I! Hill i\
T;ir»i-
TTI''i'iuii|>iisi
ii-
ik'siripi
ll)
11 sli
III
iiuii nii-nl
spi-iii-s usi-d
S|)|)
11.2
l>i-i-n|>i>rl in
S|)|) llsi-d
11.2
11.2
priipniiiii s|>|> usi-d 11.2 TI.2 prupiniiii
11.3
S|)|) lisi-il
S|)|)
11.3 pnipiirliii
I- I I I "
1 llsli
li-
inn
spi-iii-s
;il>l>ri-\
II
n
S|)|)
II
n
S|)|)
II
11 S|)|) II 11
S|)|)
;il>l>ri-\
II n
III
i n in mi i
1
;il>ri-\
1
;il>ri-\
1
;il>ri-\ I-"
1
n n;inii-
Default
black
0.85
Omnivorous bottom feeder; often eats
Median of all
in
2.14
0.45
Median of
CIS
1.41
0.45
Median of
bvs
4.29
0.10
2.03
0.85
1.72
bullhea
aquatic insects, crustaceans, molluscs,
insects
all
all
d
occasionally fishes and carrion
crustacean
bivalves
Default
black
2.67
Primarily a midwater feeder; zooplankton
Median of all
in
2.14
0.50
S
Median of
pc
1.41
0.10
Fish
Median all
f+a
2.28 0.4
2.12
2.67
5.66
crappie
and small Diptera larvae predominate in
insects
planktonic
fish eating
the diet of individuals to 12 cm SL, while
crustacean
median all
fishes and aquatic insects predominate in
s
invertebrat
the diet of larger individuals
es
Default
blackno
0.71
Eats immature aquatic insects,
Median of all
in
2.14
0.50
Median of
all
1.48
0.50
1.81
0.71
1.29
Default
Default
Default
Default
bluegill 1.03
se dace amphipods, and various other aquatic
invertebrates; also eats algae and
diatoms, which may be of little
nutritional value (Smith 1979, Becker
1983).
blue 0.68 Bottom feeder. Eats mostly crustaceans
catfish and aquatic insects when young. Later,
fishes and large invertebrates become
most important (Moyle 1976). Also
scavenges.
Feeds opportunistically on aquatic insect
larvae, planktonic crustaceans, flying
insects, snails, and other small
invertebrates; small fishes, fish eggs,
crayfish, and algae sometimes are eaten.
Larvae and juveniles often eat
cladocerans and copepod nauplii. Adults
eats mainly aquatic insects, crayfishes,
and small fishes, or, in some bodies of
water, mostly zooplankton. Feeds at all
levels of water column,
bluehea 1.04 Herbivore, Invertivore
d
sucker
brassy 1.20 Eats algae, phyto- and zooplankton,
minnow benthic invertebrates, surface drift,
bottom ooze (Becker 1983).
insects
Median of all in
insects
Median of all in
insects
all
invertebrat
es except
bivalves
2.14
2.14
0.36 Median
insects and
benthic
crustacean
s
0.68 Median of pc
planktonic
crustacean
s
in,be 1.74
1.41
0.20 Median of bvs
all
bivalves
0.20 crayfish cr
4.29
1.46
0.08
0.08
TL1
TL1
TL1
TL1
1.00
1.00
0.60 Median of all
all
invertebrat
es except
bivalves
0.50 Median of pc
planktonic
crustacean
1.48
1.41
0.40
0.40 Median of in
all insects
2.14
0.10
Fish Median all f+a 2.28 0.36
fish eating
median all
invertebrat
es
Fish Median all f+a 2.28 0.04
fish eating
median all
invertebrat
es
2.28 0.6
1.56
1.95 1.03 2.00
1.19 1.04 1.24
1.28 1.20 1.54
B-163
-------
Ki-l'i-mi Sili- Sili-
ii- di-siripi II)
inn
T;ir»i-l I'isli
iisii in
spi-iii-s
imiiinii
11 11:11111-
I'isli |)n\ :is di-si rihi-d in \:iliiri-Si-r\i-
i"ish pn-\ spp 1° 11.2111 i° ti.2 r rn.2 2° 11.2
I'lininii-nl spi-iii-s usi-d spp 11.2 pnipiiriin spp usi-d
;il>l>ri-\ II n
I
">o
11.2
spp
;il)iv\
Default
Default
Default
Default
Default
Default
Default
brook 1.79 Eats various aquatic invertebrates
stickleb (including eggs and larvae), eggs and
ack larvae of fishes, and algae. In a Manitoba
lake, was opportunistic but heavily
dependent on arthropods (Moodie 1986).
brook 0.88 Feeds opportunistically on various
trout invertebrate and vertebrate animals,
including primarily terrestrial and aquatic
insects and planktonic crustaceans.
brown 0.85 Bottom feeder. Young eat chironomid
bullhea larvae and small crustaceans. Adults eat
d larger insect larvae and fishes, also fish
eggs, mollusks, carrion, and plant
material (Becker 1983, Moyle 1976).
brown 1.38 Eats aquatic and terrestrial insects and
trout their larvae, crustaceans (especially
crayfish), molluscs, fishes, and other
animals. In streams, young feed mainly
on aquatic and terrestrial drift
invertebrates; in lakes, they feed on
zooplankton and benthic invertebrates
(Sublette et al. 1990). Large adults feed
on fishes, crayfish, and other benthic
invertebrates.
Black (not exotic to CO and NM):
Omnivorous bottom feeder; often eats
aquatic insects, crustaceans, molluscs,
occasionally fishes and carrion. Stomach
often contain substantial amounts of plant
material of unknown nutritional value
(Moyle 1976). Juveniles planktivorous; at
about 27 mm TL, feed largely on
crustaceans and midge larvae
1.21 Young eat mainly immature aquatic
insects, crayfish, molluscs, and other
deepwater invertebrates. Larger
individuals feed mostly on fishes (Becker
1983, Scott and Crossman 1973).
0.68 Bottom feeder. Young eat mainly small
invertebrates; as they grow, fishes and
crayfish become increasingly important,
though individuals of all sizes eat
abundant aquatic insects. Large fish are
mainly piscivorous (Moyle 1976).
bullhea 0.77
d
burbot
channel
catfish
Median of all all
invertebrates
except
bivalves
Median of all in
insects
Median of all in
insects
Median of
planktonic
crustaceans
pc
1.48
2.14
2.14
1.41
0.80 TL1
TL1
0.60 crayfish cr
0.68 Median of
all
invertebrat
es except
bivalves
0.20 Median of
all insects
Median of all in
insects
2.14
Median of all in
insects
Median of all in
insects
2.14
2.14
all
0.68 Median of
all
invertebrat
es except
bivalves
0.25 Median of
all
crustacean
s
0.48 Median of
planktonic
crustacean
all
pc
2° 2° 11.2 3° 11.2 3° 3° 3° 11.2 4° 11.2 4° 4° 4° 11.2 1° 1° 11.3
TI.2 pnipiiriin spp usi-d I I.2 TI.2 pnipiiriin spp usi-d I I.2 TI.2 pnipiirliii TI.3 spp usi-d
n spp TT n spp TT n spp
II
I
:il>ri-\ !¦"
II
;il>ri-\ T
1° TI.3 1° l° TI.3
spp T1.3 pniporiio
;il>l>ri-\ 'IT n
I
IH'li-iiiN T:ir»i- I Tl'iiiniposi
i- I TI-" 1 fish k-
III
1.00
0.20
1.38 1.79
2.47
1.46 0.10 Median of bvs 4.29 0.05
all
bivalves
1.48 0.20 Median of bvs
all
bivalves
4.29
0.04
Fish Median all f+a 2.28
fish eating
median all
invertebrat
es
Fish Median all f+a 2.28
fish eating
median all
invertebrat
0.25 2.22 0.S
1.96
0.08 2.11 0.85 1.79
2.14
0.12 crayfish cr
1.46
0.08
Fish Median all f+a
fish eating
median all
invertebrat
2.28
0.6 2.02 1.38 2.78
1.48 0.20 Median of bvs 4.29 0.04
all
bivalves
Fish Median all
fish eating
median all
invertebrat
f+a
2.28 0.08
2.11 0.77 1.62
1.41 0.25
1.41 0.20 crayfish cr 1.46 0.08
Fish Median all f+a
fish eating
median all
invertebrat
es
Fish Median all f+a
fish eating
median all
invertebrat
es
2.28 0.5
2.28 0.24
2.03 1.21 2.45
1.97 0.6
1.35
B-164
-------
Ki-l'i-ri-n Sili- Sili-
ii- di-siripi II)
inn
T;ir»i-l I'isli
iisii in
spi-iii-s
imiiinii
11 11:11111-
I'isli |)n\ :is di-si rihi-d in \:iluri-Si-r\i-
i"ish pn-\ spp 1° 11.2111 i° ti.2 r rn.2 2° 11.2
imiimi-nl spi-iii-s usi-d spp 11.2 prupurliii spp usi-d
;il>l>ri-\ II n
">o
11.2
spp
;il>ri-\
I 1.2
II
I
2° I 1.2
pnipiiriin
n
3° 11.2
spp iim-(I
I 1.2
spp
:il>ri-\
11.2
II
I
3° 11.2
pnipiiriin
n
4° 11.2
spp IISI-(I
4°
11.2
spp
;il>ri-\
4°
n.2
ii
i
4° 11.2
pnipiiriin
n
1°
11.3
spp
r 11 .3
spp IISI-(I
rn.3 r
spp 11.3
;il>l>ri-\ IT
I
1 ° TI.3 IH'li-iiiN T:ir»i- Tl Tiiimposi
pnipiiriin i- III I llsli k-
n III
Default
Default
Default
Default
Default
Default
Default
Default
commo
n carp
crappie
creek
chub
cutthroa
t trout
fathead
minnow
flannel
mouth
sucker
flathead
chub
freshwa
ter
drum
1.20
2.67
1.06
1.12
1.57
0.98
1.20
1.41
Omnivorous; adults eat mainly
invertebrates, detritus, fish eggs, and
plant material (Jester 1974, Becker 1983,
Sublette et al. 1990).
Black: Primarily a midwater feeder;
zooplankton and small Diptera larvae
predominate in the diet of individuals to
12 cm SL, while fishes and aquatic
insects predominate in the diet of larger
individuals. White: eats fishes, planktonic
crustaceans, and aquatic insects; small
individuals eat mostly zooplankton, fish
tend to predominate in the diet of larger
individuals, though zooplankton also
consumed (Moyle 1976)
Feeds opportunistically on various plants
and animals, from surface drift to
benthos; mostly invertivorous but large
individuals often picivorous (Becker
1983). Chironomid larvae and other
larval insects important in diet of young.
Opportunistic. Inland cutthroats feed
primarily on insects (aquatic and
terrestrial); often feeds in and especially
downstream from riffle areas; some large
individuals feed mostly on fishes; also
eats zooplankton and crustaceans.
Feeds opportunistically in soft bottom
mud; eats algae and other plants, insects,
small crustaceans, and other invertebrates
(Becker 1983, Sublette et al. 1990).
Herbivore, Invertivore Bottom feeder.
Reported to feed on diatoms, algae,
fragments of higher plants, seeds, and
benthic invertebrates (Sigler and Miller
1963; Lee et al. 1980). See Tyus and
Minckley 1988 for possible importance
of Mormon cricket as food source.
Opportunistic; eats aquatic and terrestrial
insects and some algae (Olund and Cross
1961)
Young feed mainly on minute
crustaceans; adults mostly are bottom
feeders, eat insect larvae, crustaceans,
fishes, and (mostly in rivers) clams and
expected diet
of small
invertebrates
Median of all
invertebrates
except
bivalves
Median of all
insects
all
1.48
2.14
0.65 TL1
Median of all all
invertebrates
except
bivalves
Median of all in
insects
Median of all in
insects
Median in,be
insects and
benthic
crustaceans
Median of all in
insects
Median of all crs
crustaceans
1.48
2.14
2.14
1.74
2.14
1.41
TL1 1.00
0.50 Median of pc
planktonic
crustacean
1.41
0.35
0.10
Fish Median all
fish eating
median all
invertebrat
0.70 TL1
TL1 1.00
0.20
0.50 Median of crs
all
crustacean
s
0.60 Median of crs
all
crustacean
1.41
0.20
0.75 TL1
TL1
1.41
1.00
0.20 TL1
0.25
TL1 1.00
0.20
0.80 TL1
TL1 1.00
0.44 Median of in 2.14
all insects
0.20
0.40 Median of bvs 4.29
all
bivalves
0.04
f+a
2.28
0.4
1.31 1.20 1.58
2.12 2.67 5.66
Fish Median all
fish eating
median all
invertebrat
es
Fish Median all
fish eating
median all
invertebrat
es
f+a
2.28
0.1
1.46
f+a
2.28
0.3
2.04
1.77
1.55
Fish Median all f+a
fish eating
median all
invertebrat
2.28
0.12
1.06
1.12
1.57
0.98
1.55
2.29
2.78
1.52
1.91 1.20 2.30
1.92 1.41 2.71
B-165
-------
Ki-li-ri-n Sili- Sili- T;ir»i-l I'isli I'isli pri-\ :is di-snihi-d in \:iliiri-Si-r\i- I'isli pri-> spp 1° TI.2 TTI-" l°TI.2 1° l°TI.2 2° TI.2 2°
ii- di-siripi II) IIsli nr iiiiiiiiii-nl spi-iii-s usi-d spp 11.2 pnipuriiii spp usi-d 11.2
inn spi-iii-s ;il>l>ri-\ II n spp
I'lininiii I' ;il>ri-\
n 11:11111-
snails (Becker 1983, Scott and Crossman
1973, Lee etal. 1980).
Default
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gizzard 1.21 Adults primarily bottom filter-feeding
shad detritivores
goldeye 1.21 Young-of-year eat mainly
microcrustaceans, also other
invertebrates. Older individuals eat
mainly aquatic insects obtained at surface
but also various other animals, including
frogs, fishes, and small mammals,
green 1.12 Feeds opportunistically on the larger,
sunfish more active invertebrates that occur with
them, and on small fishes. Young feed
mostly on crustaceans (zooplankton) and
aquatic insect larvae. Adults eat more
large aquatic and terrestrial insects,
crayfish, and fishes
Iowa 1.51 Eats mainly various invertebrates;
darter commonly ingested food items of adults
are midge larvae, mayfly naiads, and
amphipods, and of the young, copepods
and cladocerans. Apparently feeds on
swimming organisms and those on
bottom.
1.10 Zooplankton, insects.
kokane
e
salmon
largemo
uth bass
expected diet
of small
invertebrates
1.39 Fry feed mainly on zooplankton. Larger
young eat insects, crustaceans, and fish
fry. Adults eat mainly fishes, though
sometimes prefer crayfish or amphibians
(Moyle 1976, Smith 1979).
longnos 0.71 Eats mainly benthic insects, especially
e dace Diptera and mayflies (Becker 1983, Scott
and Crossman 1973); also eats algae and
plant material (Sublette et al. 1990).
Terrestrial insects and fish eggs common
in diet of adults from Lake Michigan (see
Sublette et al. 1990).
longnos 0.90 Eats mostly bottom invertebrates (Scott
e sucker and Crossman 1973).
TL1 TL1
Median in,be
insects and
benthic
crustaceans
Median of all in
insects
1.00
1.74
1.00
1.00
2.14
Median of all in
insects
2.14
0.58 Median of pc
planktonic
crustacean
0.70 amphipods am
Median of
planktonic
crustaceans
pc
Median of all in
insects
Median of all in
insects
1.41
2.14
2.14
0.80 Median of in
all insects
0.10 crayfish cr
0.80 TL1
TL1
Median of all
invertebrates
except
bivalves
all
1.48
1.00
11.2
II
I
2° 11.2
pnipuriiii
11
3° 11.2
spp usi-il
I 1.2
spp
:il>ri-\
11.2
II
I
3° 11.2
pnipuriiii
11
4° 11.2
spp IISI-(I
4°
11.2
spp
;il>ri-\
4°
11.2
IT
I
4° 11.2
pnipuriiii
11
r rn.3
I 1.3 spp llsi-(l
spp
rn.3 r i°n.3
spp 11.3 pnipuriiii
;il>l>ri-\ 'IT 11
I
IH'li-iiiN T:ir»i- I Tl'iiinipnsi
i- I TI-" 1 fish k-
III
1.00
1.74
1.21
1.21
1.21
2.10
1.41
0.10 crayfish cr
1.46
0.08
Fish Median all
fish eating
median all
invertebrat
es
f+a
2.28
0.24
2.05
1.12
2.29
1.22 0.16 crayfish cr 1.46 0.08 Median of pc 1.41 0.06 1.90 1.51 2.87
planktoni
c
Crustacea
ns
2.14
0.20
1.56
1.10
1.71
1.46 0.10 Fish Median all f+a 2.28 0.8 2.18 1.39 3.04
fish eating
median all
invertebrat
es
1.00 0.20 1.91 0.71 1.36
1.48 0.90 1.34
B-166
-------
Ki-l'i-ri-n Sili- Sili-
ii- di-siripi II)
inn
T;ir»i-l I'isli
iisii in
spi-iii-s
imiiinii
11 11:11111-
I'isli |)n\ :is di-si rihi-d in \:iluri-Si-r\i-
i"ish pn-\ spp 1° 11.2111 i° ti.2 r rn.2 2° 11.2
I'lininii-nl spi-iii-s usi-d spp 11.2 prnpnrlin spp usi-d
;il>l>ri-\ II n
">o
11.2
spp
;il>ri-\
I 1.2
II
I
2° I 1.2
prnpnrlin
n
3° 11.2
spp iim-(I
I 1.2
spp
:il>ri-\
3° 3° 11.2 4° 11.2 4° 4° 4° 11.2 1° 1° 11.3
TI.2 pnipiiriin spp usi-d I I.2 TI.2 pnipiiriin TI.3 spp usi-d
II n spp TT n spp
T ;il)ri-\ I-"
rn.3 r i°n.3
spp TI.3 pnipiiriin
;il>l>ri-\ 'IT n
I
IH'li-iiiN T:ir»i- I Tl'i'iinipiisi
i- I TI-" 1 llsli k-
III
Default
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Default
Default
mottled 1.38 lieiitliic feeder; forages among rocks,
sculpin mainly on immature aquatic insect larvae,
especially mayflies, chironomid midges,
and stoneflies; larger individuals also eat
caddisflies and crayfish; crustaceans,
annelids, fishes (including fish eggs) and
plant material also may be eaten; may
take swimming prey from water column
(Scott and Crossman 1973, Becker 1983).
mountai 1.38 Feeds actively on aquatic and terrestrial
n insects. Also feeds on some fish eggs and
whitefis occasionally on fishes. Bottom-oriented
h predator (Moyle 1976), occasionally
feeds at surface (Sigler and Sigler 1987).
ninespi 1.79 Eats mainly small crustaceans and
ne aquatic insects; sometimes also fish eggs
stickleb and fry (Becker 1983).
ack
norther 1.78 Young initially eat large zooplankton and
n pike immature aquatic insects. After 7-10 days
fishes begin to enter diet and eventually
dominate. Adults feed opportunistically
on vertebrates small enough to be
engulfed. (Scott and Crossman 1973).
Sight feeder.
norther 1.27 Feed effectively at all levels and food
n plains habits are generalized. Prefer aquatic
killifish insects but also feed on plants.
Median of all in 2.14
insects
Median of all in
insects
Median of all crs
crustaceans
Montana field
guide
(http://fieldgui
de.mt.gov/detai
1_AFCNB0460
O.aspx)
Median
insects and
benthic
crustaceans
Median of all
insects
in,be
2.14
1.41
1.74
2.14
0.70
Median of
all
crustacean
s
0.90
0.48 Median of
all insects
0.05
0.80 TL1
TL1
1.41
2.14
1.00
0.10 TL1
0.44
0.20
TLl
1.00
0.10
l'ish Median all f+a
fish eating
median all
invertebrat
Fish Median all f+a
fish eating
median all
invertebrat
es
Fish Median all f+a
fish eating
median all
invertebrat
es
Fish Median all f+a
fish eating
median all
invertebrat
es
2.28
2.28
2.28
2.28
0.1
0.1
0.08
0.95
1.97 1.38 2.72
2.16
2.25
1.91
1.38
1.79
1.78
1.27
2.97
3.22
4.02
2.44
Default
norther
n
redbelly
dace
1.20 Eats mainly diatoms and filamentous
algae, also zooplankton and aquatic
insects.
TLl
TLl
1.00
0.70
Median of
all insects
2.14
0.15 Median
insects
and
benthic
crustacean
s
in,be
1.74
0.15
1.28
1.20
1.54
Default
norther 1.20 Small individuals feed primarily on
n aquatic and terrestrial insects. Adults feed
squawfi on fish, insects, insect larvae, crustaceans
sh and some plankton during spring and
summer. Fishes are the major component
Median of all in
insects
2.14
0.32
Median of
all
crustacean
s
1.41
B-167
0.08
Fish Median all
fish eating
median all
invertebrat
f+a
2.28
0.6
2.17
1.20
2.61
-------
Ki-li-ri-n Sili- Sili- T;ir»i-l I'isli I'ish pri-\ :is di-sirihi-d in \:iliiri-Si-r\i- I'isli pri-> spp 1° TI.2 TTI-" l°TI.2 1° l°TI.2 2° TI.2 2°
ii- di-siripi II) IIsli nr iiiiiiiiii-nl spi-iii-s usi-d spp 11.2 pnipuriiii spp usi-d 11.2
inn spi-iii-s ;il>l>ri-\ II n spp
I'lininiii I' ;d>ri-\
n 11:11111-
of the diet in winter.
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rainbow 1.07 In lakes, feeds mostly on bottom-
trout dwelling invertebrates (e.g., aquatic
insects, amphipods, worms, fish eggs,
sometimes small fish) and plankton. In
streams, feeds primarily on drift
organisms. May ingest aquatic vegetation
(probably for attached invertebrates),
red 1.31 Eats various small invertebrates (insects,
shiner crustaceans), plant material (digestibility
may be low), and microorganisms
(Becker 1983). In Virgin River, diet
dominated by Ceratopongidae,
Simuliidae, and Chironomidae (Greger
and Deacon 1988).
redside 1.08 Feeds mainly on aquatic and terrestrial
shiner insects; also eats molluscs, plankton, and
some small fish and fish eggs. Fry eat
zooplankton and algae.
Median of all in 2.14
insects
0.75
Median in,be 1.74
insects and
benthic
crustaceans
Median of all in 2.14
insects
1.00
0.70 Median of
planktonic
crustacean
pc
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Default
river 1.01 Mo stly a bottom feeder, browses on
carpsuc periphyton associated with submerged
ker rocks and debris, ingests various small
planktonic plants and animals,
roundta 1.20 Opportunistic; eats available aquatic and
il chub terrestrial insects, gastropods,
crustaceans, fishes, and sometimes
filamentous algae (Sublette et al. 1990).
TL1
TL1 1.00
Median of all in
insects
2.14
0.75
0.55
Median of
planktonic
crustacean
s
Median of
all
crustacean
s
pc
Default
Default
Sacram 1.12 Opportunistic; diet mainly benthic insect
ento larvae, snails, mid-water insects,
perch zooplankton, and fishes (Moyle et al.
1989). Young feed mainly on small
crustaceans, but as they grow Sacramento
perch consume more aquatic insect larvae
and pupae. Large adults feed mainly on
other fishes when available,
sailfin 1.21 Eats mainly algae, vascular plants,
molly organic detritus, and mosquito larvae
(and other small invertebrates).
TL1
TL1
1.00
TL1
TL1 1.00
0.75 Median of
all insects
0.75 Median of
all insects
11.2
II
I
2° 11.2
pnipuriiii
11
3° 11.2
spp usi-d
I 1.2
spp
:d>ri-\
11.2
II
I
3° 11.2
pnipuriiii
11
4° 11.2
spp usi-d
4°
11.2
spp
;d>ri-\
4°
11.2
IT
I
4° 11.2
pnipuriiii
11
1°
11.3
spp
r 11.3
spp usi-d
1° TI.3 1°
spp T1.3
;il>l>ri-\ IT
I
1° I 1.3
pnipuriiii
11
I'. I'li-ii i\
i- I I I "
T:ir»i-
I llsli
III
iri'i'iinipnsi
II-
Fish Median all f+a 2.28 0.25 2.18 1.07 2.33
fish eating
median all
invertebrat
es
1.74 1.31 2.27
1.41
1.41
0.10
0.25
Median of
all
bivalves
bvs
4.29
0.10
Fish Median all
fish eating
median all
invertebrat
es
f+a
2.28
0.1
2.30
1.10
1.08
1.01
2.48
1.11
1.41 0.15 Median of bvs 4.29 0.15
all
bivalves
2.14 0.25
Fish Median all f+a 2.28 0.15 2.38 1.20 2.86
fish eating
median all
invertebrat
es
1.29 1.12 1.44
2.14 0.25
1.29 1.21 1.56
B-168
-------
Ki-l'i-ri-n Sili- Sili-
ii- di-siripi II)
inn
T;ir»i-l I'isli
iisii in
spi-iii-s
imiiinii
11 11:11111-
I'isli |)n\ :is di-si rihi-d in \:iluri-Si-r\i-
i"ish pn-\ spp 1° 11.2111 i° ti.2 r rn.2 2° 11.2
I'lininii-nl spi-iii-s usi-d spp 11.2 prnpnrlin spp usi-d
;il>l>ri-\ II n
I
">o
11.2
spp
;il>ri-\
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Default
Default
Default
Default
sand 1.56 Eats various aquatic and terrestrial
shiner invertebrates (especially chironomids),
algae, and (mainly) bottom particulate
matter (Becker 1983). Winter diet mostly
chironomids larvae and mayfly and
stonefly naiads (Ohio, see Sublette et al.
1990)
sauger 1.60 Larvae eat microcrustaceans. Young eat
zooplankton, immature and adult aquatic
insects, and fish fry; adults eat small
fishes and various invertebrates (Scott
and Crossman 1973), or are almost
exclusively piscivorous (Burkhead and
Jenkins 1991). Sight feeder, adapted to
low light.
sculpin 1.29 Benthic feeder; forages among rocks,
mainly on immature aquatic insect larvae,
especially mayflies, chironomid midges,
and stoneflies; larger individuals also eat
caddisflies and crayfish; crustaceans,
annelids, fishes (including fish eggs) and
plant material also may be eaten; may
take swimming prey from water column
(Scott and Crossman 1973, Becker 1983).
1.01 Invertivore
shorthe
ad
redhors
e
smallm
outh
bass
0.86 Adults almost entirely piscivorous if
sufficient prey available
Median in,be
insects and
benthic
crustaceans
Median in,be
insects and
benthic
crustaceans
Median of all in
insects
1.74
0.75 TL1
1.74
2.14
Median of all all
invertebrates
except
bivalves
Median of all in
insects
1.48
2.14
TL1
0.36 Median of pc
planktonic
crustacean
0.70 crayfish
1.00
0.20
Default
speckle 0.71 An omnivorous benthic feeder, at times
d dace feeding on drift in mid-water or rarely at
the surface (Schreiber and Minckley
1981). The diet consists mostly of benthic
insects, also includes other invertebrates,
algae, and detritus (little or no plant
material or detritus in some areas)
(Sublette et al. 1990, Woodbury 1933,
Greger and Deacon 1988). Young feed
mainly on zooplankton.
Median of all in 2.14
insects
0.70 Median in,be
insects and
benthic
crustacean
s
11.2
II
I
2° 11.2
prnpnrlin
n
3° 11.2 3°
spp usi-d I I.2
spp
:il>ri-\
11.2
II
3° 11.2
pnipiiriin
n
4° 11.2
4°
spp IISI-(I 11.2
spp
;il>ri-\
4°
11.2
IT
I
4° 11.2
pnipiiriin
n
1°
11.3
spp
r 11 .3
spp IISI-(I
r Ti.3 r
spp 11.3
;il>l>ri-\ IT
I
1° I 1.3
pnipiiriin
n
I'. I'li-ii i\
i- I I I "
T:ir»i-
I llsli
III
iri'i'iinipiisi
ll-
1.00
0.25
1.55
1.56
2.43
1.41
0.10
Fish
Median all
fish eating
median all
invertebrat
es
f+a
2.28
0.54
2.00
1.60
3.20
1.46
0.15
Fish
Median all
fish eating
median all
invertebrat
f+a
2.28
0.15
2.06
1.29
2.66
1.48 1.01 1.49
Fish Median all f+a 2.28
fish eating
median all
invertebrat
es
1.74
0.15 TL1
TL1
1.00
0.15
0.8 2.25 0.86 1.93
1.91 0.71 1.36
B-169
-------
Ki-l'i-ri-n Sili- Sili-
ii- di-siripi II)
inn
T;ir»i-l
II sli
spi-iii-s
I'limmii
1111:11111-
l-'ish
III
I'isli |)n\ :is di-si rihi-d in \:iluri-Si-r\i-
i"ish pn-\ spp 1° 11.2111 i° ti.2 r rn.2 2° 11.2
imiimi-nl spi-iii-s usi-d spp 11.2 prupurliii spp usi-d
;il>l>ri-\ II n
">o
11.2
spp
;il>ri-\
I 1.2
II
I
2° I 1.2
pnipiiriin
n
3° 11.2
spp iim-(I
I 1.2
spp
:il>ri-\
11.2
II
I
3° 11.2
pnipiiriin
n
4° 11.2
spp IISI-(I
4°
11.2
spp
;il>ri-\
4°
n.2
ii
i
4° 11.2
pnipiiriin
n
1°
11.3
spp
r 11 .3
spp IISI-(I
rn.3 r
spp 11.3
;il>l>ri-\ IT
I
1 ° TI.3 IH'li-iiiN T:ir»i- Tl Tiiimposi
pnipiiriin i- III I llsli k-
n III
Default
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stonecat 0.77 Eats mainly bottom invertebrates (insects,
crayfish); sometimes also plant material
and fishes (Becker 1983, Scott and
Crossman 1973).
sucker 1.01 White: Larvae feed near surface on
protozoans, diatoms, small crustaceans,
and bloodworms. Adults feed
opportunistically on bottom organisms,
both plant and animal (e.g., chironomid
larvae, zooplankton, small crayfishes)
(Becker 1983, Sublette et al. 1990).
Bluehead: A bottom feeder. Scrapes
algae and other organisms from rocks
with chisel-like ridges inside each lip;
ingests fine organism-laden sediments.
May feed in stream riffles, or deeper
rocky pools; in lakes it may feed over
rocks near shore. May eat aquatic insect
larvae. Flannelmouth: Bottom feeder.
Reported to feed on diatoms, algae,
fragments of higher plants, seeds, and
benthic invertebrates (Sigler and Miller
1963; Lee et al. 1980). See Tyus and
Minckley 1988 for possible importance
of Mormon cricket as food source,
tilapia 1.41 aureus: Eats mainly phytoplankton.
mossambicus: Nonselective omnivore;
eats planktonic algae, aquatic plants,
invertebrates, and small fishes (Moyle
1976). zilli: Feeds on algae and higher
plants, invertebrates, and occasionally
eats dead or dying fish,
tui chub 1.20 Adults opportunistic. They feed on plant
material, plankton, insect larvae,
crustaceans, fish fry and fish eggs, etc.
Young feed on zooplankton. Coarse-
rakered form eats more plant material,
fme-rakered form more zooplankton.
Utah 1.01 Bottom feeder. Varied diet; feeds freely
sucker on both animal and plant organisms, at all
depths throughout the year. Grazes on
filamentous algae.
Median
insects and
benthic
crustaceans
Median of all
invertebrates
except
bivalves
in,be-
all
1.74
1.48
0.70 TL1
0.50 TL1
TL1
TL1
1.00
1.00
0.20
0.50
l'ish Median all
fish eating
median all
invertebrat
f+a
2.28
0.1
1.65 0.77 1.26
1.24 1.01 1.25
Median of all
invertebrates
except
bivalves
TL1
all
1.48
0.50 TL1
TL1
1.00
0.50
1.24 1.41 1.74
TL1
1.00
0.40 Median of pc
planktonic
crustacean
1.41
Median of all
invertebrates
except
bivalves
all
1.48
0.50 TL1
TL1
1.00
0.28 Median of in
all insects
0.50
2.14
0.28 crayfish cr 1.46
0.04
1.45 1.20 1.75
1.24 1.01 1.25
B-170
-------
Ki-l'i-ri-n Sili- Sili-
ii- di-siripi II)
inn
T;ir»i-l I'isli
iisii in
spi-iii-s
imiiinii
11 11:11111-
I'isli |)n\ :is di-si rihi-d in \:iluri-Si-r\i-
i"ish pn-\ spp 1° 11.2111 i° ti.2 r rn.2 2° 11.2
imiimi-nl spi-iii-s usi-d spp 11.2 prupurliii spp usi-d
;il>l>ri-\ II n
">o
11.2
spp
;il>ri-\
I 1.2
II
I
2° I 1.2
pnipiiriin
n
3° 11.2
spp iim-(I
I 1.2
spp
:il>ri-\
11.2
II
I
3° 11.2
pnipiiriin
n
4° 11.2
spp IISI-(I
4°
11.2
spp
;il>ri-\
4°
n.2
ii
i
4° 11.2
pnipiiriin
n
1°
11.3
spp
r 11 .3
spp IISI-(I
rn.3 r
spp 11.3
;il>l>ri-\ IT
I
1 ° TI.3 IH'li-iiiN T:ir»i- Tl Tiiimposi
pnipiiriin i- III I llsli k-
n III
Default
walleye 1.60 Adults feed opportunistically on various
fishes and larger invertebrates.
Median
insects and
benthic
crustaceans
in,be
1.74
0.50
fish
Median all
fish eating
median all
invertebrat
f+a
2.28
0.5
2.01 1.60 3.21
Default
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Default
western 1.21 Opportunistic omnivore; eats mainly
mosquit small invertebrates, often taken near
ofish water surface. Also eats small fishes and,
in the absence of abundant animal food,
algae and diatoms (Moyle 1976).
Mosquito fish are principally carnivorous,
and have strong, conical teeth and short
guts (Meffe et al. 1983, Turner and
Snelson 1984). They are reported to feed
on rotifers, snails, spiders, insect larvae,
crustaceans, algae, and fish fry, including
their own progeny (Barnickol 1941,
Minckley 1973, Meffe and Crump 1987).
Cannibalism has been documented by
several authors (Seale 1917, Krumholz
1948, Walters and Legner 1980,
Harrington and Harrington 1982). Plant
material is taken occasionally (Barnickol
1941) and may make up a significant
portion of the diet during periods of
scarcity of animal prey (Harrington and
Harrington 1982). Grubb (1972) showed
that anuran eggs from temporary ponds
were preferentially selected over those
breeding in permanent systems,
white 1.48 Eats fishes, zooplankton, aquatic insects,
bass oligochaetes, and crayfish; fishes often
dominate diet of adults; diet may vary
from place to place (Moyle 1976,
Sublette et al. 1990).
white 2.67 Eats fishes, planktonic crustaceans, and
crappie aquatic insects; small individuals eat
mostly zooplankton, fish tend to
predominate in the diet of larger
individuals, though zooplankton also
consumed (Moyle 1976)
white 1.21 A bottom feeder. Young feed mostly on
sturgeo the larvae of aquatic insects, crustaceans,
n and molluscs. A significant portion of the
Median of all in
insects
2.14
0.75
Median of
all
crustacean
s
1.41
0.25
1.96 1.21 2.37
Median of all in 2.14 0.30 Median of pc 1.41 0.05 crayfish cr 1.46 0.05
insects planktonic
crustacean
s
Median of all in 2.14 0.50 Median of pc 1.41 0.10
insects planktonic
crustacean
s
Median in,be 1.74
insects and
benthic
0.31 Median of bvs 4.29 0.09
all bivalves
Fish Median all f+a 2.28
fish eating
median all
invertebrat
es
Fish Median all f+a 2.28
fish eating
median all
invertebrat
Fish Median all f+a 2.28
fish eating
median all
0.6
0.4
2.15 1.48 3.19
2.12 2.67 5.66
0.6
2.29 1.21 2.77
B-171
-------
Ki-li-mi Sill- Sill- T;ir»i-I I isli I isli pn-> :is ili-si-rihi-il in Viliiii-Si-ni- I isli pn\ spp 1° 11.2 I I I" 1° 11.2 1° 1° 11.2 2° 11.2 2° 2° 2° 11.2 3° 11.2 3° 3° 3° 11.2 4° 11.2 4° 4° 4° 11.2 1° 1° 11.3 1° 11.3 1° l° TI.3 i:ili-ui\ T:ir»i- l l l'iiuiiposi
ii- di-siripi II) IIsli III iiiiiiiiii-nl spi-iii-s usi-il spp 11.2 pnipiiriin spp usi-d 11.2 TI.2 pniporliii spp usi-il 11.2 TI.2 pn>pi>rlii> spp usi-il 11.2 TI.2 pn>pi>rlii> TI.3 spp usi-il spp T1.3 pniporiio 111" i llsli k-
iiili spi-iii-s ;il>l>ri-\ II 11 spp II n spp IT n spp IT n spp ;il>l>ri-\ II II III
ionium I-" ;ihiv\ l" :il>ri-\ I-" ;il>ri-\ l" I-"
n n.imi-
dicl oi" laraer slur" con consists oi" fish. crustaceans
in vertebral
es
Default
Default
white
sucker
wiper
1.11
1.48
Adults feed opportunistically on bottom
organisms, both plant and animal (e.g.,
chironomid larvae, zooplankton, small
crayfishes) (Becker 1983, Sublette et al.
1990).
Adults are predatory on fishes and larger
crustaceans (Hassler 1988).
expected
common spp in
benthos
TL1
crayfish
TL1
1.00
1.46
0.50 Median of
all insects
0.20
2.14
0.30
Median of
planktonic
crustacean
s
pc
1.41
0.10 crayfish cr
1.46
0.10
Fish Median all f+a
fish eating
median all
invertebrat
2.28
1.43 1.11
1.58
0.8 2.11 1.48 3.13
Default
yellow 1.42 Larvae and young primarily zooplankton
perch feeders; older young eat mostly
invertebrates associated with bottom and
with aquatic plants; adults feed among
plants and along bottom on larger
invertebrates and small fishes (Moyle
1976).
Median
insects and
benthic
crustaceans
in,be 1.74
0.64 Median of pc
planktonic
crustacean
s
1.41
0.13 TL1
TL1 1.00
0.07
Fish Median all f+a
fish eating
median all
invertebrat
es
2.28
0.16 1.73 1.42 2.47
Saiki et
al. 1993
Saiki et
al. 1993
Saiki et
al. 1993
bluegill 1.03
largemo
uth bass
western
mosquit
ofish
site-specific: 0.23 chironomid; 0.3
microcrustacea; 0.47 amphipod
1.39 site-specific: 0.73 fish; 0.27 crayfish
1.21 site-specific: 0.89 molluscs, and insects;
0.065 chironomid; 0.045 microcrustacea
stomach
analysis
stomach
analysis
stomach
contents show
a large
terrestrial
component
amphipods am 1.22
crayfish
Median
insects and
benthic
crustaceans
1.46
in,be 1.74
0.47 Median of
planktonic
crustacean
s
0.27 Saiki
bluegill
TTFcomp.
0.89 midges
pc
1.41
BG 1.47
mg
1.90
0.30 midges mg 1.90
0.73
0.07 Median of pc 1.41
planktonic
crustacean
s
0.23
0.05
1.43 1.03 1.47
1.47 1.39 2.04
1.74 1.21 2.10
Formatio
Crow
CC-
brown
n 2012
Creek -
150
trout
CC150
Formatio
Crow
cc-
sculpin
n 2012
Creek -
150
CC150
1.38 Proportions as described in table B-10
1.29 Proportions as described in table B-10
Median of all in 2.14 0.57 midges mg 1.90 0.27 mayflies mf 2.38 0.16
insects
Median of all in 2.14 0.57 midges mg 1.90 0.27 mayflies mf 2.38 0.16
insects
2.12 1.38
2.12 1.29
2.91
2.74
B-172
-------
Ki-li-n-n
Sili-
Sik-
T;ir»i-I
ii-
di-siripi
ll)
11 sli
inn
spi-iii-s
iniiinni
n n.imi-
Formatio
Crow
i_i_-
bro\ui
n 2012
Creek -
1A
trout
1A
Formatio
Crow
CC-
sculpin
n 2012
Creek -
1A
1A
Formatio
Crow
CC-
brown
n 2012
Creek -
350
trout
CC350
Formatio
Crow
cc-
sculpin
n 2012
Creek -
350
CC350
Formatio
Crow
cc-
brown
n 2012
Creek -
3A
trout
3A
Formatio
Crow
cc-
sculpin
n 2012
Creek -
3A
3A
Formatio
Crow
cc-
brown
n 2012
Creek -
75
trout
CC75
Formatio
Crow
cc-
sculpin
n 2012
Creek -
75
CC75
Formatio
Deer
DC-
brown
n 2012
Creek
600
trout
Formatio
Deer
DC-
sculpin
n 2012
Creek
600
Formatio
Hoopes
HS
brown
n 2012
Spring -
trout
HS
Formatio
Hoopes
HS
sculpin
n 2012
Spring -
HS
Formatio
Hoopes
HS-3
brown
n 2012
Spring -
trout
HS3
Formatio
Hoopes
HS-3
sculpin
n 2012
Spring -
HS3
Ill
I'isli piv\ :is (k-siril)i'(l in VilinvSini-
i"ish |)iv\ s|>|> i° 11.2111 i° n.2 r rn.2 2° 11.2
imiimi-nl spicks usi-il spp 11.2 pnipiiriiii spp usi-d
ill>l>IY\ II 11
I
2° 2° 2° 11.2 3° 11.2 3° 3° 3° 11.2 4° 11.2 4° 4° 4° 11.2 1° 1° 11.3
TI.2 I I.2 pnipiiriiii spp usi-il I I.2 TI.2 pnipiiriiii spp usi-il I I.2 TI.2 pnipiiriiii TI.3 spp usi-il
n spp TT n spp
spp II
;il)iv\ I-"
ii
spp II
:il>ri-\ I-"
spp II
;il>ri-\ l"
rn.3 r i°n.3
spp 11.3 priipnrlin
;il>l>ri-\ IT n
I
KITiiliv T:ir»i- lll'iiimposi
III 1 fish ii-
III
1.38 Proportions as described in table Li-10
1.29 Proportions as described in table B-10
1.38 Proportions as described in table B-10
1.29 Proportions as described in table B-10
1.38 Proportions as described in table B-10
1.29 Proportions as described in table B-10
1.38
1.29
1.38
1.29
1.38
1.29
1.38
1.29
Proportions as described in table B-10
Proportions as described in table B-10
Proportions as described in table B-10
Proportions as described in table B-10
Proportions as described in table B-10
Proportions as described in table B-10
Proportions as described in table B-10
Proportions as described in table B-10
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all bvs
bivalves
Median of all bvs
bivalves
Median of all crs
crustaceans
Median of all crs
crustaceans
2.14 0.79 midges mg 1.90 0.09 mayflies mf 2.38 0.12
2.14 0.79 midges mg 1.90 0.09 mayflies mf 2.38 0.12
2.14 o.:
2.14 o.:
1.41 0.40
1.41 0.40
midges mg 1.90 0.07 mayflies mf 2.38 0.13
midges mg 1.90 0.07 mayflies mf 2.38 0.13
2.14 0.85 midges mg 1.90 0.05 mayflies mf 2.38 0.10
2.14 0.85 midges mg 1.90 0.05 mayflies mf 2.38 0.10
2.14 0.49 midges mg 1.90 0.38
2.14 0.49 midges mg 1.90 0.38
2.14 0.44 midges mg 1.90 0.21
2.14 0.44 midges mg 1.90 0.21
4.29 0.44 midges mg 1.90 0.32
4.29 0.44 midges mg 1.90 0.32
mayflies mf 2.38 0.13
mayflies mf 2.38 0.13
mayflies
mayflies
mf
mf
blackwor bw
ms
blackwor bw
ms
Median of in
all insects
Median of in
all insects
2.14 0.33
2.14 0.33
2.38 0.35
2.38 0.35
1.29 0.24
1.29 0.24
mayflies mf 2.38 0.27
mayflies mf 2.38 0.27
2.15 1.38
2.15 1.29
2.16 1.38
2.16 1.29
2.15 1.38
2.15 1.29
2.08 1.38
2.08 1.29
2.18
2.18
2.81
1.38
1.29
1.38
2.81 1.29
1.91 1.38
1.91 1.29
2.96
2.78
2.97
2.79
2.97
2.78
2.87
2.69
3.00
2.81
3.86
3.63
2.63
2.47
B-173
-------
Ki-li-mi Sili-
ii- di-siripl
inn
Sili- T:ir»i-I I'isli
II) fish' III
spi-iii-s
imiiinii
11 11:11111-
I'isli |)n\ :is di-si rihi-d in \:iliiri-Si-r\i-
i-'ish pn-\ spp 1° 11.2111 i° ti.2 r rn.2 2° 11.2
imiimi-nl spi-iii-s usi-d spp 11.2 pnipiiriio spp usi-d
;il>l>ri-\ II 11
I
2° 2° 2° 11.2 3° 11.2 3° 3° 3° 11.2 4° 11.2 4° 4° 4° 11.2 1° 1° 11.3
TI.2 I I.2 pnipuriiii spp usi-d I I.2 TI.2 pnipiiriin spp usi-d I I.2 TI.2 pnipiiriin TI.3 spp usi-d
n spp TT n spp
spp II
;il)iv\ I-"
ii
spp II
:il>ri-\ I-'
spp II
;il>ri-\ I-'
rn.3 r i°n.3
spp TI.3 pniporiid
;il)l)n-\ 'IT n
I
IH'li-iiiN 'l':n«i- I ri'i'iiiiiposi
i- I TI-" 1 llsli k-
III
r'onnalio
n 2012
Fonnatio
n 2012
Fonnatio
n 2012
Fonnatio
n 2012
Fonnatio
n 2012
Fonnatio
n 2012
Sage
Creek -
LSV2C
Sage
Creek -
LSV2C
Sage
Creek -
LSV4
Sage
Creek -
LSV4
South
Fork
Tincup
Cr.
South
Fork
Tincup
Cr.
LSV- brown
2C trout
LSV- sculpin
2C
LSV-
4
brown
trout
LSV- sculpin
4
SFTC brown
-1 trout
SFTC sculpin
-1
1.38 Proportions as described in table Li-10
1.29 Proportions as described in table B-10
1.38 Proportions as described in table B-10
1.29 Proportions as described in table B-10
1.38 Proportions as described in table B-10
1.29 Proportions as described in table B-10
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
Median of all in
insects
2.14 0.57 midges mg 1.90 0.12 mayilies ml" 2.38 0.31
2.14 0.57 midges mg 1.90 0.12 mayflies mf 2.38 0.31
2.14 0.53
2.14 0.53
2.14 0.93
2.14 0.93
midges mg 1.90 0.34
midges mg 1.90 0.34
mayflies mf 2.38 0.13
mayflies mf 2.38 0.13
Median of bvs 4.29 0.03 mayflies mf 2.38 0.04
all bivalves
Median of bvs
all bivalves
4.29 0.03 mayflies mf 2.38 0.04
2.19 1.38
2.19 1.29
2.09 1.38
2.09 1.29
2.22 1.38
2.22 1.29
3.01
2.83
2.70
3.05
B-174
-------
Table B-9. Calculation of site-specific invertebrate proportions using invertebrate counts in Formation 2012
Ol'tlrl
< Jrllll-
Ihiliilnl I'liiHlinii liilri'iiii Sliviiin SI- I iiHiip ( i vrk
ill
l!cki\i I ii-diim
( i'oh ( ivrk
nr
(Mil
Ephemeropt
Atenella
CN
CG
era
margarita
Ephemeropt
Baetis spp.
sw
CG
era
Ephemeropt
Centroptilum
sw
CG
era
conturbatum
Ephemeropt
Cinygmula
CN
sc
era
spp.
Ephemeropt
Diphetor
SW
CG
era
hageni
Ephemeropt
Drunella
CN
P
era
coloradensis
Ephemeropt
Drunella
CN
P
era
grandis
Ephemeropt
Epeorus
CN
SC
era
longimanus
Ephemeropt
Ephemerella
CN
CG
era
dorothea
infrequens
Ephemeropt
Ephemerella
CN
CG
era
aurivillii
Ephemeropt
Paraleptophle
SW
CG
era
bia spp.
Ephemeropt
Tricorythodes
CN
CG
era
minutus
Plecoptera
Hesperoperla
CN
P
pacifica
Plecoptera
Isoperla sp.
CN
P
Plecoptera
Malenka sp.
CN/SP
SH
Plecoptera
Pteronarcys
CN/SP
SH
sp.
Plecoptera
Skwala sp.
CN
P
Plecoptera
Sweltsa sp. p
CN
P
Trichoptera
Agapetus sp.
CN
SC
Trichoptera
Arctopsyche
CN
P
sp.
Trichoptera
Brachycentrus
CN
F
sp.
Trichoptera
Cheumatopsy
CN
F
che sp.
Trichoptera
Dicosmoecus
BU
SH
sp.
Trichoptera
Dolophilodes
CN
F
•si- I ( I
( ( "5
< ( 1511
< < .550
I i x iil iii
ii
Dull' K 2') 2IMI" '>'>200 ') 2 2 .i 200S '>1200 S 24 200 •> .i 200 ') I 200 S 2.5 200 ') 4 200
X (i ~ (i ~ S (i ~ s
21
10
3
7
12
12
33
21
56
14
5
9
11
25
14
4
4
85
7
16
18
29
89
11
11
27
90
14
35
38
2
61
7 7
3 4 7
2
13
l)i'i'i*( reck
llllll|ll"> *S|l|-ill>i
S;mr ( ivrk
('rim ( reck
IX (.1111
IIS
•)" 200 S 2" 200 ')X 200X ')X200 X 24 200"
(i ~ (i
253
2
1
1
76
14
67
76
11
I is.?
I S\ 2(
I s\ 4
( ( I \
< ( ,5\
'> 4 200 •) (, 2000
X
56
X 2X 20 '> 5 200X ') X 200 X 2X 20 '> 5 200 ') 5 200 •) I 200 X 25 20 ') (. 200 •) 4 200 X 2(. 20
0" (• 0" X (i (i 0" X (i 0"
249
316
27
53
46
57
32
1
3
62
56
•) ~ 200
X
61
I nl:i
I
5
2041
1
16
30
29
38
12
25
11
21
14
13
62
30
35
14
13
7
20
14
2
23
13
17
33
65
34
153
23
29
1
29
20
73
11
27
13
61
3
15
18
25
12
75
25
217
46
212
24
37
77
2
191
635
21
7
28
B-175
-------
Orilrr
< Jrllll-
ILiliilnl
l!ih;i\ i
Ml
liiiHliiin
:il
1 llllTllll
IT
SIIVlllll
1 oi'iiliu
SI- 1 iiu ii|) ( irrk
SI 1(1
< < "5
( row ( ivrk
< '< 1511
< < .550
(ir<>ii|iN
II
Ifcilr
X 2') 2IHI" ')') 2IHI
S
') 2 21 III
(•
S 2.? 21II1
').? 2IHIS
•) 1 200 S 24 200
(.
').? 200
s
•) 1 200
(•
S 2.? 200
') 4 200
S
sp.
Trichoptera
Glossoma sp.
CN
SC
0
Trichoptera
Helicopsyche
sp.
Hesperophyla
x sp.
Hydropsyche
sp.
Hydroptila sp.
CN
sc
3
3
5 4
5
93
Trichoptera
Trichoptera
CN
CN
SH
F
5
4
5
47
50
23
29 17
11
74
97
41
Trichoptera
CN
SC
6
8
9
1
1
Trichoptera
Trichoptera
Lepidostoma
spp.
Micrasema sp.
SP/CB
CN
SH
SH
1
1
1 3
8
7
9
6 8
65 1
18
14
67
6
Trichoptera
Neothremma
sp.
Oecetis
disjuncta
Onocosmoecu
s sp.
Oligophlebod
es sp.
Parapsyche
sp.
Psychoglypha
sp.
Rhyacophila
spp.
Wormaldia
spp.
Ametor sp.
CN
SC
0
Trichoptera
Trichoptera
Trichoptera
Trichoptera
CN
CB
CN
CN
P
SH
SC
P
8
1
1
1
2
1
11
16
5
2
3
Trichoptera
SP/CB
CG
1
3
Trichoptera
Trichoptera
Coleoptera
CN
CN
sw
P
F
P
0
3
5
7 3
3
4
5
5
9 17
1 8
16
15
3
2
5
5
9
6
Coleoptera
Brychius sp.
CB
SC
7
2
1
3
Coleoptera
Cleptelmis sp.
CN
CG/SC
4
3 26
4
Coleoptera
Dubiraphia sp.
CN
CG/SC
4
3
Coleoptera
Coleoptera
Heterlimnius
corpulentus
Optioservus
quadrimaculat
us
Oreodytes sp.
CN/BU
CN
CG/SC
CG/SC
4
4
97 267
43
109
68
40 205
153
78
162
167
Coleoptera
SW/DV
P
5
6
1
Coleoptera
Paracymus sp.
CN
P/OM
5
1
Coleoptera
Megaloptera
Zaitzevia
paravula
Sialis sp.
CN/BU
BU/CB
CG/SC
P
4
4
170 57
1
5
4
1
3
1 1
1
7
23
5
18
I)rrl"< Irrk
ll(iii|H"> S|iiiim
S;mr ( I rrk
( Voh ( I rrk
IX 01 HI
IIS
IIS.?
I S\2<
I S\ 4
( ( I \
«> ~ 200 S 2" 200 ') X 20IS ') S 201 X 24 200"
(. " (•
•) 4 201 ') (. 20110 S 2X 20 ') 5 20IS ') X 201 X 2X 20 •> 5 201 ') 5 201 ') I 201 X 25 20 •> 0 201 ') 4 201 X 20 20
S II" 0 II" S 0 0 II" S 0 II"
I
I
•) " 21III
S
1 14
16
16
7
23
30
2
83
32
5
28
12
11
3
21
48
13
9
33
16
10
18
2
14
9
132
4
11
151
53
76
63
1
27 153
19 81
91 29 105 79
2
13 4 2
3 36
74 246
16 11
69
83
151
11
4
214
70
1012
39
141
273
4
17
1
13
32
3
236
77
1
16
6 46
3
67
129
13
2556
7
1
366
B-176
-------
I
I
9
5
1
37
119
20
13
8
3
4
74
29
4
3
11
1
760
27
2168
1
2
405
69
174
10
1
6
288
I llllTllll
IT
Shr:im SI- I iiHiip ( ivrk
( row ( ink
l)rrl"( IV rk
ll(iii|H"> S|iiinn
S;mr ( I rrk
I ¦ itiilin S||(| (("5 ( '(150 ((.>50 l)( 000 IIS
II
l):ilr K 2') 2110" ')')2IHI *> 2 200 S 2.? 200 ').5 200X ') I 200 S 24 200 ').? 200 ') I 200 S 2.? 200 4 4 200 ')" 200 S 2" 200 ') S 200S ') S 200 S 24 200"
S (i " (i " S (i " S (i " (,
IIS.?
I S\2(
') 4 200 ') (• 2000 S 2X 20 ') 5 200S ') S 200 S 2X 20 ') 5 200
S 0" (i 0" S
1
10
19
13
18 78
188
15
2
5
7
195
30
3
173
26
143
2
6
2
49
17
99 143
1
17
1
102
10 30
33
15
3
151
19
92
72
2
52
124
25
101 5
5 2
57 27
13 21
3
23 83
38
24
20
34
12
25
2
43
24
91
19
6
114
55
14
32
B-177
-------
Onlci
< Jrllll-
ILiliilnl
l!ih;i\ i
¦ ¦I-
I'liiHlinii
:il
1 rrllill!!
liilcriin SMviini
IT
1 iii'iiliu
SI' 1 illl'lip (
si 1(1
I'l'l'k
< < "5
(
I'llW ( I'l'l'k
< '< 150
< < ,?5M
l)rrl'( I'l'l'k
IX 6MM
lis
1 Innprv
Spriim
lis.?
SilHi- <
1 S\2<
I'l'l'k
1 S\ 4
< ( 1 \
< rim
< I'l'l'k
< < S\
1 ul;i
1
( H'lllip-
II
Ifcilr
X 2') 2MM" ')') 2IHI
s
') 2 2
-------
Table B-10. Summary of Formation 2012 invertebrate data.
l'livlum
Subphylum
Class
Subclass
Inlraclass
Superorder
()rdcr
Lookup II)
Common name
SI
1 CI
( ( "
(
Counl
l'roporlion
Counl
l'roporlion
Connl
Arthropoda
Insecta
Pterygota
Ephemeropteroidea
Ephemeroptera
Ephemeroptera
Mayflies
36
0.04
185
0.12
231
Arthropoda
Insecta
Pterygota
Exopterygota
Plecoptera
Plecoptera
Stoneflies
107
0.12
85
0.06
40
Arthropoda
Insecta
Amphiesmenoptera
Trichoptera
Trichoptera
Caddisflies
30
0.03
268
0.18
283
Arthropoda
Insecta
Pterygota
Neoptera
Endopterygota
Coleoptera
Coleoptera
Beetles
631
0.72
234
0.15
408
Alderflies,
dobsonflies and
Arthropoda
Insecta
Neoptera
Megaloptera
Megaloptera
fishflies
1
0.00
4
0.00
1
Dragonflies and
Arthropoda
Insecta
Pterygota
Odonatoptera
Odonata
Odonata
damselflies
True bugs (cicadas,
aphids,
planthoppers,
leafhoppers, shield
Arthropoda
Insecta
Neoptera
Paraneoptera
Hemiptera
Hemiptera
bugs)
5
0.01
Arthropoda
Insecta
Panorpida
Diptera
Diptera
True flies
42
0.05
143
0.09
103
Chironomidae
Chironomidae
Arthropoda
Insecta
(family)
(family)
Midges
556
0.37
385
Hirudinea
Annelida
Clitellata
Hirudinea
(class)
Leeches
1
Springtails (not
Arthropoda
Entognatha
Collembola
Collembola
insects!)
2
Oligochaeta
Annelida
Clitellata
Oligochaeta
(class)
Worms
5
0.01
24
0.02
17
Bivalvia
Mollusca
Bivalvia
(class)
Clams
2
0.00
6
0.00
2
Gastropoda
Mollusca
Gastropoda
(class)
Snails and slugs
21
0.02
7
0.00
Arthropoda
Crustacea
Malacostraca
Amphipoda
Amphipoda
Crustaceans
Arthropoda
Crustacea
Ostracoda
Ostracoda
Sea shrimp
1
Platyhelminthes
Turbellaria
Tricladida
Tricladida
Flatworms
Acari
Arthropoda
Chelicerata
Arachnida
Acari
(subclass)
Mites and ticks
4
0.00
7
Total
880
1516
1481
Midge
0.00
0.37
Mayfly
0.04
0.12
Other insects
0.93
0.48
Molluscs
0.03
0.01
Crustaceans
0.00
0.00
Annelids
0.01
0.02
Other
0.00
0.00
50 CC350 IX'600 IIS
roporlion Counl Proportion Counl Proportion Counl l'roporlion Counl
192
18
539
457
0.13
0.01
0.36
0.30
444
195
229
76
0.34
0.15
0.18
0.06
115
59
34
18
IIS3 I.SV2C I.SY4 CC1A CC3A
l'roporlion Counl l'roporlion Connl l'roporlion Connl l'roporlion Connl Proportion
0.11
0.06
0.03
0.02
325
20
230
65
0.24
0.01
0.17
0.05
421
26
324
327
0.28
0.02
0.21
0.22
56
30
135
29
0.13
0.07
0.30
0.07
168
11
325
507
0.12
0.01
0.23
0.36
136
22
623
311
0.00
145
108
0.10
0.07
55
272
0.04
0.21
29
241
0.03
0.24
89
106
0.07
0.08
85
154
0.06
0.10
36
149
0.08
0.33
221
127
0.16
0.09
166
70
16
11
4
15
0.01
0.01
0.00
0.01
27
0.02
0.01
0.00
178
9
319
2
0.18
0.01
0.32
0.00
3
2
16
19
471
0.00
0.00
0.01
0.01
0.35
43
12
54
21
51
0.03
0.01
0.04
0.01
0.03
0.02
0.00
0.00
9
4
21
2
1
0.01
0.00
0.01
0.00
0.00
0.00
75
24
29
1505
1307
1004
1346
1518
445
1402
1468
0.26
0.16
0.56
0.00
0.00
0.01
0.01
0.07
0.13
0.77
0.01
0.00
0.01
0.01
0.21
0.34
0.42
0.01
0.00
0.02
0.00
0.24
0.11
0.14
0.33
0.00
0.18
0.00
0.08
0.24
0.30
0.01
0.36
0.00
0.00
0.10
0.28
0.50
0.04
0.05
0.03
0.00
0.33
0.13
0.52
0.00
0.00
0.02
0.00
0.09
0.12
0.76
0.02
0.00
0.01
0.00
0.05
0.09
0.77
0.04
0.00
0.05
0.00
B-179
-------
Total
1.00
1.00
Take the top 3
that are above
1%
Insects
Molluscs
Mayfly
0.93 Insects
0.03 Midge
0.04 Mayfly
1.00
0.50 Insects
0.38 Midge
0.13 Mayfly
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.58 Insects
0.27 Midge
0.16 Mayfly
1.00
0.79 Insects
0.07 Midge
0.13 Mayfly
1.00
0.44 Midge
0.21 Molluscs
Worms
and
0.35 leeches
1.00
0.32 Insects
0.44 Crustaceans
0.24 Mayfly
1.00
0.33 Insects
0.40 Midge
0.27 Mayfly
1.00
0.57 Insects
0.12 Midge
0.31 Mayfly
1.00
0.53 Insects
0.34 Midge
0.13 Mayfly
1.00
0.78 Insects
0.09 Midge
0.12 Mayfly
1.00
0.85
0.05
0.10
1.00
B-180
-------
APPENDIX C: Summaries of Chronic Studies
Considered for Criteria Derivation
White sturgeon C-2
Sacramento splittail C-12
Fathead minnow C-15
Flannelmouth & razorback suckers C-22
Northern pike C-24
Chinook salmon C-27
Rainbow trout & brook trout C-32
Cutthroat trout C-51
Dolly Varden C-65
Brown trout C-68
Desert pupfish C-86
Eastern and western mosquitofish C-103
Striped bass C-105
Bluegill sunfish C-106
Largemouth bass C-147
See Appendix E for descriptions of other, less conclusive studies with:
Rainbow trout
Fathead minnow
Sacramento splittail
White sucker
See Appendix E for descriptions of invertebrate studies.
C-l
-------
Tashjian, D.H., S.J. The, A. Sogomoyan and S.S.O. Hung. 2006. Bioaccumulation and chronic toxicity
of dietary L-selenomethionine in juvenile white sturgeon (Acipenser transmontanus). Aquatic
T oxicol .79:401-409.
Test Organism:
Exposure Route:
White sturgeon (Acipenser trans montanus)
Dietary only
Seleno-L-methionine was added to an artificial diet consisting of vitamin-free
casein, wheat gluten, egg albumin, dextrin, vitamin mix, BTM-mineral mix,
cellulose, corn oil, cod liver oil, choline chloride and santoquin; the measured
dietary concentrations were 0.4, 9.6, 20.5, 41.7, 89.8, 191.1 mg Se/kg dw.
Test Duration:
8 weeks
Study Design: 25 juvenile white sturgeon were placed in each of 24 90-L tanks. Treatments
were randomly assigned to the 24 tanks resulting in 4 replicates per dietary
treatment. Four fish from each tank were sampled after 0, 4 and 8 weeks for
weight, length, liver weight, condition factors, hepatosomatic indices, hemocrit,
histopathology, and selenium measurement in liver, kidney, muscle and gill
tissues. 8 fish after 0 and 8 weeks were sampled for whole body selenium
measurement.
Effects Data: Sturgeon survival did not differ significantly among treatment groups after the 8-
week exposure with a mean survival rate of 99 across all groups. Fish fed 41.7 to
191.1 mg Se/kg dw exhibited significant declines in body weight (see table). All
other endpoints measured were as sensitive or less sensitive to selenium in the
diet as body weight.
Mean (SE) white sturgeon moisture, lipid and whole body Se after 8-week exposure
Treatment
group
Moisture, % ww
Lipid, % ww
muscle Se, mg/kg dw
whole body Se, mg/kg dw
0.4
76.8 (0.5) b
9.5 (4) abc
8.2 (0.6) e
5.2 (0.4) c
9.6
77.0 (0.7) b
9.5 (0.9) abc
17.2 (0.7) d
11.8 (0.9) b
20.5
76.8 (0.3) b
10.1 (0.4) ab
22.9 (1.5) c
14.7 (0.8) b
41.7
77.3 (0.5) b
9.6 (0.7) abc
36.8 (1.8) b
22.5 (1.4) a
89.8
78.5 (0.3) ab
7.6 (0.4) bed
52.9 (3.2) a
34.4 (2.3) a
191.1
80.0 (0.4) a
6.1 (0.4) cd
54.8 (2.8) a
27.5 (4.4) a
C-2
-------
Mean (SE) white sturgeon body weight increase after 8-week exposure
Treatment
group
Body weight
increase (%)
muscle Se, mg/kg dw
whole body Se, mg/kg dw
0.4
282.9 (4.6) a
8.2 (0.6) e
5.2 (0.4) c
9.6
285.5 (9.9) a
17.2 (0.7) d
11.8 (0.9) b
20.5
277.7 (6.1) a
22.9 (1.5) c
14.7 (0.8) b
41.7
191.0 (12.6) b
36.8 (1.8) b
22.5 (1.4) a
89.8
106.5 (5.8) c
52.9 (3.2) a
34.4 (2.3) a
191.1
28.6 (3.6) d
54.8 (2.8) a
27.5 (4.4) a
Letters denote statistical groupings among treatments within each exposure period (p<0.05).
Chronic Value: Using the logistic equation with a log transformation of the exposure
concentrations (TRAP program), the ECi0 and EC2o values for reduction in body
weight are 15.08 and 17.82 mg Se/kg dw whole body and 27.76 and 32.53 mg
Se/kg dw muscle tissue.
C-3
-------
White sturgeon (Tashjian et al 2006)
350
300
250
200
150
100
50
0
,9
.8
Log([Se] muscle, mg/kg dw)
Parameter Summary (Logistic Equation Regression Analysis)
Parameter
Guess
FinalEst
Std Error
95%LCL
95%UCL
LogXSO
1.6006
1.6303
0.0314
1.5304
1.7301
S
1.6574
2.938
0.925
-0.005
5.882
Y0
284.2
286,3
18 9
226.1
346.5
Effect Concentration Summary
% Effect
Xp Est
95%LCL
95%UCL
50.0
42.69
33.92
53.72
20.0
32.53
21.17
49.99
10.0
27.76
15.63
49.30
5.0
23.98
11.75
48.93
06/19/2009 10 32 MED Toxic Response Analysis Model, Version 1 03
C-4
-------
White sturgeon (Tashjian et al 2006)
350
300
250
1
® 200
* 150
E 100
1.5
1.6
1.2
1.3
1.4
.8
,7
.8
.9
1.0
1.1
Log([Se] whole body, mg/kg dw)
Parameter Summary (Logistic Equation Regression Analysis)
Parameter
Guess
FinalEst
Std Error
95%LCL
95%UCL
LogX50
1.3403
1.3750
0.0643
1.1702
1.5797
S
2.283
2.794
1.908
-3.277
8.865
Y0
284.2
294.2
45.0
151.0
437.3
Effect Concentration Summary
% Effect
Xp Est
95%LCL
95%UCL
50.0
23.71
14.80
37.99
20.0
17.820
6.890
46.090
10.0
15.078
4,160
54.655
5.0
12.926
2.587
64.584
06/19/2Q09 10:42 MED Toxic Response Analysis Modei, Version 1.03
C-5
-------
Linville, R.G. 2006. Effects of Excess Selenium on the Health and Reproduction of White Sturgeon
(Acipenser transmontanus): Implications for San Francisco Bay-Delta. Dissertation. University of
California at Davis.
Test Organism: White Sturgeon (Acipenser trans montanus)
Exposure Route: Dietary only
Selenium was added to the treatment in the form of selenized yeast. Selenized
yeast (2.2%; Selenomax®, Ambi Inc.) was added to a commercial salmonid diet
and pelleted with fish oil. For the control diet, the selenized yeast mixture
contained 1.3% selenized yeast and 98.7 tortula yeast. Only selenized yeast was
added to the treatment diet. After pelleting, the diet was allowed to air dry on
drying racks.
Test Duration: Females were fed 0.3% body weight/day the experimental diet for 6 months.
Study Design: 16 adult female white sturgeon (approximately 5 years old, mean weight and fork
length: 22.71 kg and 134.59 cm) were exposed in a freshwater flow through
system to either the control diet (8 females in one tank fed 1.4 mg/kg Se) or
treatment (8 females in a separate tank fed 34 mg/kg Se, Se from selenized yeast)
for 6 months. After the 6 month dietary exposure, females were induced to spawn
and fertilized with non-exposed male milt. Eggs were hatched in jars keeping
eggs from each female separate. For each progeny cohort, 3000 larvae were
randomly distributed into 3 reps for stage 40 (intestinal portion is void of yolk
material, but stomach is not differentiated and is filled with yolk) sampling and 3
reps for stage 45 (yolk sac absorbed, start exogenous feeding) sampling. Se and
biological measurements were made in each replicate.
Effects Data: No Se effects were observed for length or weight of larvae. Effects were
determined for edema (Table 1), skeletal deformities (Table 2) and larval survival
(Table 4). Because the mortalities for each cohort were recorded up to the time
the sample was collected for abnormalities, a combined effects variable can be
the total proportion of hatched larvae which were both alive and without any
abnormalities at stage 45 (Table 4). This was calculated as PS(l-PA), where PS
is the proportion survival in the test chambers prior to sampling and PA is the
proportion of the sample of surviving larvae with abnormalities. Binomial
confidence limits are included in Table 4 for percent survival and percent
abnormalities for each cohort to visualize significant differences among data
points and between data points and fitted curves. Such confidence limits cannot
be directly calculated for the combined effects variable, for which confidence
limits were estimated by combining the lower and upper confidence limits of the
individual effects variables using the same equation as above (this slightly
overestimates the confidence limit range).
In Table 4, only cohort T2 is significantly different from the controls, based both
on larval survival and abnormalities. That this selenium effect is also supported
by the microinjection studies of Linville, which showed large abnormality
frequencies for egg Se injected with >15 mg/kg, but little or no effect at lower
concentrations (this is only supporting information because direct injection of a
C-6
-------
specific form of Se is not a complete surrogate for setting effect concentrations
for maternally transferred Se). For cohort T3, the data for abnormalities indicate
some effects, but cannot be considered a definite effect concentration due to a
combination of considerations - overlapping confidence limits with controls, no
increase in mortality, limited information on within-cohort variability, and, based
on egg concentrations, no effects for cohort T1 at a higher concentration.
ECio Calculations: The combined effects variable is plotted versus Se concentration in the eggs in
Figure 1. With only one definite partial effect, TRAP cannot be used to estimate
a curve. Instead, the interpolation protocol is applied between the last two points
based on specifying the highest no-effect concentration (HNOEC), 11.0 mg/kg,
to be the EC0 in the interpolation equation and specifying the upper control
plateau (Y0 in TRAP) to be average survival of the lower four points. The
resultant TRAP slope is 3.0 and the interpolated ECi0 is 15.6 mg/kg.
The egg ECio of 15.6 mg/kg is slightly lower than the value of 16.3 mg/kg in the
previous draft (Figure 3). The lower value was due to the inclusion of larval
survival with abnormalities in the endpoint and using interpolation between the
last two points rather than a TRAP model of the dataset.
Linville (2006) similarly calculated a 10% effective dose (ED10) of the combined
skeletal and edema data of 15.3 mg Se egg/kg dw using a logit regression.
Linville (2006) also noted statistically significant differences using a Tukey
Honest Significant Difference (HSD) test between Se and control treatments with
respect to both the incidence of Stage 45 skeletal and total deformities,
respectively, for the maternal transfer study. These author-reported results
support the evidence of an effect of selenium in white sturgeon similar to the
ECio of 15.6 mg Se/kg egg dw interpolated by TRAP.
The combined effects variable is plotted versus Se concentration in muscle in
Figure 2. Unlike for the egg concentration, the muscle concentration for cohort
T3, with a small but not significant effect, is greater than that for cohort Tl, with
no effect, so that TRAP can be used to estimate a curve, although only barely so.
This analysis was by tolerance distribution analysis with the log-triangular
model. The resultant TRAP estimates are 100% for the control value and 8.8 for
the EC0 (about 11% below the Tl concentration); the standard deviation is 0.14
log units, equivalent to a slope of 3.7. The ECio estimate is 11.9 mg/kg.
Chronic Value: The chronic value for combined deformities and larval survival using egg Se is
an ECio of 15.6 mg egg/kg dw. The chronic value for this same endpoint in
muscle tissue is an ECi0 of 11.9 mg muscle/kg dw.
C-7
-------
Table 1. Edema deformities.
Control
Treatment
Larval Se
Edema
Larval Se
Cohort
Edema (%)
(mg/kg dw)
Cohort
(%)
(mg/kg dw)
C3
0.00 (1)
2.43
T1
0.00(1)
11.6
Stage 36
C4
0.00 (1)
1.69
T2
0.00(1)
18.4
C5
0.00 (1)
2.67
T3
6.67(1)
7.75
Stage 40
C4
0.00 (3)
1.8
T1
0.00 (3)
11.6
C5
0.00 (3)
2.88
T2
4.44 ±2.22 (3)
20.4
T3
1.67 ± 1.67 (2)
7.22
Stage 45
C4
0.00 (3)
1.96
T1
0.00 (3)
12
C5
0.00 (3)
2.59
T2
15.56 ± 1.11 (3)
19.4
T3
0.00 (2)
7.61
Table 2. Skeletal deformities.
Control
Treatment
Larval Se
Larval Se
Cohort
Skeletal (%)
(mg/kg dw)
Cohort
Skeletal (%)
(mg/kg dw)
C3
0.00 (1)
2.43
T1
0.00(1)
11.6
Stage 36
C4
0.00 (1)
1.69
T2
0.00(1)
18.4
C5
0.00 (1)
2.67
T3
10.00(1)
7.75
Stage 40
C4
1.11 ± 1.11 (3)
1.8
T1
0.00 (3)
11.6
C5
1.11 ± 1.11 (3)
2.88
T2
14.44 ± 1.11 (3)
20.4
T3
8.33 ± 1.67 (2)
7.22
Stage 45
C4
0.00 (3)
1.96
T1
0.00 (3)
12
C5
0.00 (3)
2.59
T2
21.11 ± 1.11 (3)
19.4
T3
13.33 ±3.33 (2)
7.61
C-8
-------
Table 3. Combined edema and skeletal deformities.
Control
Cohort
Affected (%)
Egg Se
(mg/kg)
Larval Se
(mg/kg)
Treatment
Abnormal
Cohort (%)
Egg Se
(mg/kg)
Larval Se
(mg/kg)
Stage 36
C3
0.00 (1)
2.46
2.43
T1
0.00 (1)
11
11.6
C4
0.00 (1)
1.61
1.69
T2
0.00 (1)
20.5
18.4
C5
0.00 (1)
2.68
2.67
T3
16.67 (1)
7.61
7.75
1.11± 1.11
Stage 40
C4
(3)
1.61
1.8
T1
0.00 (3)
11
11.6
1.11± 1.11
18.89 ± 1.11
C5
(3)
2.68
2.88
T2
(3)
20.5
20.4
T3
10.00 ± 0 (2)
7.61
7.22
Stage 45
C4
0.00 (3)
1.61
1.96
T1
0.00 (3)
11
12
27.78 ±2.94
C5
0.00 (3)
2.68
2.59
T2
(3)
20.5
19.4
13.33 ±3.33
T3
(2)
7.61
7.61
Table 4. Stage 45 data combined abnormalities and percent larval survival.
Cohort
Egg Se
(mg/kg)
Muscle Se
(mg/kg)
% Survival
(95% Binomial CL)
% Abnormal
(95% Binomial CL)
[# Abnormal]1
% Alive & w/o
Abnormalities
(95% Binomial CL)
C4
1.61
1.22
99.7
(98.9-99.9)
0.0
(0.0-4.2)
[0,0,0]
99.7
(95.7-99.9)
C5
2.68
1.48
99.7
(98.9-99.9)
0.0
(0.0-4.2)
[0,0,0]
99.7
(95.7-99.9)
T3
7.61
11.1
>99.6
(98.7-99.8)
13.3
(3.7-24.6)
[3,5]
86.4
(74.4-96.3)
T1
11
9.93
>99.6
(98.7-99.8)
0.0
(0.0-4.2)
[0,0,0]
99.7
(95.7-99.9)
T2
20.5
15.3
91.6
(90.1-92.8)
27.8
(18.8-38.3)
[7,8,10]
66.2
(55.6-75.4)
Bracketed numbers denote abnorma
larvae in each of the 2-3 replicates of n=30.
C-9
-------
(/)
£ 100 -
05
E
o
c
_Q
<
80 ¦
60 ¦
T*\
I
°3
40 ¦
20 ¦
0
CL
2 3 5 10
mg Se/kg egg (dw)
20 30
Figure 1. White sturgeon percent alive and without abnormalities as a function of the logarithm of
selenium concentrations in eggs. TRAP is used to interpolate between the last two points; EC10 = 15.6
mg Se/kg egg dw.
(/)
g 100 +
"to
E
_Q
<
+->
D
O
o3
2 3 5 10
mg Se/kg muscle (dw)
20 30
Figure 2. White sturgeon percent alive and without abnormalities as a function of the logarithm of
selenium concentrations in female muscle. TRAP tolerance distribution analysis with the log-triangular
model; EC10 =11.9 mg Se/kg muscle dw.
C-10
-------
1.2
1.0
.8
.6
CL
.4
.2
0
0
Log(mg Se/kg egg dw)
Parameter Initial Final
LogX50 1.416 1.4215
S 2 2.6306
Y0 0.96667 0.96667
Figure 3. TRAP analysis from previous draft. Initial estimate for slope set equal to or less than 2.645 (set
to 2 for this figure). ECi0 =16.3 mg/kg.
C-ll
-------
Teh, S.J., X. Deng, D-F Deng, F-C Teh, S.S.O. Hung, T.W. Fan, J. Liu, R.M. Higasi. 2004. Chronic
effects of dietary selenium on juvenile Sacramento splittail (Pogonichthys macrolepidotus). Environ. Sci.
Technol. 38: 6085-6593.
Test Organism: Sacramento splittail (Pogonichthys macrolepidotus)', juveniles 7-mos.old
Exposure Route: Dietary only
Dietary Treatments: 8 graded levels of dietary Se; dietary levels obtained by combining selenized
yeast with Torula (non-active) yeast. Selenized yeast contained approximately
21% of Se as selenomethionine and proteinaceous Se forms. Diet was formulated
as pellets by mixing dry ingredients with water and oil, fan-dried, crumbled and
sieved. Analyzed levels: 0.4 (no selenized yeast), 0.7, 1.4, 2.7, 6.6, 12.6, and 57.6
mg/kg.
Fish were fed twice daily with a daily feeding rate of 3% BW in first 5 months
and then adjusted to 2% BW thereafter.
Test Duration: 9 months
Study Design: A flow-through system with 40 fish/tank (24 total tanks) was used; each tank
held 90 L. Flow rate was 4 L/min. Water temperature was maintained at 23°C for
6 months and then 18°C for last 3 months due to failure of water heating system.
5 fish were sampled from each tank at 5 and 9 months and measured for gross
deformities, length, weight, Se in liver and muscle. Sections of the liver were
kept for histopathology. Condition factor (100 x BW/length), heptatosomatic
index (100 x liver weight/BW), BCF (total organ Se/dietary Se) were determined.
Effects Data: Mortality was observed in the two highest dietary treatments: 10 and 34.3%,
respectively. No mortalities were observed in fish fed diets # 12.6 mg/kg. No
significant difference in growth of fish fed 12.6 mg/kg Se in diet, but there was in
the fish fed 26.6 mg/kg Se. See table below for levels of Se in fish at 9 months
and associated effects.
Authors determined prevalence of deformities was higher in fish fed 6.6 and 12.6
mg/kg Se in their diet, however a dose-response relationship did not occur (e.g.,
no deformities in high concentration). Gross pathology was a more sensitive
endpoint than growth.
C-12
-------
Summary of effects and assoc. dietary and tissue concentrations in Sacramento splittail
after 9 month exp.
Dietary conc'n mg/kg
0.4
0.7
1.4
2.7
6.6
12.6
26.0
57.6
Se in liver, mg/kg dw
20.1
18.6
20.0
23.0
26.8
31.3
40.4
73.7
Se in muscle, mg/kg dw
6.6
6.9
9.2
10.1
15.1
18.9
29.4
38.7
Liver histopathology (mean lesions scores, N=15)
Macrophage aggregate
0.13
0.07
0.2
0.27
0.40
0.20
0.20
0.85
Glycogen depletion
0
0
0.2
0
0.4
0.2
0
1.38
Single cell necrosis
0
0
0
0.07
0.13
0
0.07
0.46
Fatty vacuolar degeneration
0
0
0
0.2
0.53
0.07
0.2
0.08
Eosinophilic protein droplets
0
0
0
0
0
0
0.07
0.85
Sum of mean lesion scores
0.13
0.07
0.4
0.54
1.46
0.47
0.54
3.62
Gross Pathology (No. of deformities, N=15)
Facial deformities (eye, jaw, and mouth)
0
1
0
1
5
3
0
0
Body deformities (kyphosis, lordosis,
scoliosis)
0
0
4
2
3
1
1
0
Prevalence of deformity (%)
0
6.7
26.7
20
53.3
26.7
6.7
0
Chronic Value: Using gross pathology as the endpoint (prevalence of deformities, %), the
NOAEC is 10.1 mg Se/kg dw and the LOAEC is 15.1 mg/kg Se dw in muscle
tissue; MATC or CV = 12.34 mg/kg Se in muscle dw.
The above concentrations in juvenile muscle tissue cannot be exactly translated
into an equivalent egg-ovary or whole-body concentration in adult splittail. But
using the median egg-ovary to muscle ratio of 1.59 for the family Cyprinidae, the
NOEC and MATC would represent 16.1 and 19.6 mg Se/kg egg-ovary. Using the
median muscle to whole-body ratio of 1.26 for the family Cyprinidae, the NOEC
and MATC would represent 8.04 and 9.83 mg Se/kg whole body. However,
appropriateness of these conversion estimates rests upon uncertain assumptions
that the muscle concentrations in juvenile splittails equal those of adult splittails
under the same exposure conditions, and that splittail tissue ratios are those
typical of the family Cyprinidae.
Comments: The authors observed deformities including spinal deformities using fish that
were 7-months-old at test initiation. This is the only study in which deformities
were observed in fish that were not exposed maternally.
Deng et al. (2008) exposed Sacramento splittail juveniles (21-day post hatch) to
dietary selenium and dietary methylmercury in a two factorial design for four
weeks. No adverse effects (growth, condition factor, lethargy or abnormalities)
were observed in the selenium only exposures. The splittail accumulated
approximately 3.5 mg Se/kg ww muscle in the highest dietary exposure (35 mg
C-13
-------
Se/kg. Using the average percent moisture in fish muscle of 78.4% (May et al.
2000), the dw Se concentration is 16.2 mg Se/kg muscle indicating the
recommended CV does not over-estimate an effect concentration.
Rigby et al. (2010) re-analyzed the juvenile Sacramento splittail data generated in
the Teh et al. (2004) study. The authors used logistic regression to estimate EC
values for deformities on a culled data set which eliminated the three highest
dietary treatments due to their departure from a standard concentration-response
relationship. The ECi0 value for the culled data set was 7.9 mg Se/kg dw muscle
which is lower than the recommended CV of 12.3 mg Se/kg dw muscle. Due to
the lack of a concentration-response relationship across the entire dietary range
and the lack of effects in the Deng et al. (2008) study, an ECi0 of 7.9 mg Se/kg
dw muscle is too uncertain for a recommended CV. Although the recommended
CV of 12.3 mg Se/kg dw muscle is based on deformities (an uncertain response),
it is considered representative of an effect level for this species because of the
significant reductions in growth at the two highest test concentrations.
C-14
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Bennett, William N., Arthur S. Brooks, and Martin E. Boraas. 1986. Selenium uptake and transfer in
an aquatic food chain and its effects on fathead minnow larvae. Arch. Environ. Contam. Toxicol. 15:513-
517.
Fathead minnow (Pimephalespromelas; 2 to 8 day-old larvae).
Dietary only
Green alga, Chlorellapyrenoidosa were exposed to Se (H275Se04) in culture
water for 3 days. Rotifers, Brachionus calyciflorus, were cultured in chambers
with selenium containing green algae at the ratio of 25 jug algae/ml to 50 jug
rotifer/ml for 5 hr. The rotifers were filtered to separate them from the algae and
immediately heat-killed. The Se concentration in the rotifers was measured for
75Se activity.
9 to 30 days
Selenium uptake by larval fathead minnows was measured in three experiments.
Se-contaminated and control rotifers for feeding to larval fish were prepared in
advance using the low algae:rotifer ratio. Daily equal volumes of rotifers were
divided among five 800 mL polypropylene larval chambers. Three chambers
received Se-contaminated rotifers and two received control rotifers. The rotifers
were dead at the time of feeding (heat killed).
Larval fish were hatched from eggs spawned in the laboratory. After hatching,
active larvae were divided equally among the larval test chambers (daily renewal
exposures using dechlorinated Lake Michigan water). Larvae were initially fed
rotifers raised on control algae (no selenium). The age of the larvae when first
fed Se-contaminated rotifers was 4, 9, and 3 days post-hatch for experiments 1, 2,
and 3, respectively. Larval fish were fed Se-contaminated rotifers for 7, 9, and 7
days in the 3 experiments. A post-exposure observation period of 19 and 2 days
was used for experiments 1 and 2, respectively. During this time the larvae were
fed control rotifers. Daily, larvae from a replicate were removed from the test
chamber, washed, placed in a 20 ml vial, and counted for 75Se activity for 20 min.
All larvae were then placed in test chambers with fresh food rations. At the end
of the study all fish were individually dried and weighed.
Experiment 1
Experiment 2
Experiment 3
Initial feeding of control diet
(days)
3
8
2
Day Se diet first fed
4
9
3
Day Se diet last fed
11
17
9
Observation days on control diet
19
2
0
Age at study termination (days)
30
19
9
C-15
Test Organism:
Exposure Route:
Test Duration:
Study Design:
-------
Effects Data:
Experiment 1
Experiment 2
Experiment 3
Mean food Se concentration
(mg/kg)
>70
68
55
Food intake ((_ig rotifers/larva)
50
1330
1190
Initial larvae mean dry wt. at start
of Se-laden food (jug)
90
400
100
Final larvae mean dry wt. (jug) at
end of test
1470 (Control)
800 (Treatment)3
1888 (Control)
1354 (Treatment)3
475 (Control)
416 (Treatment)
Final mean larval Se content (jug
Se/larva)b
0.0062
0.0700
0.0248
Final mean larval Se
concentrations (mg Se/kg dw)
43.0
51.7
61.1
a Significantly different from the control.
b Values when Se-laden feeding was ended.
Selenium was measured in the test water during the feeding exposures, but the
concentrations were insignificant (0.84 |Jg/L). Survival was not affected by the
selenium exposures. Preliminary tests showed that fathead minnow larvae would
reach plateau concentrations of selenium within the 7- to 9-day exposure periods.
The food supply was sufficient to sustain growth of the larvae during the study,
according to the authors. The authors state that selenium uptake and higher
selenium content in experiment 2 larvae was due to their larger size and ability to
consume more rotifers/unit time. Se-exposed larvae were significantly smaller
(p<0.05) in mass than controls for experiments 1 and 2.
Chronic Value: GM of mean larval Se concentrations measured in the three experiments, i.e.,
43.0, 51.7, and 61.1 mg/kg dw WB, respectively, is 51.40 mg Se/kg dw.
C-16
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Dobbs, M.G., D.S. Cherry, and J. Cairns, Jr. 1996. Toxicity and bioaccumulation of selenium to a
three-trophic level food chain. Environ. Toxicol. Chem. 15:340-347.
Rotifer (Brachionus calyciflorus), and fathead minnow (Pimephales promelas)
12 to 24 hr-old at start.
Dietary and waterborne
Water
Filtered and sterilized natural creek water supplemented with nutrients (Modified
Guillard's Woods Hole Marine Biological Laboratory algal culture medium) for
algal growth. Sodium selenate (Na2Se04) was added to test water to obtain
nominal concentrations of 100, 200, or 400 (.ig Se/L. Concentrations remained
stable and equal in each trophic level.
Control Diet
No selenium was added to the water medium for the alga; green alga was free of
selenium for the rotifer; and rotifers were free of selenium for the fathead
minnow.
Selenium Diet
Sodium selenate was added to the culture medium for the alga; green alga
thereby contained a body burden for the rotifer; and rotifers thereby contained a
body burden for the fathead minnow.
Dietary Treatments: Each trophic level had a different treatment. The green alga was exposed directly
from the water (1, 108.1, 204.9, 397.6 (.ig total Se/L); rotifers were exposed from
the water (1, 108.1, 204.9, 393.0 |_ig total Se/L) and the green alga as food (2.5,
33, 40, 50 mg Se/kg dry wt.); and the fathead minnow were exposed from water
(1, 108.1, 204.9, 393.0 (ig total Se/L) and the rotifer as food (2.5, 47, 53, 60 mg
Se/kg dry wt.).
Test Duration: 25 days
Study Design: A flow-through system utilizing a stock solution of filtered and sterilized creek
water controlled at 2^C was used to expose three trophic levels of organisms.
Approximately one liter of media was pumped from the algal chamber into the
rotifer chamber each day. A cell density between 3 and 6 / 10' cells/ml was
delivered to the rotifer chambers. Rotifers were started at a density of 151.4 ± 7.7
females/ml and one liter/day of rotifers containing culture water was
intermittently pumped into the minnow chamber. (B. calyciflorus has a life span
of about 7 days at 25°C.) The pump was necessary to overcome the swimming
ability of rotifers to avoid an overflow tube. Larval fathead minnows
(35/chamber) were prevented from escaping by a screened overflow. Chambers
were cleaned daily and aeration was provided. All chambers were duplicated for
test replication and water was measured for selenium on days 0, 2, 6, 7, 11, 14,
17, 20, and 24. All algal and rotifer biomass and selenium samples were made on
these days. Fathead minnow chambers were measured for biomass, dissolved
selenium, and tissue selenium concentrations of days 0, 7, 11, 14, 20, and 24.
Test Organism:
Exposure Route:
C-17
-------
Additional measurements were made in the 200 (.ig Se/L test chambers on the
fathead minnow on day 16. Selenium concentrations were maintained near the
nominal concentrations and the standard deviation of mean concentrations was
less than 4 percent.
Effects Data: Rotifers. Rotifers did not grow well and demonstrated reduced survival at all
selenium exposure concentrations during the 25 day test. By test day 7 only the
lowest test concentration (108.1 (ig/L) had surviving rotifers which showed a
decrease in selenium content from test days 18 through 25. A reduction in rotifer
biomass was discernable by test day 4 in the selenium treatments and since all
test concentrations had viable rotifer populations present, the effect level was
calculated using these data.
Effect of Dietary and Waterborne Selenium on Rotifers after 4 Days Exposure
Se in water, jig/L
Se in diet, mg/kg dw
Se in rotifer tissue,
mg/kg dw
rotifer biomass, mg/ml
dw
1
2.5
2.5
0.028
108.1
33
40
0.025
202.4
40
54
0.011
393
50
75
0.003
Fathead minnows. Due to the reduction of rotifer biomass in the higher test
concentrations, fish mortality and reduction in fish growth observed in the latter
days of the test was difficult to discern between effects from starvation and
selenium toxicity. The data from test day 8 was selected for determining the
effect of selenium on fathead minnows because starvation could be excluded as a
variable.
C-18
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Effect of Dietary and Waterborne Selenium on Larval Fathead Minnows after 8 Days Exposure
Se in water, jig/L
Se in diet, mg/kg dw
Se in fathead minnow
tissue, mg/kg dw
Average fish weight,
mg dw
1
2.5
2.5
0.8
108.1
47
45
0.7
202.4
53
75
0.4
393
60
73
0.2
Chronic Value:
Rotifers 42.36 mg Se/kg dw (EC2o)
Fish < 73 mg Se/kg dw (LOAEC) - not amenable to statistical treatment; the LOAEC
was based on the observation that a >50 percent reduction in mean fish weight
occurred at this tissue concentration.
C-19
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Schultz, R. and R. Hermanutz. 1990. Transfer of toxic concentrations of selenium from parent to
progeny in the fathead minnow (Pimephalespromelas). Bull. Environ. Contam. Toxicol. 45:568-573.
Test Organism: Fathead minnow (Pimephales promelas; Adults)
Exposure Route: Dietary and waterborne
Selenite was added to artificial streams which entered the food web; thus, fish
were also exposed to selenium in the diet.
Study Design: Four Monticello artificial streams were used for the study which lasted from
September 1987 to September 1988. For each study, two streams (treated) were
dosed continuously to achieve 10 |a,g/L and two streams served as controls. Mean
selenium concentrations at the head of the treated streams were 9.8 ±1.2 and
10.3 ±1.7 |a,g/L, respectively. The concentrations of selenium measured in the
water from controls streams were all less than the detection limit, i.e., 2 (ig/L.
Spawning platforms were submerged into each stream. One subset of six embryo
samples (n = 2000 embryos per sample) were collected from the streams for
selenium analysis. Another subset of ten embryo samples were reared in
incubation cups receiving the same stream water dosed with sodium selenite via a
proportional diluter. The treated embryos in egg cups received an average 9.7 ±
2.6 |ag Se/L. Samples of hatched larvae were analyzed for selenium content while
others were inspected for occurrence of edema and lordosis. Prior to test
termination, female parents were seined. The mean selenium content in the
ovaries of seven to eight females from the treated and control streams was
reported.
Effects Data: Edema and lordosis occurred in approximately 25 percent of the fish spawned
and reared in 10 (ig Se/L. Corresponding occurrence in control fish incubated in
the egg cups was only 1 and 6 percent, respectively. Table 1 provides the
abnormality observations and the selenium residues in the embryos and ovaries
from the control and treated streams. Although a case can be made that the Se
treatment had a higher rate of edema and lordosis, there are some problems that
add uncertainty to the estimation of an effect concentration (R. Erickson, pers.
comm.). Heavy mortality/loss of embryo/larvae during monitoring and the erratic
occurrence of the abnormalities (e.g., there is a significant incidence of edema in
only 3 of 10 replicates for the Se treatment) led to the conclusion that results
should not be used for criterion derivation. However, the data from this study
support the range of reproductive effect levels determined in other studies. The
Se concentration in embryos from the 10 (ig/L treatment stream of 3.91 mg/kg
ww converts to 25.6 mg/kg dw using 15.3% dw (N=3 range 14.7 - 15.6%) for
fathead minnow eggs (R. Erickson, pers. comm). The previous draft used the Se
concentrations in the ovaries collected at the end of the study for the effect
concentration estimate. However, it was determined that the embryos are a more
direct representation of Se exposure and toxicity to the larvae.
Chronic Value: The LOEC for embryos is <25.6 mg Se/kg dw.
C-20
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Table 1. Percent Abnormalities in Fathead Minnow Larvae and the Associated Selenium Concentrations
in Embryos and Ovaries.
Treatment
[Se] embryos,
mg/kg ww (SD)
[Se] ovaries,
mg/kg ww (SD)
Edema, % (SD)
Lordosis, % (SD)
Control
0.31 (0.01)
0.77 (0.14)
0.9 (2.2)
5.6(8.8)
10 jig/L
3.91 (1.87)
5.89 (2.21)
24.6(36.1)
23.4 (20.8)
SD = standard deviation
C-21
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Beyers, D.W. and Sodergren, C. 2001a. Evaluation of interspecific sensitivity to selenium exposure:
Larval razorback sucker versus flannelmouth sucker. Larval Fish Laboratory. Department of Fishery and
Wildlife Biology, Colorado State University, Fort Collins, Colorado.
Test Organism:
Exposure Route:
Study Design:
Effects Data
Chronic Value:
Larval flannelmouth sucker (Catostomus latipinnis) and larval razorback sucker
(Xyrauchen texanus)
Dietary and waterborne - laboratory exposure (28-d early life stage)
Continuous flow diluter supplied a range of aqueous test concentrations <1, 25.4,
50.6, 98.9, and 190.6 |_ig/L selenate. Well water was used as the dilution water.
Across the range of aqueous exposure concentrations, each test chamber was fed
the same daily ration of living rotifers containing selenium at <0.702, 1.35, 2.02,
4.63, and 8.24 mg/kg dw, respectively. Rotifers accumulated selenium from
algae (Chlorella vulgaris) exposed to 0, 25, 50, 100, and 200 :g/L selenate.
Replicated (n=4) exposure beakers using a randomized, balanced 5x2 factorial
design (1st factor - selenium; 2nd factor - species). Survival was monitored daily
and growth measured at the end of the 28-day exposure. Selenium was measured
in the larvae at the end of the 28-day exposure.
No survival effects were observed and there were no decreases in fish weight or
length. Fish mass was found to increase as a function of selenium concentration.
The chronic values for the flannelmouth sucker and razorback sucker were >10.2
and >12.9 mg Se/kg dw, respectively, based on the concentrations of selenium
measured in whole-body tissue of larval fish at the highest water and dietary
selenium concentrations.
C-22
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Beyers, D.W. and Sodergren, C. 2001b. Assessment of exposure of larval razorback sucker to selenium
in natural waters and evaluation of laboratory-based predictions. Larval Fish Laboratory. Department of
Fishery and Wildlife Biology, Colorado State University, Fort Collins, Colorado.
Test Organism: Larval razorback sucker (Xyrauchen texanus)
Exposure Route: Dietary and waterborne - laboratory exposure (28-d early life stage)
Larvae were exposed in a daily static-renewal system to control water
(reconstituted very hard) and site waters: De Beque, Orchard Mesa, North Pond
diluted 50%, and North Pond. Each water type received either a control diet
(rotifers) or a diet previously exposed to the site water (site food: rotifers fed
algae exposed to respective site water).
Study Design: Replicated (n=4) exposure beakers using a randomized, balanced 5x2 factorial
design (1st factor - test water type; 2nd factor - rotifers cultured in control water or
in site water). Survival was monitored daily and growth measured at the end of
the 28-day exposure. Selenium was measured in the larvae at the end of the 28-
day exposure.
Effects Data: No survival effects were observed. There were no significant decreases in growth
of fish exposed to both site water and site food compared to fish exposed to
control water and control food. There was a significant increase in growth of fish
exposed to site water and control food relative to fish exposed to control water
and control food (p<0.0001). There were reductions in the growth of fish (14%)
exposed to site water and site food compared to site water and control food
(p<0.0001). Due to the lack of a dose-response relationship in both the
concentration of selenium in the food (rotifers) and growth, and the concentration
of selenium in the fish larvae and growth, the authors did not attribute the effect
of site food on the growth of fish to selenium.
Chronic Value: The NOAEC for the razorback sucker larvae in the four site water types based on
selenium in whole-body tissue were: De Beque >5.45 mg Se/kg dw; Orchard
Mesa >11 mg Se/kg dw; North Pond 50% dilution >41.1 mg Se/kg dw; North
Pond >42 mg Se/kg dw. Because no significant effects were observed in larvae
exposed to North Pond water at >42 mg Se/kg dw whole-body tissue, this value
was selected as the chronic value for the study.
C-23
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Muscatello, J.R., P.M. Bennett, K.T. Himbeault, A.M. Belknap and D.M. Janz. 2006. Larval
deformities associated with selenium accumulation in northern pike (Esox lucius) exposed to metal
mining effluent. Environ. Sci. Technol. 40:6506-6512.
Test Organism:
Exposure Route:
Test Duration:
Study Design:
Effects Data:
Northern pike (Esox lucius)
Dietary and waterborne - field exposure
Eggs were collected in the field and incubated in the laboratory. The test was
terminated when the majority of the fry exhibited swim-up and had absorbed the
yolk.
The study area was Key Lake uranium milling operation in north-central
Saskatoon. Spawning northern pike were collected from four sites, one reference
(Davies Creek) and three exposure sites, David Creek near-field (high exposure),
Delta Lake (medium exposure), and David Creek far-field (low exposure). The
exposure sites were located approximately 2, 10 and 15 km downstream of the
effluent discharge. Milt and ova were stripped from ripe fish and eggs were
fertilized in the field. Females were saved for metal analysis and age
determination. Subsamples of ova (prior to fertilization) were collected for metal
analysis.
Although the study sites represent open systems where fish can potentially
migrate among sites, radiotelemetry data from tagged adult pike (Muscatello and
Janz, unpublished data) indicate high site fidelity at the "high" and "medium"
exposure sites (lakes). In contrast, the "low" exposure site likely represents pike
that migrated from further downstream sites that were likely of similar Se
exposures as the reference site.
Eggs were incubated using a two-way ANOVA experimental design using water
collected from reference or exposure sites. So, embryos originating from
reference or exposure site females were incubated in either reference or
appropriate exposure water. In addition, embryos from reference site females
were incubated in water from all four study sites. 50 viable embryos from each
individual female were transferred to each of four replicate incubation chambers.
Cumulative time to 50% eyed, 50% hatch and 50% swim-up were determined.
When the majority of the fry exhibited swim-up and had absorbed the yolk, the
remaining fry were preserved and examined for deformities.
Mean egg diameter and fertilization success did not differ among sites.
Cumulative embryo mortality throughout incubations was not significantly
different among the sites ranging from 45 to 60%. There were no significant
differences in the cumulative time to reach 50% eyed embryos, 50% hatch or
50% swim-up among treatments. Differences in the percent total deformities
between test waters used during embryo incubation exposures were not
significant, so the data were combined for each site (see Table below).
C-24
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Selenium concentrations in eggs and muscle from female northern pike collected from reference
and exposed sites and associated total deformities in embryos
Site
Site ID
Female
fSe] mg/kg dw
Total
Egg
Muscle
deformities %
Davies Creek
Reference
1
3.45
0.86
17
Davies Creek
Reference
2
2.72
1.89
2.5
Davies Creek
Reference
3
3.39
2.56
15.51
Davies Creek
Reference
4
3.72
1.34
7.13
Davies Creek
Reference
5
2.69
1.04
10.41
David Creek (far field)
Low
1
3.39
1.95
20.32
David Creek (far field)
Low
2
4.07
2.04
13.19
David Creek (far field)
Low
3
4.07
1.26
15.33
David Creek (far field)
Low
4
4.07
2.48
18.83
David Creek (far field)
Low
5
3.4
1.26
11.8
Delta Lake
Medium
1
43.19
17
37.8
Delta Lake
Medium
2
24.53
16.52
31.71
Delta Lake
Medium
3
26.14
16.52
26.29
David Creek (near field)
High
1
48.23
47.82
39.5
David Creek (near field)
High
2
N/A*
28.72
N/A*
* female had no eggs
Significant increases in total deformities (edema, skeletal deformities,
craniofacial deformities and fin deformities) were observed in fry originating
from pike collected at the medium exposure site. Determination of an effect level
for the percent total deformities relative to the concentration of selenium in eggs
or in female muscle tissue was not amenable to analysis by TRAP. One
requirement of TRAP is to have a response greater than 50%, which was not
satisfied with the available data.
When data are not amenable to determining an effect level using a software
program, such as TRAP, one way to estimate the effect level is to make a direct
measurement of effect at an exposure or tissue concentration. For example, if
only a control and one exposure concentration, 10 |ag/L, were tested in an acute
toxicity test and there was 100% survival in the control and 35% in the 10 |ag/L,
the effect level would be an EC35 of 10 fxg/L. Such an approach was used to
estimate effect in the Muscatello et al. data. Because no significant differences
were observed in either selenium concentrations in eggs or percent total
deformities between the reference and low exposure site, the data from these 10
sites were combined. Similarly, the egg and muscle selenium and total deformity
data were combined for the 4 medium and high exposure sites. These means,
geometric for the selenium concentrations and arithmetic for the percent total
deformities, are given in the following table.
C-25
-------
Mean selenium in northern pike egg and muscle and effect values for reference
and exposure sites
Sites
[Se] in eggs,
mg/kg dw
(geometric
mean)
[Se] in muscle,
mg/kg dw
(geometric
mean)
Total deformities, %
(arithmetic mean)
Total deformities,
% (accounting for
reference
deformities and
transformed to
new scale)3
Reference
sites (includes
low exposure)
3.462
1.570
13.20
0
exposure sites
34.00
21.70
33.82
23.76
a The % total del
ormities in the reference and exposed sites were normalized to t
le reference effect
(13.2%) and then transformed to a new scale (100%). i.e, Abbott's formula.
The percent affected becomes 24% or an EC24 and the effect level is 34.00 mg
Se/kg dw in eggs and 21.70 mg Se/kg in muscle.
Chronic Value: EC24 = 34.00 mg Se/kg dw in eggs. Note: an ECi0 cannot be estimated with the
data.
C-26
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Hamilton, S.J., K.J. Buhl, N.L. Faerber, R.H. Wiedermeyer and F.A. Bullard. 1990. Toxicity of
organic selenium in the diet of chinook salmon. Environ. Toxicol. Chem. 9:347-358.
Test Organism: Chinook salmon (Oncorhynchus tshawytscha Walbaum; swim-up larvae)
Exposure Route: Dietary only
Control Diet
Oregon moist pellet diet where over half of the salmon meal was replaced with
meal from low-selenium mosquitofish (1.0 mg Se/kg dw) collected from a
reference site.
Selenium Diet # 1
Oregon moist pellet diet where over half of the salmon meal was replaced with
meal from high-selenium mosquitofish (35.4 mg Se/kg dw) collected from the
San Luis Drain, CA, termed SLD diet.
Selenium Diet #2
Oregon moist pellet diet where over half of the salmon meal was replaced with
meal from low-selenium mosquitofish same as in the control diet, but fortified
with seleno-DL-methionine (35.5 mg Se/kg dw), termed SeMet diet.
Dietary Treatments: Each selenium diet was formulated to contain about 36 mg Se/kg dw as the high
exposure treatment. The remaining treatments were achieved by thoroughly
mixing appropriate amounts of high-exposure treatment diet with control diet to
yield the following nominal concentrations (3, 5, 10, and 18 mg Se/kg dw).
Test Duration: 90 days
Study Design: Each dietary treatment was fed twice each day to swim-up larvae (n=100) in each
of two replicate aquaria that received 1 L of replacement water (a reconstituted
experimental water that simulated in quality a 1:37 dilution of water from the San
Luis Drain, CA minus the trace elements) every 15 minutes (flow-through
design). Mortality was recorded daily. Growth was evaluated at 30-day intervals
by measuring the total lengths and wet weights of two subsets of individual fish
(n=10x2) held in separate 11.5 L growth chambers within each replicate
aquarium. Tissue samples were collected for whole-body selenium
determinations (dw basis) at 30-day intervals throughout the study; 10, 5, and 2
fish were sampled from each duplicate treatment after 30, 60, and 90 days of
exposure, respectively. Concentrations of selenium measured in water were
below the limit of detection (1.5-3.1 |ag/L) in all dietary selenium exposure
concentrations.
C-27
-------
Effects Data: The magnitude of reduced growth was most evident in the weight of the fish,
although total length was significantly reduced in fish fed high Se-laden diets as
well. The effect of increasing dietary selenium on mean larval weight was similar
in both the SLD and seleno-methionine diets.
Effect of San Luis Drain Diet on Growth and Survival of Chinook Salmon Larvae after 60 Days
Se in diet, mg/kg dw
Se in chinook salmon,
mg/kg dw
Mean larval weight, g
Survival, %
1
0.9
3.35
99
3.2
3.3
2.68
97.3
5.3
4.5
2.76
93
9.6
8.4
2.8
95
18.2
13.3
2.62
92.4
35.4
29.4
1.4
89
Effect of Seleno-methionine Diet on Growth and Survival of Chinook Salmon Larvae after 60
Days
Se in diet, mg/kg dw
Se in chinook salmon,
mg/kg dw
Mean larval weight, g
Survival, %
1
0.9
3.35
99
3.2
2
3.08
100
5.3
3.1
3.22
95
9.6
5.3
3.07
94.1
18.2
10.4
2.61
92.4
35.4
23.4
1.25
62.5
C-28
-------
Chronic Value: Due to unacceptable control mortality of swim-up larvae in control treatments
after 90 days (33.3 percent - SLD diet; 27.5 percent - SeMet diet), chronic values
had to be determined from respective values reported after 60 days (tables
above).
Analysis of the elemental composition of the SLD diet indicated that B, Cr, Fe,
Mg, Ni and Sr were slightly elevated compared to the control and SeMet diets.
No additional analyses were performed to determine the presence of other
possible contaminants, i.e., pesticides.
Diet
type
EC2o values
ECio values
Survival
(after 60 d of
exposure)
Growth
(after 60 d of exposure)
Growth
(after 60 d of exposure)
Tissue Se
(mg/kg dw)
Whole body Tissue Se
(mg/kg dw)
Whole body Tissue Se
(mg/kg dw)
SLD
NAa
15.73
11.14
SeMet
NAa
10.47
7.355
a The EC2o and ECi0 values for survival of swim-up larvae versus levels of selenium for the SLD and
SeMet dietary exposure could not be estimated using non-linear regression.
C-29
-------
Hamilton et al (1990) Chinook Salmon fed SLD Diet
Logistic Equation, Three Parameter Model, Se concentrations logio transformed
O)
'<5
4.0
3.5
3.0
2.5
¦= 2.0
CO
>
CO
CO
CD
1.5
1.0
.5
U
0
.2
.4
O
CO
CO
Log(Se in Chinook Salmon mg/kg
Guess
FinalEst
SE
95% LCL 95%UCL
LogX50
1.453
1.453
7.30E-02
1.2206 1.6854
StDev
1.353
1.353
6.67E-01
-7.71E-01 3.4769
YO
2.968
2.968
1.89E-01
2.3651 3.5709
% Effect
Xp Est
95% LCL
95% UCL
50
28.379
16.62
48.458
20
15.734
5.7003
43.431
10
11.143
2.4771
50.127
5
8.1085
1.1213
58.637
DF
SS
MS
F P
Total
5
2.0749
0.41498
Model
2
1.8202
0.91009
10.719 0.95699
Error
3
0.2547
8.49E-02
1.2
1.4
1.6
C-30
-------
Chinook salmon SeMet diet (Hamilton et al. 1990)
_
>
to
1.6
1.4
.8
.8
1.0
1.2
0
.2
.4
Log([Se]whole body, mg/kg dw)
Parameter Summary (Logistic Equation Regression Analysis)
Parameter
Guess
FinalEst
StdError
95%LCL
95%UCL
LogXSO
1.3148
1.2823
0.0242
1.2053
1.3593
S
0 6971
1.3214
0.1826
0.7404
1.9025
Y0
3.217
3.239
0.067
3.027
3.452
Effect Concentration Summary
% Effect
Xp Est
95%LCL
95%UCL
50.0
19.156
16.045
22.870
20.0
10.472
7.516
14.591
10.0
7.355
4.595
11.775
5 0
5.312
2.899
9.733
06/19/2009 13:52 MED Toxic Response Analysis Model, Version 1 03
C-31
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Hilton, J.W. and P.V. Hodson. 1983. Effect of increased dietary carbohydrate on selenium metabolism
and toxicity in rainbow trout (Salmo gairdneri). J. Nutr. 113:1241-1248.
Test Organism: Rainbow trout (Oncorhynchus mykiss; juvenile; approx. 0.6 g each)
Exposure Route: Dietary only
Low carbohydrate diet (LCD)
This diet contained capelin oil at 11 percent of the diet with cellulose as the filler.
High carbohydrate diet (HCD)
This diet contained cerelose at 25 percent of the diet with cellulose as the filler.
For both diets, the selenium was supplemented as sodium selenite which was
mixed with cellulose and then added to the diet as a selenium premix.
Test Treatments: The two diets were supplemented with selenium (as sodium selenite) at the rate
of 0, 5, or 10 mg/kg dw to make up the six different dietary selenium treatments
(n = 3 low carbohydrate diet; n= 3 high carbohydrate diet). The six diets were fed
to duplicate groups of 100 fish. The trout were fed to satiation 3-6 times per day.
Measured concentrations of selenium in the low carbohydrate diet were: 0.6
(control), 6.6, and 11.4 mg/kg dw, and the measured concentrations of selenium
in the high carbohydrate diet were: 0.7 (control), 6.6, and 11.8 mg/kg dw. The
tanks received a continuous flow of water with a flow rate of 3-4 liters per
minute.
Test Duration: 16 weeks
Study Design: Body weights, feed: gain ratios, and total mortalities were determined after each
28-day interval. After 16 weeks, approximately 20 fish were randomly removed
from each tank, weighed, and blood was collected for hemoglobin, hematocrit,
and plasma glucose, protein, and calcium determination. The livers and kidneys
were then dissected. The livers were assayed for glycogen content, and samples
of both liver and kidney were assayed for selenium content. Additional
subsamples of fish were sacrificed and assayed for selenium content and for ash,
crude protein, and moisture content (n=6 per treatment). Finally, 30 fish were
killed, their livers and kidneys dissected, and analyzed for Ca, Cu, Fe, Mg, P, and
Zn content.
Effects Data: The only overt sign of selenium toxicity was food avoidance observed in trout
fed the highest selenium content in both low and high carbohydrate diets, which
led to significantly reduced body weight after 16 weeks. There were no
significant differences detected between treatment groups in hematological
parameters. Kidney, liver, and carcass selenium levels increased with increasing
selenium content of the diet, however, only the liver selenium concentrations
were significantly affected by dietary selenium level, dietary carbohydrate level,
and the interaction between the two treatments. Mineral analysis of the kidney
showed significantly higher levels of calcium and phosphorous in trout reared on
the two highest levels of dietary selenium. Concentrations of copper in the liver
increased significantly with increasing dietary selenium levels and decreasing
dietary carbohydrate levels.
C-32
-------
Effect of Selenium in Low carbohydrate Diet to Rainbow Trout
Se in diet, mg/kg dw
Se in trout liver, mg/kg dw
Trout weight, kg/100 fish
0.6
0.8
3.3
6.6
38.3
3.3
11.4
49.3
1.8
Effect of Selenium in High carbohydrate Diet to Rainbow Trout
Se in diet, mg/kg dw
Se in trout liver, mg/kg dw
Trout weight, kg/100 fish
0.7
0.6
2.7
6.6
21.0
2.3
11.8
71.7
1.4
Chronic Value: The following table lists the NOAEC, LOAEC and MATC for both diets in liver
tissue. EC values could not be determined for this study. Data did not meet
minimum requirements for analysis.
Diet
NOAEC, mg Se/kg dw
liver
LOAEC, mg Se/kg dw
liver
MATC, mg Se/kg dw
liver
Low carb
38.3
49.3
43.5
high carb
21.0
71.7
38.8
C-33
-------
Hicks, B.D., J.W. Hilton, and H.W. Ferguson. 1984. Influence of dietary selenium on the occurrence of
nephrocalcinosis in the rainbow trout, Salmo gairdneri Richardson. J. Fish Diseases. 7:379-389.
(Note: These data are the exact same as reported for the low carbohydrate diet in Hilton and Hodson
1983, with the addition of prevalence of nephrocalcinosis occurring in trout after 16 to 20 weeks of
consuming the contaminated test diets).
Test Organism:
Exposure Route:
Test Treatments:
Test Duration:
Study Design:
Effects Data:
Rainbow trout (Oncorhynchus mykiss; juvenile; approx. 0.6 g each)
Dietary only
This diet contained capelin oil at 11 percent of the diet with cellulose as the filler.
The selenium was supplemented as sodium selenite which was mixed with
cellulose and then added to the diet as a selenium premix.
The test diet was supplemented with selenium (as sodium selenite) at the rate of
0, 5, or 10 mg/kg dw to make up the three different dietary selenium treatments.
The three diets were fed to duplicate groups of 100 fish. The trout were fed to
satiation 3-6 times per day. Measured concentrations of selenium in the low
carbohydrate diet were: 0.6 (control), 6.6, and 11.4 mg/kg dw. The tanks received
a continuous flow of water with a flow rate of 3-4 liters per minute.
16 to 20 weeks
See Hilton and Hodson (1983). After 20 weeks on the test diets, ten fish were
randomly removed from each treatment. Tissues for histopathological
examination included the stomach, intestine and pyloric ceca (including
pancreas), spleen, liver, heart, kidney, skin, muscle, and gills.
Only effects of selenium on kidney tissue are included in the article. The kidneys
of the 10 trout fed the highest selenium content in the diet exhibited normal
appearance. Five of these trout exhibited precipitation of calcium in the tubules
with some epithelial necrosis, but no loss of epithelial continuity. Extensive
mineralized deposition of Ca within the tubules, tubular dilation and necrosis of
tubular epithelium, ulceration of tubules, and intestinal Ca mineralization was
observed in four of the ten fish.
Chronic Value: Same as for growth of rainbow trout reported by Hilton and Hodson (1983). The
MATC estimated for growth of rainbow trout relative to final concentration of
selenium in liver tissue of trout reared on the low carbohydrate diet is the GM of
38.3 (NOAEC) and 49.3 (LOAEC) mg/kg dw, or 43.45 mg/kg dw.
EC values could not be determined for this study. Data did not meet minimum
requirements for analysis.
C-34
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Hilton, J.W., P.V. Hodson, and S.J. Slinger. 1980. The requirements and toxicity of selenium in
rainbow trout (Salmo gairdneri). J. Nutr. 110:2527-2535.
Test Organism: Rainbow trout (Oncorhynchus mykiss; juvenile; approx. 1.28 g each)
Exposure Route: Dietary only
A casien-torula yeast diet was formulated to contain geometrically increasing
levels of selenium from 0 to 15 mg/kg dw. The selenium was supplemented as
sodium selenite which was mixed with cellulose and then added to the diet as a
selenium premix.
Test Duration: 20 weeks
Study Design: Six test diets were fed to triplicate groups of 75 fish. The trout were fed to
satiation 3-4 times per day, 6 days per week, with one feeding on the seventh
day. Measured concentrations of selenium in the diet were: 0.07 (control), 0.15,
0.38, 1.25, 3.67, and 13.06 mg/kg dw. The tanks received a continuous flow of
dechlorinated tap water from the City of Burlington, Ontario municipal water
supply. The waterborne selenium content of this water was 0.4jli g/L. During the
experiment, the fish were weighed every 2 weeks with the feeding level adjusted
accordingly. Mortalities were noted daily and the feed consumption for each
treatment was recorded weekly. After 4 and 16 weeks, three to six fish were
randomly removed from each tank, sacrificed, and their livers and kidneys
removed and weighed. An additional three to six fish were then obtained from
each treatment, killed, and prepared for tissue analysis. Organs and carcasses
were freeze-dried for determination of selenium concentration. After 16 weeks,
three more fish were removed. Kidney, liver, spleen and dorsal muscle tissue was
dissected for examination of histopathology. At the end of 8 and 16 weeks, four
to five fish were removed, sacrificed, and a blood sample was taken for
hematological measurements (hematocrit, red blood cell count, and blood iron
concentration). After 20 weeks, three to four more fish were removed, sacrificed,
and a blood sample was taken for measurement of glutathione peroxidase
activity.
Effects Data: There were no significant differences detected between treatment groups in
histopathology, hematology, or plasma glutathione peroxidase activity. Trout
raised on the highest dietary level of selenium (13.06 mg/kg dw) had a
significantly lower body weight and a higher number of mortalities (10.7;
expressed as number per 10,000 fish days) than trout from the other treatments
levels after 20 weeks of exposure.
C-35
-------
Effects on Juvenile Rainbow Trout
Se in diet, mg/kg dw
Se in Liver, mg/kg dw
Weight, g/fish
Mortality*
0.07
0.6
3.2
0
0.15
0.95
3.5
0.38
2.4
3.7
0.6
1.25
11
4.1
0.6
3.67
40a
4.1
13.06
100D
1.4
10.7
expressed as number per 10,000 fish-days
NOAEC
LOAEC
Chronic Value: NOAEC = 40 mg Se/kg dw
LOAEC =100 mg Se/kg dw
MATC = 63.25 mg Se/kg dw
C-36
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Holm, J. 2002. Sublethal effects of selenium on rainbow trout (Oncorhynchus mykiss) and brook trout
(Salvelinus fontinalis). Masters Thesis. Department of Zoology, University of Manitoba, Winnipeg, MB.
Holm, J., V.P. Palace, K. Wautier, R.E. Evans, C.L. Baron, C. Podemski, P. Siwik and G. Sterling.
2003. An assessment of the development and survival of rainbow trout (Oncorhynchus mykiss) and brook
trout (Salve linus fontinalis) exposed to elevated selenium in an area of active coal mining. Proceedings of
the 26th Annual Larval Fish Conference 2003, Bergen, Norway. ISBN 82-7461-059-B.
Holm, J., V.P. Palace, P. Siwik, G. Sterling, R. Evans, C. Baron, J. Werner, and K. Wautier. 2005.
Developmental effects of bioaccumulated selenium in eggs and larvae of two salmonid species. Environ.
Toxicol. Chem. 24: 2373-2381.
Test Organism:
Exposure Route:
Study Design:
Effects Data
Rainbow trout (Oncorhynchus mykiss; spawning adults) and brook trout
(Salvelinus fontinalis; spawning adults)
Dietary and waterborne - field exposure
Total selenium concentrations measured at the high selenium site ranged from 6
to 32 |ag/L. Selenium was not measured at the reference streams; selenium
concentrations at reference locations in the area ranged from <0.5 to 2.2 |ag/L.
Spawning fish were collected at low selenium or reference streams (Deerlick
Creek, Wampus Creek and Cold Creek), a slightly elevated selenium stream
(Gregg Creek), and an elevated selenium stream (Luscar Creek) in the
Northeastern slopes region of Alberta, Canada. An active coal mine is the source
of selenium in the elevated streams. Eggs and milt from the spawning trout were
expressed by light pressure from abdomen. Individual clutches of eggs were
fertilized from a composite volume of milt derived from 3-5 males. Fertilized
eggs from individual females were reared to swim-up stage and examined for a
number of parameters including percent fertilization, mortality, edema, and
deformities (craniofacial, finfold, and spinal malformations). Similar studies
were conducted in 2000, 2001 and 2002. One notable difference is that the
embryos were incubated at 8°C in 2000 and at 5°C in 2001. The authors noted
that 5°C is a better representation of the actual stream temperature during embryo
development.
Other than selenium, there were no significant differences in the concentrations
of other elements (Al, As, Sb, Ba, Be, Ni, B, Cd, Ca, Cr, Co, Cu, Fe, Pb, Li, Mg,
Mn, Hg, Mo, Ag, Sr, Tl, Th, Sn, Ti, U, V, Zn) in trout eggs between the low level
and elevated selenium streams. There are two ways to approach determination of
effects due to selenium in this study and both are presented here. The first
approach determines effects based on a comparison of average conditions
between streams (between streams approach). For example, if there is a
significant difference between the average frequency of deformities in a
contaminated stream and reference stream, the effect level for the between
streams approach would be the average concentration of selenium in the tissue
from the contaminated stream. The second approach evaluates individual
response variables (e.g., edema, deformities) against the individual selenium
tissue concentrations for the combined contaminated and reference stream data
set with each year (within streams approach). This approach, which results in an
C-37
-------
EC estimate (e.g., ECi0) if the data meet the model assumptions, is explained
below.
Between streams approach: For each sampling location (stream), data for the
three years (Tables 1 and 2) were combined in the between streams analysis of
variance (ANOVA). For rainbow trout embryos, there were no significant
differences in fertilization, time to hatch and mortality between the streams with
elevated selenium and the reference streams. ANOVA indicated significant
differences in the frequency of embryonic effects between streams (Table 3). The
analysis did not prove useful; however, due to a higher occurrence of effects in
some of the reference streams relative to the exposed streams (Tables 3 and 4).
The between streams analysis, therefore, was not used to determine effect
concentrations for rainbow trout.
ANOVA of brook trout data indicated the only significant difference in
embryonic abnormalities among sites was craniofacial deformities (Tables 5 and
6). Significant differences were also found for fertilization and larval weight. The
highest average percent fertilization was observed at the site with the greatest
concentration of selenium in eggs, which indicates that the differences in
fertilization among sites were not caused by variation in selenium concentrations.
Because the percent of embryos with craniofacial deformities in Luscar Creek
was 7.9% (2.1% in Cold Creek), it was not considered biologically meaningful.
Likewise the significantly lower larval weights at the exposed sites was not large
(16% lower than Cold Creek larvae) and again coupled with the low occurrence
of abnormalities by the brook trout, a signature of selenium effects, the lower
larval weights were not considered biologically meaningful.
Within streams approach: As with the between streams analysis, data were
combined for the three years of study in the within streams analysis (Tables 1 and
2). Craniofacial deformities, skeletal deformities and edema in rainbow trout
embryo, as a function of selenium in egg ww, were fitted to a curve using a
weighted regression and threshold sigmoidal equation from which ECi0 values
were calculated (see Figures 1, 2 and 3). EC estimates for finfold deformities,
length and weight of rainbow trout embryos could not be made because of
inadequate dose-response. The brook trout data were not suitable for fitting
logistic curves (Figure 5).
C-38
-------
Table 1. Rainbow trout embryo-larval parameters collected from a high Se site (Luscar Creek), an
intermediate Se site (Gregg River), and reference sites (Deerlick Creek and Wampus Creek) in
northeastern Alberta over three consecutive years.
Year Site Female # Se in eggs, %craniofacial %skeletal %finfold %edema
mg/kg ww deformities deformities deformities
2000
Luscar
11
6.84
7.18
13.26
1.66
4.97
2000
Luscar
12
6.66
1.48
4.43
0.74
1.85
2000
Luscar
14
11.6
14.43
23.71
7.22
85.57
2000
Deerlick
16
1.78
0.63
1.9
0.63
0.63
2000
Deerlick
17
1.39
0
0
0
0
2000
Deerlick
18
1.00
0
0.86
0
0
2000
Deerlick
15
5.01
0
0
0
0
2001
Luscar
1
5.39
7.35
6.76
3.53
2.94
2001
Luscar
3
8.39
6.29
4.97
2.98
6.95
2001
Luscar
4
6.48
22.22
22.22
33.33
26.67
2001
Luscar
8
4.47
12
9.33
2.67
10.67
2001
Luscar
14
10.4
34.55
44.85
4.24
43.64
2001
Luscar
32
5.64
8.24
5.97
3.13
9.09
2001
Luscar
33
3.88
5.26
6.58
9.21
3.95
2001
Luscar
39
5.14
1.91
3.18
0
1.27
2001
Luscar
40
3.36
11.62
7.05
5.39
6.64
2001
Luscar
41
11.7
37.67
83.41
3.59
87
2001
Deerlick
8
3.68
9.55
5.45
1.36
5.45
2001
Deerlick
9
3.08
5.39
4.98
0.41
2.07
2001
Deerlick
10
1.62
7.89
7.89
5.26
10.53
2001
Deerlick
16
2.62
24.24
48.48
3.03
12.12
2001
Deerlick
17
2.79
14.13
15.22
4.35
20.65
2001
Deerlick
21
1.96
13.27
35.71
7.14
25.51
2001
Deerlick
22
3.13
1.09
2.17
0
1.09
2001
Deerlick
23
3.03
9.65
14.04
3.51
7.89
2001
Deerlick
25
3.32
9.25
13.29
7.51
8.09
2001
Deerlick
39
2.43
11.89
9.09
7.69
14.69
2001
Gregg
2
4.57
11.97
7.75
15.49
7.04
2001
Gregg
3
4.49
5.58
9.3
2.33
4.65
2001
Gregg
5
4.05
4.95
5.45
2.48
5.94
2001
Gregg
9
5.09
20
13.85
15.38
16.15
2001
Gregg
18
5.97
16.13
19.35
41.94
35.48
2001
Wampus
9
2.66
16.07
0
1.79
7.14
2001
Wampus
13
2.04
7.84
9.8
1.31
7.84
2002
Luscar
3
5.4
60.47
27.9
93
14
2002
Luscar
8
18.3
94.12
23.5
4.4
97.1
2002
Luscar
10
22
100
64.3
3.6
100
2002
Luscar
12
15.7
82.35
47.1
66.7
52.9
C-39
-------
Year
Site
Female #
Se in eggs,
mg/kg ww
%craniofacial
deformities
%skeletal %finfold
deformities deformities
%edem
2002
Luscar
22
20.5
100
42.1
2.1
100
2002
Luscar
23
6.3
5.59
6.6
1.6
2.7
2002
Luscar
24
26.8
100
100
0
100
2002
Luscar
26
6.5
1.72
1.7
4.3
0.9
2002
Deerlick
10
5.9
5.65
7.26
7.26
3.23
2002
Deerlick
18
7.8
10.77
1.54
9.23
3.08
2002
Deerlick
21
5
6.9
6.9
20.69
1.72
2002
Deerlick
24
4.3
2.88
2.88
21.58
0.72
2002
Deerlick
25
4.4
5.3
5.3
6.82
3.03
2002
Deerlick
26
6.6
2.95
1.85
1.11
1.85
2002
Gregg
1
5.8
4.76
3.81
3.81
3.81
2002
Wampus
1
3
18.84
14.49
72.46
11.59
2002
Wampus
2
4
0
0
100
100
2002
Wampus
3
4.6
4.1
3.28
7.58
0.61
2002
Wampus
4
4.7
25
20
70
12.5
2002
Luscar
28
7
19.23
0
76.9
0
C-40
-------
Table 2. Brook trout embryo-larval parameters collected from a high Se site (Luscar Creek), an
intermediate Se site (Gregg River), and reference site (Cold Creek) in northeastern Alberta over
three consecutive years.
Year Location Female # Se in egg, mg/kg %craniofaci %skeletal %finfold %edema
2000
Luscar
1
4.78
15.38
0
0
15.38
2000
Luscar
2
4.83
38.06
1.49
3.73
1.49
2000
Luscar
3
5.98
7.39
3.03
0.34
0.5
2000
Luscar
5
3.86
25
5.7
8.77
4.82
2000
Luscar
12
6.06
16.77
1.83
0.7
0
2000
Luscar
13
5.8
4.06
1.42
0.2
0
2000
Luscar
14
5.17
4.13
0.49
0.36
0.12
2000
Luscar
15
9.92
16.22
0.54
0.54
0
2000
Luscar
16
5.03
5.61
0
0.27
0.27
2000
Luscar
17
6.01
9.44
5.83
0.83
1.11
2000
Luscar
18
12.7
14.34
0.72
0
0.36
2000
Cold
21
1.15
3.26
1.48
0.89
0
2000
Cold
22
1.83
4.83
1.38
1.38
0.69
2000
Cold
24
0.97
1.67
0
0.72
0
2000
Cold
25
No data
3.31
1.1
1.66
1.1
2000
Cold
26
0.59
3.45
4.83
6.9
0.69
2000
Cold
33
1.35
6.15
0
1.54
0
2000
Cold
34
2.18
6.45
0
0.81
0
2001
Cold
6
1.79
0
0
0
0
2001
Cold
7
1.36
1.61
0.69
0.46
1.38
2001
Cold
8
0.94
1.36
0
0.27
0.54
2001
Cold
21
1.07
0.43
0
0
0
2001
Cold
51
1.09
0
2.13
0
6.38
2001
Luscar
3
8.4
0
0.93
0
0.46
2001
Luscar
7
7.26
1.35
1.62
0.81
0.27
2001
Luscar
17
14.6
2.22
0.63
0.32
0
2001
Luscar
19
9.79
7.55
2.11
2.42
0.3
2001
Luscar
59
5.8
2.28
0.46
0.91
0.46
2001
Luscar
60
9.03
3.16
0
1.05
1.05
2001
Luscar
61
7.29
0
0
9.09
0
2001
Luscar
64
7.08
1.54
2.19
0
0
2001
Luscar
76
7.1
36.71
13.29
19.65
1.16
2001
Luscar
82
6.06
1.11
0.22
0.88
0.44
2001
Luscar
83
5.82
6
2
5.6
0.8
2001
Gregg
3
7.08
6.32
1.58
20.53
1.58
2001
Gregg
22
7.95
0
0
1.08
0
2001
Gregg
23
9.23
0.5
0.5
2.51
0
2001
Gregg
25
6.46
0.56
0
0.56
0
C-41
-------
Year Location Female # Se in egg, mg/kg %craniofaci %skeletal %finfold %edema
2001
Gregg
2001
Gregg
2001
Gregg
2001
Gregg
2002
Luscar
2002
Luscar
2002
Luscar
2002
Luscar
2002
Luscar
2002
Luscar
2002
Luscar
2002
Luscar
2002
Gregg
2002
Gregg
2002
Gregg
2002
Cold
2002
Cold
2002
Cold
2002
Cold
2002
Cold
2002
Cold
2002
Cold
2002
Cold
2002
Cold
2002
Cold
31
7.35
32
4.91
33
7.02
34
5.01
17
6.28
23
5.27
26
6.36
38
18.9
42
4.95
44
6.47
54
7.96
56
18.8
25
6.27
37
4.58
39
6.67
32
0.42
26
0.89
2
0.94
5
1
29
1.02
23
1.2
48
1.25
42
1.6
22
1.74
51
2.11
0.51
1.7
7.21
0.48
1.88
1.88
0
0.37
1.7
12.74
7.34
0.46
1.81
0.52
0.9
0.54
2.79
0.44
0
0.25
0.33
0.33
3.99
0.75
1.23
1.23
2.99
0
3.57
1.19
0
0.6
0
0
0.96
0.32
0.25
0.5
0.72
1.09
0.35
0.35
9.52
4.76
0
0
0
0
2.17
2.17
0.17
0
3.37
0.48
4.38
0
0
0
0.85
0.21
0
0.46
0.26
0.26
0
0.18
0.15
0.15
0
0
0
0
0.5
0.75
0
0
0
0
1.19
1.19
0
0
0
0.29
0
0
0.25
0
0.36
0.72
0.35
0.35
2.38
0
0
0
1.09
1.09
0
2.17
C-42
-------
Table 3. Results of ANOVA comparing rainbow trout endpoints among sites
% fertilization
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
77.60
25.8653
0.06336703
0.978935
Residuals
51
20817.33
408.1829
% mortality
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
3751.51
1250.504
1.848008
0.1502207
Residuals
51
34510.50
676.676
% craniofacia
deformities
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
8093.97
2697.989
4.430272
0.007732133
Residuals
50
30449.48
608.990
% skeletal deformities
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
3279.30
1093.101
2.773923
0.05094422
Residuals
50
19703.16
394.063
% finfold deformities
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
6273.17
2091.056
3.888612
0.01417887
Residuals
50
26886.93
537.739
% edema
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
8902.51
2967.502
3.449597
0.0233558
Residuals
50
43012.30
860.246
C-43
-------
Table 3. Results of ANOVA comparing rainbow trout endpoints among sites (continued)
Fry length
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
5.0847
1.694896
0.5694271
0.6377436
Residuals
50
148.8246
2.976493
Fry weight
Df
Sum of Sq
Mean Sq
F Value
Pr(F)
Site
3
1721.104
573.7012
3.563888
0.02080915
Residuals
48
7726.859
160.9762
Table 4. Rainbow trout means (standard deviation) for measurements made in eggs, embryos and
larvae spawned from fish collected at exposed sites (Luscar and Gregg Creeks) and reference sites
(Deerlick and Wampus Creeks).
Parameter
Site
Luscar Cr.
Gregg Cr.
Deerlick Cr.
Wampus Cr.
egg Se, mg/kg ww
9.93 (6.77)
6.52 (4.11)
3.49 (1.90)
3.5 (1.09)
fertilization, %
77.8 (20.3)
81.2 (12.7)
77.5 (20.9)
77.5 (24.1)
mortality, %
35.0 (29.5)
34.2 (32.5)
18.1 (14.6)
37.3 (34.5)
craniofacial, %
33.3 (37.2)
10.6 (6.5)
7.1(6.1)
12.0 (9.6)
skeletal, %
25.0(27.9)
9.9 (5.8)
9.2 (12.3)
7.9 (8.2)
finfold, %
15.0(27.1)
13.6 (15.2)
5.4 (6.2)
42.2 (43.7)
edema, %
34.5 (40.3)
12.2 (12.3)
6.1 (7.3)
23.3 (37.8)
larval length, mm
18.5 (2.0)
19.4 (1.6)
19.0 (1.5)
19.2 (0.9)
larval weight, mg
53.3 (16.3)
44.6 (10.4)
41.2 (9.3)
40.6 (8.4)
C-44
-------
Table 5. Brook trout means (standard deviation) for measurements made in eggs, embryos and
larva spawned from fish collected at exposed sites (Luscar and Gregg Creeks) and
Parameter
Site
Luscar Cr.
Gregg Cr.
Cold Cr.
egg Se, mg/kg ww
7.78 (3.80)
6.59 (1.39)
1.26 (0.47)
fertilization, %
92.8 (7.2)
78.4(18.2)
89.1 (19.6)
mortality, %
6.5 (8.9)
2.9 (2.3)
6.9(12.1)
craniofacial, %
7.9 (10.1)
2.3 (2.5)
2.1 (2.6)
skeletal, %
2.0 (3.3)
0.8 (0.7)
1.0(1.4)
finfold, %
1.9 (4.1)
3.1 (6.0)
0.9(1.5)
edema, %
1.0 (2.9)
0.3 (0.6)
0.7(1.4)
larval length, mm
17.4 (1.1)
17.9(0.9)
18.5 (1.2)
larval weight, mg
31.7 (8.6)
31.3 (5.4)
37.8 (7.2)
% fertilization
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
1683.3
841.67
3.9128
0.0253
Residuals
60
12906.4
215.11
% mortality
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
131.4
65.72
0.7257
0.4882
Residuals
60
5433.6
90.56
% craniofacial deformities
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
519.1
259.54
4.9427
0.0103
Residuals
60
3150.6
52.51
C-45
-------
Table 6. Results of ANOVA comparing brook trout endpoints among sites (continued)
% skeletal deformities
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
19.2
9.58
1.5631
0.2179
Residuals
60
367.6
6.13
% finfold deformities
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
37.5
18.74
1.2562
0.2921
Residuals
60
895.1
14.92
% edema
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
4.6
2.32
0.4966
0.6110
Residuals
60
280.6
4.68
Fry length
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
16.1
8.04
6.5265
0.0027
Residuals
60
73.9
1.23
Fry weight
df
Sum of Sq
Mean Sq
F Value
Pr(F)
site
2
546.2
273.10
4.6644
0.0131
Residuals
60
3512.9
58.55
C-46
-------
100'
80 ¦
CO
0)
'-I—'
'E
o
4—
CD
Q
CC 60 -
o
cc
£
O
o
o
40 -
20 -
• •
„ •
- • «
.• V v.
10
20
mg Se/kg egg
Figure 1. Rainbow trout percent normal (100 - % craniofacial deformities) as a function of the
logarithm of selenium concentration in eggs wet weight (Exposure Variable). TRAP weighted
regression analysis using a threshold sigmoid equation. The background value was estimated to be 90.2%,
the slope 4.8%, and the ECio 10.2 mg Se/kg egg ww.
100 i
(/)
U
~ 80
60
-------
1 2 5 10 20
mg Se/kg egg
Figure 3. Rainbow trout percent normal (100 - % edema) as a function of the logarithm of selenium
concentration in eggs wet weight (Exposure Variable). TRAP weighted regression analysis using a
threshold sigmoidal equation excluding the one outlier with 100% edema at 4 mg/kg. The background
value was estimated to be 92.8%, the slope 4.6%, and the ECi0 9.5 mg Se/kg egg ww.
The previous draft used a TRAP logistic regression (Figure 4). A weighted regression using a threshold
sigmoidal equation (Figures 1-3) is a better application of these data.
120
in
-------
Figure 5. Plot of percent abnormal for craniofacial, skeletal and finfold deformities and edema
against selenium concentration in brook trout eggs ww, 2000 and 2001 data.
• ~
vtro
.'¦Vm *
w
.a;
H—I
E
L_
>2
a;
CD
-i—»
a;
w
14 1
12 -
10 -
8 -
6 -
V
4 -
2 -
o
¦
0 -
Vom
v©o
8 10 12 14 16
8 10 12 14 16
8 10 12 14 16
Egg Se concentration
(ing/g, wet weight)
7 i
6 -
5 -
£4 ¦
CD
E 3H
0
B 2 -
1 -
0 -
•
Luscar 2001
o
Cold 2001
~
Gregg 2001
V
Cold 2000
¦
Luscar 2000
~
• •
^ . T. . • #
woan tWw ~
—i 1—
0 2
8 10 12 14 16
Egg Se Concentration
(ing/g, wet weight)
C-49
-------
The effect levels determined using the within streams approach resulted in values based on ww in eggs.
The primary tissue for which the reproductive effect levels were based, eggs, was converted from ww to
dw using the average percent moisture of 61.2% for rainbow trout eggs reported by Seilor and Skorupa
(2001).
Chronic Values: Brook trout: Between streams approach
No effects at ECi0 level at 7.78 mg Se/kg eggs ww or 20.05 mg Se/kg eggs dw;
egg. Chronic value is >20.05 mg Se/kg eggs dw. Table 3 data, converted to dry
weight, suggest no effects at least up to 25-35 mg Se/kg eggs dw.
Rainbow trout: Within streams approach
ECio value (edema) at 9.5 mg Se/kg egg ww or 24.5 mg Se/kg egg dw. Chronic
value is 24.5 mg Se/kg eggs dw.
C-50
-------
Kennedy, C.J., L.E. McDonald, R. Loveridge, M.M. Strosher. 2000. The effect of bioaccumulated
selenium on mortalities and deformities in the eggs, larvae, and fry of a wild population of cutthroat trout
(Oncorhynchus clarkii lewisi). Arch. Environ. Contam. Toxicol. 39:46-52.
Cutthroat trout (Oncorhynchus clarkii lewisi; spawning adults, 3-6 years)
Dietary and waterborne - field exposure
Total selenium concentrations measured at the time the eggs were taken were
<0.1 |jg/L from the reference site and 13.3 to 14.5 |a,g/L at the exposed site.
At reference and exposed site (Fording River, BC, Canada which receives
drainage from open-pit coal mining), eggs were stripped from females (n=20
from reference site; n=17 from exposed site) and fertilized from milt from one
male collected at each site. Fertilized eggs were reared in well water and
examined for time to hatch, deformities (craniofacial, finfold, skeletal and yolk
sac malformations), and mortalities. Inspection of deformities in eggs was
performed using 40X magnification.
No significant correlations between the selenium concentrations in the eggs from
either site and: hatching time (reference, 25.5-26.5 days; exposed, 22-25.5 days);
percent deformities preponding (reference, 0-2.4%; exposed, 0-0.34%); percent
deformities after ponding (reference, 0-0.26%; exposed, 0-0.09%); percent
mortalities preponding (reference, 1.5-70.3%; exposed, 1-100%); percent
mortalities after ponding (reference, 0.3-4.3%; exposed, 1.5-43.7%); total percent
mortalities (reference, 2.8-55.8%; exposed, 3.7-100%). The average selenium
residues in tissues were as follows:
Site
Adult fish liver, mg Se/kg
dw
Adult fish muscle, mg Se/kg
dw
eggs, mg Se/kg dw
Reference
8.2; Range: 3.4-14.6
2.4; 1.4-3.8
4.6
Exposed
36.6; Range: 18.3-114
12.5; Range: 6.7-41
21.2
Chronic Value: >21.2 mg Se/kg dw in eggs
>12.5 mg Se/kg dw in muscle
C-51
Test Organism:
Exposure Route:
Study Design:
Effects Data
-------
Hardy, R.W. 2005. Effects of dietary selenium on cutthroat trout (Oncorhynchus clarkii) growth and
reproductive performance. Report for Montgomery Watson Harza. December 14, 2005.
Test Organism: Cutthroat trout (Oncorhynchus clarkii, 0.9 g)
Exposure Route: Dietary only
Six experimental dietary treatments were produced by cold extrusion. The
formulation of the diet was designed to be similar to commercial trout diets and
had a proximate composition of 45% protein and 16% lipid. Seleno-methionine
diluted in distilled water (100 j^ig/L) was added in appropriate volumes to each
batch of feed to facilitate pelleting. Measured dietary selenium concentrations
were 1.2 (control), 3.8, 6.4, 9.0, 11.5, and 12 mg Se/kg dw. Fry were fed initially
at a rate of 10 times per day 6 days each week to apparent satiation. Feeding
frequency decreased as fish grew.
Test Duration: 124 weeks (865 days, 2.5 yrs)
Study Design: Groups of 50 fish were placed into triplicate tanks (145 L) receiving 4-15 L/min
of hatchery water at 14.5EC and fed one of the six experimental diets. The fish in
each tank were bulk-weighed and counted every 14 days for the first 12 weeks of
the experiment, and then every 4 weeks until 48 weeks. Samples of fish for
whole-body selenium analysis were taken at each sampling date for the first 12
weeks followed by every 3 months thereafter. After six months of feeding, the
fish were transferred to 575 L tanks and the number of replicate tanks per dietary
treatment was reduced to two. After 80 weeks of feeding, the fish were
transferred to 1050 L outdoor tanks each supplied with 70 L/min of constant
temperature (14.5°C) spring (hatchery) water. After 2.5 years of the feeding trial,
fish were spawned and whole body selenium level, egg selenium level, % eyed
eggs, % hatched eggs, and % deformed larvae were examined.
Effects Data: No signs of toxicity (reduced growth or survival relative to controls) were
observed in fish fed the highest dietary selenium treatment (12 mg Se/kg dw)
after the first 80 weeks of exposure just prior to transfer outdoors. No signs of
clinical disease were evident, and no relationship was found between feed
conversion ratios and the level of selenium added to the feed. Average whole
body selenium levels of female Henry's Lake cutthroat trout at spawning at 2.5 to
3 years of age were 5.87, 9.10, 11.37 and 5.61 mg Se/kg dw in the four highest
dietary treatments. Average egg selenium levels in the same four dietary
treatments were 6.61, 5.05, 5.18, and 16.04 mg Se/kg dw. Percent survival from
the eyed stage to hatching varied among treatment groups, with the control and
the highest Se dietary treatment having the second highest survival (85%) and the
fifth dietary treatment group the highest (93%). Percent deformed larvae ranged
from a low of 5.6% in controls to a high of 20.2% in the 6.4 mg Se/kg dw dietary
treatment group; larvae in the two highest dietary treatment groups only
exhibited 7 and 6.8 %, respectively.
Chronic Value: The chronic value for embryo/larval deformity is aNOAEC of >11.37 mg Se/kg
dw whole-body parent tissue and >16.04 mg Se/kg dw egg.
C-52
-------
Rudolph, B-L, I. Andreller, CJ. Kennedy. 2008. Reproductive success, early life stage development,
and survival of Westslope cutthroat trout (Oncorhynchus clarkii lewisi) exposed to elevated selenium in
an area of active coal mining. Environ. Sci. Technol. 42: 3109-3114.
Test Organism: Westslope cutthroat trout (Oncorhynchus clarkii lewisi)
Exposure Route: Field collected.
In June, 2005, eggs were collected from 12 females from Clode Pond (exposed
site) and 16 females from O'Rourke Lake (reference site). Milt was obtained
from 3-5 males at each site. Clode Pond is on the property of Fording River Coal
Operations in Southeast British Columbia with reported selenium concentrations
of 93 (ig/L. O'Rourke Lake is an isolated water body into which Westslope
cutthroat trout were stocked in 1985, 1989 and 1992 and has selenium levels
reported <1 |_ig/L.
Test duration: Through the end of yolk sac absorption (at swim-up) by the alevins.
Study Design: Individual batches of eggs were fertilized in the field with 2 ml composites of
milt. Water-hardened eggs were transported to the rearing laboratory. Eggs and
alevins were monitored daily for fertilization, hatching and mortality. After the
yolk sacs were absorbed, alevins were sacrificed and preserved in Davidson's
solution.
All viable fry (n = 4,922) after yolk absorption were observed for the frequency
and severity of skeletal (lordosis, kyphosis, and scoliosis), craniofacial (head,
eyes or jaw), and fin malformations as well as edema. The authors used a
graduated severity index (GSI) for deformities in which fry were scored 0
(normal) to 3 (severe) based on the level of defect.
Effects Data: Eggs with the four highest Se concentrations (86.3 to 140 mg/kg dw) collected
from Clode Pond fish died before reaching the laboratory (Table 1). Excluding
the eggs that died from females CP1, CP3, CP4 and CP5, fertilization (total eggs
reaching the eyed stage/total eggs x 100) was not related to Se concentrations in
the eggs. The percent of alevins (post hatch to swim-up stage) that died was
related to the selenium concentration in the eggs (Table 1). Note: The data used
to estimate the ECi0 value excluded the variable from OL1 and OL2 (shaded
areas in Table 1). These are data from the reference lake in which only 57% of
the larvae survived (OL1) or where the % dead eggs plus % hatch did not add up
to % 100. Alevin survival was meaningfully higher in the other 15 clutches of
eggs from the reference site (85.1 to 99.8%). Because there were insufficient
partial effects, a TRAP model was not used to estimate the ECi0 value. The data
consist of a cluster background data and a cluster of 100% mortality (Figure 1).
With no way to fit a credible curve, the interpolation method is applied here with
the EC0 set to 20.6 mg/kg with background % survival of 95.75% (not including
the one low outlier) and the second extrapolation point being 46.8 mg/kg with
0.3% survival. The resultant slope is 5.6 (similar to slopes in other datasets where
it was estimated) and the ECio is 24.7 mg/kg. Note: TRAP was used in the
previous draft to derive a similar ECi0 of 24.1 mg/kg, however as stated above, it
C-53
-------
was determined that the data are not amenable to a TRAP model because of
insufficient partial effects.
An ECio based on Se in maternal muscle was estimated using the same approach
as was used for Se in eggs, that is, by interpolation between an EC0 and a high
ECP. An EC 10 of 16.6 mg Se/kg muscle dw was interpolated from an EC0
(HNOEC) of 13.4 mg/kg and the average background survival of 95.75 and the
ECioo set to 34.7 mg/kg muscle (Figure 2).
Deformity analysis was not performed on the alevins that died prior to the swim-
up stage. Therefore, due either to dead eggs or dead alevins, the occurrence and
severity of deformities were assessed on four clutches of eggs from Clode Pond
(CP2, CP6, CP11 and CP 12) with a range of 11.8 to 20.6 :g Se/g dw and 15 of
the 16 clutches (all eggs died in OL8) from O'Rourke Lake (Table 1). There was
no correlation between egg Se concentration and frequency of deformity or
edema. Statistical differences between sites were observed (p < 0.05) for skeletal
deformities and edema for both the frequency of the occurrence and the severity
score (Table 2). Note: the percent and severity score of skeletal deformities were
greater in the reference site than in the exposed site.
The effect level for this study was based on the alevin mortality data and not the
deformity measurements. Although edema occurred statistically more often at the
exposed site (87.7% at Clode Pond, 61.2% at O'Rourke Lake), it was not
correlated with selenium levels in the eggs. Also the greater occurrence of
skeletal malformations in the reference site confounded the use of statistical
differences between sites to determine effect levels for this study.
Effect Concentration: 24.7 mg Se/kg dw in eggs; 16.6 mg Se/kg dw in muscle.
C-54
-------
Table 1. Fertilization, egg mortality and alevin mortality for offspring from individual fish
collected in Clode Pond and O'Rourke Lake.
Muscle [Se]
Egg [Se]
Dead
Dead
%
Fish ID
mg/kg dw
mg/kg dw
Hatch %
eggs, %
alevins, %
Survivj
Clode Pond
(exposed site)
CP1
38.8
88.3
0
100
NA
CP2
11.8
16.1
98.2
1.8
0.9
99.1
CP3
40.4
86.3
0
100
NA
CP4
46.1
121
0
100
NA
CP5
50.4
140
0
100
NA
CP6
34.7
51
92.6
7.4
92.6
0.0
CP7
39
65.3
91.1
8.9
91.1
0.0
CP 8
7
11.8
63.9
36.1
0.8
98.7
CP9
35.4
46.8
63.4
36.6
63.2
0.3
CP10
35.5
75.4
82.4
17.6
82.4
0.0
cpii
11.3
16.9
77.9
22.1
1.3
98.3
CP12
13.4
20.6
97
3
5.1
94.7
avg
30.3
61.6
55.5
44
42
20.0
SD
15.1
42.4
42.5
42
44
0.0
O'Rourke Lake
(reference site)
Oil
s :x
i: <)
71.4
:x h
42 w
39.9
oi.:
7.7
13 w
27.7
53 I
<•> <¦)
75.1
OL3
8.16
12.5
96.1
3.9
2.4
97.5
OL4
8.03
15
85.5
14.5
12.7
85.1
OL5
8.12
14.9
80.7
19.3
5.3
93.4
OL6
6.61
15.2
68
32
4
94.1
OL7
8.52
12.9
97.9
2.1
0.2
99.8
OL8
7.22
12.3
0
100
NA
OL9
7.25
16.7
87.2
12.8
4.5
94.8
OLIO
7.64
13.1
79.6
2.5
5.5
93.1
OL11
8.74
15.6
89.2
10.8
2.4
97.3
OL12
8.2
13.9
83.6
16.4
3
96.4
OL13
7.86
15.1
74.1
25.9
2.8
96.2
OL14
8.5
13.1
77.8
22.2
0.5
99.4
OL15
7.62
12.3
88.2
11.8
2.6
97.1
OL16
8.13
12.7
54.8
45.2
4.8
91.2
avg
7.9
13.9
72.6
25
7
SD
0.6
1.4
25.8
25
10
1 % Survival based on % hatch
C-55
-------
Table 2. Deformity results (frequency and severity) for offspring from O'Rourke Lake and Clode
Pond. Values are presented as mean ± SE. * indicates a significant difference (p < 0.05) between means
from the two sites.
Frequency of deformity, %
O'Rourke Lake
Clode Pond
Skeletal*
37.4 ±3.6
16.5 ±2.2
Craniofacial
10.2 ±2.0
5.7 ± 1.0
Finfold
10.6 ±3.1
7.5 ±3.84
Edema*
61.2 ±4.9
87.7 ±2.0
Severity of deformity, score
Skeletal*
0.47 ±0.07
0.18 ±0.02
Craniofacial
0.12 ±0.03
0.06 ±0.01
Finfold
0.15 ±0.05
0.09 ±0.05
Edema*
0.61 ±0.05
0.88 ±0.02
CD
>
w
100 -
80 -
60 -
40 -
20 -
10
20
50
—1
100
mg Se/kg dw egg
Figure 1. Post-hatch survival of Westslope cutthroat trout alevin as a function of the logarithm of
the selenium concentration in eggs.
C-56
-------
100
80
<0
> 60
W
5- 40
20
—i—
10
—i—
20
50
mg Se/kg muscle dw
Figure 2. Post-hatch survival of Westslope cutthroat trout alevin as a function of the logarithm of
the selenium concentration in maternal muscle.
C-57
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Nautilus Environmental. 2011. Evaluation of the Effects of Selenium on Early Life Stage Development
of Westslope Cutthroat Trout from the Elk Valley, BC. Report to Elk Valley Selenium Task Force,
November 24, 2011.
Test Organism: Westslope cutthroat trout (Oncorhynchus clarkii lewisi)
Exposure Route: Field collected. Adult fish were collected and spawned from lentic and lotic
environments in areas proximate to Teck Coal's Fording River Operations. Eggs
were also obtained from fish collected from Connor Lake, a lake located within
the Elk valley watershed not exposed to mine discharges and considered a
reference site and a methodological control.
Test Duration: Fertilized eggs were reared in the laboratory until they reached swim-up fry
stage. A subset of fry surviving at swim-up were reared for an additional 28 days.
Study Design: Gametes were stripped from the ripe adults in the field during June and July 2008
and transported immediately to the laboratory in coolers containing wet ice. Eggs
were fertilized in the laboratory. After stripping the eggs, female fish were
sacrificed and the whole body stored on ice for later Se analysis. For a given
female, approximately 240 fertilized eggs were divided into four replicates of 60
eggs. In cases when fewer eggs were available three replicates of 60 eggs were
used. If less than 180 eggs were available, either 3 or 4 replicates of 30 were
used. Females with less than 90 eggs were not used. The fertilized eggs were
maintained in the laboratory until the fry reached swim-up at which point
deformities were assessed. Survival was also assessed up to swim-up. In test
chambers in which there were at least 40 surviving fish at swim-up, one-half of
the surviving fish were maintained for an additional 28 days. Survival, length,
weight and deformities were assessed in the 28-day post swim-up test.
The number, type and severity of deformities were measured at swim-up and at
the end of the 28-day post swim-up test. Deformity assessments were conducted
on recently killed fresh fish to avoid artifacts caused by preservation. A
graduated severity index (GSI) was assigned to each of four types of
deformity/abnormality: skeletal, craniofacial, finfold and edema. Graduated
Severity Index (GSI) methods followed those described in Holm et al. (2003) and
Rudolph et al (2006; 2008).
Effects Data: Survival of the larvae from hatch through swim-up spawned from the four fish
collected from the reference site, Connor Lake, ranged from 73 to 92% (egg Se
4.32 to 7.31 mg/kg dw) (Table 1). Larval survival at swim-up was also generally
high for fish collected in the Se exposed sites up to egg Se concentration 29.6
mg/kg dw (Table 1, Figure 1). Larvae exposed above this egg Se concentration
had poor to no survival. Larvae from one fish (P00811) below this threshold did
have poor survival (11.7%). The authors noted that the many of the eggs from
this fish displayed an unusual distribution of lipid vesicles which resulted in
greater than 50% mortality in the first 24 hours due to egg breakage. The
remaining eggs may have been compromised due to the organic material released
during the egg breakage.
C-58
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The rate of deformities in larvae at swim-up showed no relationship with Se in
egg through 29.6 mg/kg dw (Table 2).
The results of the 28-day post swim-up test showed no relationships between
larval survival or deformities and egg Se (Table 3). The authors also measured
the length and weight of larvae at the end of the 28 day test; neither of which
showed a relationship with egg Se concentration.
Se Tissue Concentrations. Two analytical laboratories (A and B) measured Se in
the eggs. The mean difference in egg Se concentrations between the two
laboratories was 34.2%. To better understand the difference between the two
laboratories, five egg samples (i.e., from five different fish) from this study were
sent to both laboratories in 2010. Both laboratories digested the eggs using the
methods they used in their own 2008 original analysis. The respective digestates
were split and then shared between laboratories. Both labs then measured
selenium in their own digestates and the digestate received from the other lab.
The results of this follow-up study showed that when each lab used their own
digestion procedures Laboratory A had on average 43% higher measurements in
the 2008 analysis and 23% higher in the follow-up 2010 analysis. When each lab
measured selenium using the same digestate the difference in the Se
measurements between labs was on average only 1 to 8%. The authors concluded
that although both laboratories employed acceptable and approved practices,
Laboratory A used a more efficient digestion process resulting in higher Se
measurements. To compensate for the reduced Se measurements in Laboratory B,
its values were increased by 34.2%. The measurements made by Laboratory A
are marked in Table 1; unmarked values are Laboratory B measurements
increased by 34.2%.
Effect Concentration: The most sensitive endpoint determined by TRAP was larval survival at swim-
up. Interpolation was used to estimate an effect concentration for larval survival
with the entire egg Se dataset that included egg Se measurements from
Laboratory A and adjusted measurements from Laboratory B (ECi0 = 31.1 mg/kg
egg dw; Figure 1) and using only the egg Se measurements from Laboratory A
(Figure 2). Because the Laboratory A dataset estimated slightly lower EC values,
the ECio of 27.7 mg/kg egg dw is the selected effect concentration for this study.
Note: In the previous draft, a TRAP model was used to estimate the ECi0.
However, because of insufficient partial effects, TRAP was determined not
appropriate so the ECi0 was estimated using an interpolation between the
HNOEC and the LOEC (see Figure 3 for the TRAP analysis used in the previous
draft).
C-59
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Table 1. Summary of westslope cutthroat trout larvae surviving to swim-up per parent female (fish
ID) including location of collection of parent female and concentration of selenium in the eggs.
Proportion surviving
Se egg, Replicate Replicate Replicate Number Total
Fish ID
Location
mg/kg dw
Replicates
mean
min
max
survivors
number
Y093
Lentic
3.88*
4
0.8125
0.6667
0.9167
195
240
CL1
Reference
4.32
4
0.9167
0.8833
1
220
240
R082
Lotic
5.21
3
0.9056
0.8333
0.95
163
180
CL4
Reference
5.96*
4
0.7333
0.6
0.8
176
240
CL2
Reference
6.82
4
0.8333
0.7
0.9167
200
240
CL3
Reference
7.31
4
0.8542
0.8167
0.8833
205
240
P00815
Lotic
7.6
3
0.8222
0.7167
0.95
148
180
R026
Lotic
12.53
4
0.5792
0.5
0.65
139
240
P00823
Lotic
12.71
4
0.8875
0.85
0.95
213
240
R039
Lotic
12.9
4
0.6042
0.55
0.65
145
240
R086
Lotic
13.4*
4
0.9417
0.85
0.9833
226
240
R077
Lotic
14.29
3
0.6444
0.6167
0.6667
116
180
R042
Lotic
16.44
3
0.8
0.7
0.9
72
90
R055
Lotic
16.5
4
0.8792
0.7833
0.9667
211
240
R043
Lotic
16.85
4
0.8667
0.7667
0.9667
104
120
R074
Lotic
17.8*
4
0.9375
0.8833
0.9833
225
240
P00811
Lotic
19.25
1
0.1167
0.1167
0.1167
7
60
P00809
Lotic
19.72
4
0.7667
0.65
0.8833
184
240
P00803
Lotic
24.8*
4
0.9375
0.9333
0.95
225
240
R078
Lotic
29.61
4
0.8825
0.8333
0.9333
105
119
G099
Lotic
34.2*
4
0.2083
0.1667
0.2667
50
240
0087
Lentic
54.7*
4
0.07083
0.01667
0.2
17
240
0085
Lentic
56.8*
4
0
0
0
0
240
W052
Lentic
61.1*
4
0
0
0
0
240
R069
Lotic
65.61
4
0
0
0
0
240
R071
Lotic
72.9
4
0
0
0
0
240
W094
Lentic
73.1
4
0
0
0
0
240
UT101
Lentic
74.67
4
0
0
0
0
240
*Laboratory A dataset
C-60
-------
Table 2. Summary of westslope cutthroat trout larval deformities to swim-up per parent female
(fish ID) including location of collection of parent female and concentration of selenium in the eggs.
Fish ID
Location
Se egg,
mg/kg dw
Skeletal
combined
Craniofacial
combined
Finfold
combined
Edema
combined
Deformities
combined
Y093
Lentic
3.88*
4.5%
0.9%
4.4%
1.9%
7.7%
CL1
Lentic
4.32
7.6%
1.9%
1.0%
1.0%
9.5%
R082
Lotic
5.21
1.2%
1.3%
2.5%
0.0%
3.7%
CL4
Lentic
5.96*
4.3%
7.3%
1.7%
0.7%
12.6%
CL2
Lentic
6.82
11.1%
3.7%
0.8%
3.0%
15.9%
CL3
Lentic
7.31
5.0%
2.0%
1.0%
0.0%
7.0%
P00815
Lotic
7.6
0.0%
2.7%
0.0%
2.9%
5.6%
R026
Lotic
12.53
2.1%
2.1%
0.7%
1.4%
2.1%
P00823
Lotic
12.71
1.9%
2.9%
1.8%
5.6%
7.4%
R039
Lotic
12.9
2.1%
1.9%
2.9%
4.9%
9.9%
R086
Lotic
13.4*
2.7%
1.0%
0.0%
0.0%
2.7%
R077
Lotic
14.29
1.7%
10.4%
0.9%
12.2%
15.5%
R042
Lotic
16.44
1.2%
0.0%
0.0%
2.6%
2.6%
R055
Lotic
16.5
0.0%
2.8%
1.0%
2.9%
4.7%
R043
Lotic
16.85
0.9%
2.6%
1.8%
1.7%
4.4%
R074
Lotic
17.8*
2.7%
1.8%
0.9%
0.9%
3.6%
P00809
Lotic
19.72
3.9%
2.8%
3.3%
4.7%
9.0%
P00803
Lotic
24.8*
2.7%
0.9%
0.0%
0.9%
4.5%
G092
Lotic
26.1
0.0%
1.9%
1.9%
4.4%
4.4%
R078
Lotic
29.61
1.8%
0.0%
1.0%
2.9%
5.7%
G099
Lotic
34.2*
14.5%
53.9%
6.8%
28.2%
64.7%
*Laboratory A dataset
C-61
-------
Table 3. Summary of larval survival and rates deformities after the 28-day post swim-up test per
parent female (fish ID) including location of collection of parent female and concentration of
selenium in the eggs.
Sample
Egg Se
Survival
Skeletal
Craniofacial
Finfold
Total
Fish ID
Location
size (n)
(mg/kg dw)
(%)
(%)
(%)
(%)
(%)
CL1
Reference
112
4.3
99.1
0
0
0
0
CL2
Reference
93
6.8
99
0
0
0
0
CL3
Reference
96
7.3
91.7
0
1
1
2
CL4
Reference
68
6
98.6
0
0
4.3
4.3
Y093
Lentic
93
3.9
95.6
0
0
2
2
R082
Lotic
71
5.2
87.4
0
2.9
0
2.9
P00815
Lotic
69
7.6
91.1
0
1.2
1.4
2
P00823
Lotic
105
12.7
96.3
0
0
0
0
R086
Lotic
112
13.4
97.2
0
0.9
0
0.9
R077
Lotic
36
14.3
92.4
2.8
2.8
2.8
4.2
R055
Lotic
101
16.5
95.9
0
4.6
0
4.6
R074
Lotic
106
17.8
93.1
0
0
0
0
P00809
Lotic
65
19.7
91.7
0
0
0
0
P00803
Lotic
108
24.8
95.7
0
0
1
1
100-
mg Se/kg egg
Figure 1. Labs A and B datasets. EC10 based on interpolation between the one partial effect (34.2
mg/kg, 20.8%) and an ECO set at the HNOEC and the average % survival for all the NOECs (29.6
mg/kg and 81.1%). The slope is 20.5 and the EC 10 is 31.1 mg/kg. Note: the gray point denotes egg
batch with quality problems noted by authors and was not used in the analysis.
C-62
-------
100 -
mg Se/kg egg
Figure 2. Lab A dataset.* EC10 based on interpolation between the one partial effect (34.2 mg/kg,
20.8%) and an ECO set at the HNOEC and the average % survival for all the NOECs (24.8 mg/kg
and 87.25%). The slope is 9.4 and the EC10 is 27.7 mg/kg.
*Although some scientists have attempted to explain certain occurrences of improved response with
increasing concentration in terms of nutrient selenium sufficiency-deficiency, the concentrations involved
in this study are too high to for selenium deficiency to be an explanation. The figure's apparent bi-phasic
measured response is thus best explained as being a chance outcome of noise.
C-63
-------
1.1
1.0
.9
.8
.7
.6
.5
.4
.3
.2
0
.4
.6
.8
1.0
1.2
1.4
1.6
1.8
2.0
Log(Se egg), mg/kg dw
Figure 3. (From previous draft) Tolerance distribution; Model option - Triangular distribution (3
parameter). Includes Laboratory "A" dataset only TRAP ECi0 estimate = 24.0 mg/kg.
C-64
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Golder Associates. 2009. Development of a Site-specific Selenium Toxicity Threshold for Dolly Varden
Char. Report to Northgate Minerals Corporation, PO Box 3519, Smithers, British Columbia. Report
Number 04-1421-101/2000.
Test Organism: Dolly Varden (Salvelinus malma)
Exposure Route: Field collected.
Adult Dolly Varden char were collected from reference (North Kemess Creek),
high Se exposure (Upper Waste Rock Ponds and Creek) and moderate Se
exposure (lower Waste Rock Creek) sites during September 22 to 24, 2008. Eggs
were stripped from females and fertilized with milt from males collected from the
reference site. Fertilized eggs were taken to the laboratory for testing.
Test duration: The test was terminated when 90% of the larvae reached swim-up, approximately
5 months after fertilization.
Study Design: Approximately 30 fertilized eggs were added to each replicate rearing container.
The number of replicates per female parent ranged from one to four depending
on the number of eggs available. Embryos were maintained in 4 L containers
with 3.5 L dechlorinated tap water in a static-renewal system (3 renewals
times/week) at 5°C. The condition of the embryos and alevins were observed
daily and any dead individuals were counted and removed. Test termination
occurred over a 3-day period during February 11 to 13, 2009. The hatched larvae
were sacrificed using an overdose of the anesthetic, clove oil. Individual length
and weight were measured on each fry, and deformity analysis was performed on
fresh unpreserved larval fish using 40X magnification.
A graduated severity index (GSI) was used for deformity assessment (skeletal,
craniofacial, and finfold as well as edema). The narrative criteria were the same
as used by Holm et al. (2005) and Rudolph et al. (2008).
Effects Data: Alevin survival was not related to Se concentration in the eggs (Table 1). Almost
all of the mortality occurred during the egg stage. Only 4 alevins died during the
study, 1 from Fish #19 and 3 from Fish #2, both females collected at an exposed
site. The prevalence of deformities increased sharply after the selenium egg
concentration exceeded 50 mg/kg dw (Table 1, Figure 1). The proportion of
Dolly Varden larvae with any type of deformity (skeletal, craniofacial, and
finfold as well as edema) as a function of the log of the selenium concentration in
the eggs using TRAP (logistic equation) produced an ECi0 value of 56.22 mg/kg
dw eggs (Figure 1).
C-65
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Table 1. Selenium concentration in the eggs of Dolly Varden char and the survival of alevins to the
swim-up stage and the proportion of larvae without any type of deformity.
Survival of eggs to swim- Proportion of
[Se] up larvae
eggs without any
Fish
#
Sample
ID
Location
mg/kg
dw
Initial
End
%
type of
deformity
WRC-
1
F105
Waste Rock Creek
56.6
120
71
59
0.89
2
WRC-F61
Waste Rock Creek
65.8
120
81
68
0.58
WRC-
5
F103
Waste Rock Creek
32.6
29
29
100
0.97
6
WRC-F83
Waste Rock Creek
51.9
120
115
96
0.97
WRC-
15
F104
Waste Rock Creek
56.3
60
48
80
0.90
19
WRC-F86
Waste Rock Creek
60.5
120
115
96
0.72
9
NK-F30
North Kemess Creek
11
30
1
3
a
12
NK-F29
North Kemess Creek
10.5
46
15
33
1.00
17
NK-F21
North Kemess Creek
5.4
90
86
96
0.91
Southern Collection
SCD1
Redd # 1
Ditch
10.3
30
18
60
1.00
Southern Collection
SCD2
Redd #2
Ditch
24.7
40
32
80
1.00
C-66
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Figure C-l. Proportion of Dolly Varden alevin without any type of deformity as a logistic
function of the logarithm of the selenium concentration in eggs (TRAP).
1.2 r
E 1.0
o
O
CD
CO
O
o
o
Q_
O
r =0.933
1.0 1.2 1.4 1.6
Iog10 Egg Se (mg/kg dw)
2.0
Guess
Final
SE
95% LCL
95% UCL
LogX50
1.844
1.829
0.007
1.812
1.845
Slope
4.152
6.963
1.252
4.003
9.924
YO
0.975
0.980
0.017
0.939
1.021
ECx
EC
95% LCL
95% UCL
50
67.42
64.92
70.01
20
60.12
57.96
62.35
10
56.22
53.00
59.64
5
52.85
48.64
57.43
1
46.11
40.13
52.99
DF
SS
MS
F
P
Total
9
1.74E-01
1.93E-02
Model
2
1.63E-01
8.13E-02
51.429
0.99993
Error
7
1.11E-02
1.58E-03
C-67
-------
AECOM. 2012. Reproductive success study with brown trout (Salmo trutta). Data quality assurance
report. Final. December 2012.
Formation Environmental. 2011. Brown Trout Laboratory Reproduction Studies Conducted in Support
of Development of a Site-Specific Selenium Criterion. Prepared for J.R. Simplot Company by Formation
Environmental. Revised October 2011.
Test Organism: Brown trout (Salmo trutta)
Exposure Route: Field collected.
Adult female and male brown trout were collected at three field sites from two
streams downstream of the Smokey Canyon mine. In addition, brown trout eggs
were obtained from two hatcheries as method controls.
Test duration: Embryo-larval monitoring to 15 days post swim-up.
Study Design: Eggs were collected from 26 ripe female brown trout at three field sites
downstream of the Smokey Canyon mine. These included one site on the highly
impacted Sage Creek (LSV2C) as well as two sites along Crow Creek (CC-150
and CC-350) downstream of the conflux with Sage Creek. The downstream -
most station along Crow Creek (CC-150) was intended to be a field control. Eggs
were fertilized in the field with milt collected from males collected at the same
site as females. Fertilized eggs were water hardened at the site using stream
water, then placed in oxygenated plastic bags and stored on ice in the dark
(cooler) for transportation to laboratory. Selenium was measured in adult fish
(whole body) and in eggs of field collected females. In addition, eggs were
collected from 8 ripe females obtained from the Saratoga National Fish Hatchery
(SC) to serve as method controls. Similar to field-caught fish, SC hatchery
females were stripped of eggs and fertilized by milt from males obtained from
the same hatchery. As a result of lower than expected hatch rates and fungal
contamination in some SC hatchery samples, additional hatchery fish were
obtained (as already fertilized eyed embryos) from the Spring Creek Trout
Hatchery (SPC), which were divided into four treatments.
Approximately 600 fertilized eggs from each female (or 600 eyed embryos for
SPC treatments) were placed in egg cups for hatching and monitoring. After
swim up, remaining fry were thinned to a target of 100 fry/treatment and
monitored for an additional 15-day post swim up feeding trial. Test termination
ranged from 83 to 88 days after hatch for all but the Spring Creek Hatchery egg
treatments, which occurred 50 days after the arrival of fertilized, eyed embryos
from that hatchery.
Endpoints measured in the laboratory study were fecundity, hatch, growth,
survival/mortality, and feeding success (growth) post swim up. Larval brown
trout were also evaluated for deformities (craniofacial, vertebral, fin) and edema.
For this study, deformities were combined and assessed as having at least one
deformity, or being fully free of deformities (i.e., normal).
C-68
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Effects Data: Se concentrations in eggs ranged from 6.2-12.8 mg Se/kg dw at CC150, 6.9-14.0
mg Se/kg dw at CC350, and 11.2-40.3 mg Se/kg dw at LSV2C. Se
concentrations in hatchery eggs ranged from 0.76-1.2 mg Se/kg dw at the SC
hatchery, and were 0.73 mg Se/kg dw at the SPC hatchery. The Se whole body
concentration in field collected fish ranged from 7.2-22.6 mg/kg dw at LSV2C,
4.7-8.4 mg/kg dw at CC150, and 5.5-9.2 mg/kg dw at CC350. Se whole body
concentrations in SC hatchery fish ranged from 2.5-4.3 mg/kg dw. Hatchery data
were combined with field data and included in all analyses.
Three endpoints were considered for purposes of calculating an ECi0. These were
percent survival, percent fully free from deformities, and percent surviving and
normal. Initially, data for these endpoints were combined and analyzed for both
portions of the test: hatch through swim up and the 15-day post swim feeding
trial. Data for these endpoints over both portions of the test are shown in Tables
1-3.
A U.S. Fish and Wildlife (2012) review of the Formation Environmental (2011)
report suggested that fish lost due to an overflow even resulting from a drain the
became clogged with food during the 15-day post swim up portion of the test
were more likely to have been dead or deformed, and proposed that all treatments
that lost fish to the overflow event should be excluded from the ECi0 calculation.
In the 2014 and 2015 draft Se documents, endpoints assessed for the hatch
through 15-day post swim up test were analyzed using two scenarios. In the
"worst-case" scenarios, the hypothesis from the USFWS review was examined,
by treating all fish lost to overflow as either dead or deformed, rather than
excluding those treatments altogether. In the "optimistic" scenario, the overflow
event was treated as a random technician error unrelated to selenium toxicity, and
any lost fish were removed from the calculation. In other words, fish lost to
overflow were assumed to be equally likely to have been dead or deformed
compared to fish that were not lost.
Because of the importance of these data for the numeric criterion calculation, and
because of several experimental factors that resulted in the calculation of several
reasonable ECi0s, such as the loss of fish due to an overflow event described
above, EPA conducted a careful and thorough reanalysis of the study data and
subjected the reanalysis to independent, external peer review (ERG 2012) to
confirm the validity and scientific robustness of the approach taken by EPA in
the reanalysis and use of the reanalyzed data. Those assessments were then
superseded by a reanalysis of a more complete enumeration of the deformity
counts provided by AECOM (2012). All analyses reported in the 2014 and 2015
draft Se documents and the current Se document used values from the updated
dataset provided by AECOM (2012).
Hatch Through 15-Day Post Swim Up Combined Data
In the 2014 and 2015 draft Se documents, data for three endpoints, survival,
deformities, and combined survival+deformities were considered for both
portions of the test. The first portion of the test was from hatch through swim up,
lasting 88 days (on average). The second portion was the 15-day post-swim up
C-69
-------
feeding trial. None of the fry from the five treatments with Se concentrations of
26.8 mg/kg and higher reached swim-up. However, surviving fry from those
treatments were included in the post-swim up feeding trial.
Combined Survival and Deformity Endpoint
Selenium concentrations and counts of total larvae, and counts of proportions of
fully normal larvae (alive and normal) are included in Table 1. Background
percentages of live and normal individuals were extremely variable and often low
(Figure 1). In the 2014 draft document, ECi0s for the optimistic (21.16 mg/kg)
and worst case (20.65 mg/kg) scenarios were calculated, and these were also
reported in the 2015 draft document. Although there is a clear demarcation
between treatments equal to or less than 20.5 (ig/L and treatments equal to or
greater than 26.8 (ig/L, suggesting an effect level between these concentrations, a
careful reanalysis of these data following the release of the 2015 draft Se
document determined that a meaningful ECi0 cannot be calculated because of the
high background variability.
C-70
-------
Table 1. Brown trout selenium concentrations and survival + deformity data (combined endpoint) from hatch to test end (15 days post
swim up).
Sample IDa
Whole
body
Se, mg/kg
d\v
Egg Se
mg/kg
dvv
#
Normal
# Normal
that were
dead at
assessment
#
Normal
and
alive
# Live fish
assessed for
deformities
# Fish died
during test
# Fish lost to
overflow
during post
swim up test
# Live fish
assessed + # died
during test.
Prop. Live fish
assessed + # died
during test.
SC-001
3.6
0.76
63
63
115
8
123
0.512
SC-002
4.1
0.94
72
72
113
4
117
0.615
SC-003
3.7
0.83
131
131
302
7
9
309
0.424
SC-004
4.3
0.92
46
46
140
28
168
0.274
SC-005
3
1.2
23
23
42
6
48
0.479
SC-006
3.1
1.2
457
457
535
8
543
0.842
SC-007
2.7
1
93
93
137
30
167
0.557
SC-008
2.5
0.96
283
283
359
6
10
365
0.775
SPC-001C
0.73
427
427
570
8
578
0.739
SPC-002C
0.73
371
371
545
20
565
0.657
SPC-005C
0.73
400
400
561
8
569
0.703
SPC-006C
0.73
427
427
556
17
573
0.745
CC-150-009
8.4
12.8
106
106
142
11
153
0.693
CC-150-011
5.6
8.4
87
87
266
2
268
0.325
CC-150-012
6.7
8.5
156
156
282
12
294
0.531
CC-150-013
5.9
8.4
137
137
310
46
26
356
0.385
CC-150-015
6
9.1
210
210
445
14
459
0.458
CC-150-016
7
7.5
13
13
23
3
43
26
0.500
CC-150-017
5.6
6.6
99
99
163
7
33
170
0.582
CC-150-018
4.7
6.9
195
195
486
16
502
0.388
CC-150-020
7.2
6.2
453
453
558
6
564
0.803
CC-350-006
9.2
14
120
120
386
26
412
0.291
CC-350-007
5.5
6.9
68
68
131
10
20
141
0.482
CC-350-008
8.5
9.5
269
269
338
21
28
359
0.749
LSV2C-002
8.9
12.8
483
483
544
4
16
548
0.881
LSV2C-003
13.8
40.3
2
2
0
0
395
395
0.000
LSV2C-004
17.9
36
16
16
0
0
289
289
0.000
LSV2C-005
13.6
26.8
8
8
0
0
267
267
0.000
LSV2C-008
9.6
17.7
147
147
194
4
45
198
0.742
C-71
-------
Whole
# Normal
#
# Fish lost to
body
Egg Se
that were
Normal
# Live fish
overflow
# Live fish
Prop. Live fish
Se, mg/kg
mg/kg
#
dead at
and
assessed for
# Fish died
during post
assessed + # died
assessed + # died
Sample ID11
dw
dw
Normal
assessment
alive
deformities
during test
swim up test
during test.
during test.
LSV2C-010
22.6
38.8
5
5
0
0
97
97
0.000
LSV2C-012
7.2
13.2
217
217
554
17
571
0.380
LSV2C-016
9.2
13.4
440
440
530
20
550
0.800
LSV2C-017
13.2
20.5
110
110
150
28
19
178
0.618
LSV2C-019
8.6
12.5
267
267
390
22
39
412
0.648
LSV2C-020
11.3
11.2
240
240
296
5
36
301
0.797
LSV2C-021
20
28.1
8
8
0
0
404
404
0.000
a SC - Saratoga National Fish Hatchery; SPC - Spring Creek Trout Hatchery; CC - Crow Creek; LSV - Sage Creek
b Test end was 15 days after swim up.
c Arrived as fertilized, eyed-eggs. No whole body Se measurement possible.
C-72
-------
SC Hatchery
^ SPC Hatchery
CC-150
CC-350
A LSV-2C
0.5 1.0
log(Dg Se/kg dw)
Figure 1. Proportion of alive and normal larvae plotted against Se
concentrations in eggs. Effects were highly variable across the entire
background concentration range (20.5 mg/kg and lower), such that a meaningful
ECio could not be calculated for this endpoint.
Deformity Endpoint
Selenium concentrations, counts of larvae assessed for deformities, and counts
and proportions of normal larvae are included in Table 2. As with the combined
endpoint, background (at or below 20.5 mg/kg) proportions of deformities were
highly variable (Figure 2). In the 2014 draft document, ECi0s were calculated for
both the optimistic and worst case scenarios, and the ECi0 of 15.91 mg/kg for the
worst case scenario was used as the ECi0 for Salmo. During the review phase
following the release of the 2014 draft Se document, several public commenters
noted that because of the high variability, more than one ECi0 could be calculated
by TRAP for both the optimistic and the worst case scenarios depending on the
initial model conditions, in particular the slope of the falling limb of the
concentration-response curve. For the optimistic scenario, ECi0s based on initial
conditions ranged from 16.36-21.95 mg/kg, and for the worst case scenario,
ECioS based on initial conditions ranged from 15.91-21.58 mg/kg. In order to
evaluate the most appropriate ECio for the deformity endpoints, models were
evaluated based on residual sum of squares, and the ECi0 for the model with the
lowest residual sum of squares was selected as the most appropriate. For the
worst case scenario deformity endpoint, the model with the lowest residual sum
C-73
-------
of squares was the ECi0=21.58 mg/kg model, and for the optimistic deformity
endpoint, the model with the lowest residual sum of squares was the ECi0=21.94
mg/kg model.
These variable ECi0s were the result of large variability in background
concentration, with several treatments at low Se concentrations experiencing
greater than 60% deformities (Figure 2). Although there is clear evidence of an
effect between the 20.5 and 26.8 mg/kg concentrations, because of this high
background variability, a careful re-analysis of these data following the release of
the 2015 draft Se document determined that a meaningful ECio could be
calculated for the deformity endpoint.
Some of the background variability in deformities appears to be the result of
differences among field sites. For example, deformity rates among field samples
appear to be greater for fish hatched from eggs collected in the two Crow Creek
sites (CC-150, CC-350) compared to Sage Creek (LSV-2C) (Figure 2). If the
result of higher background deformities among Crow Creek sites is not a random
artifact, it suggests a confounding factor, unrelated to selenium exposure.
Whether the higher deformity rates represent random variation, population
differences, other environmental quality differences (unrelated to Se), or
methodological issues is unclear.
Table 2. Brown trout selenium concentrations and deformity data from hatch to test end (15 days
post swim up).
Whole
# Assessed for
# Lost to
body
Egg Se
deformities.
overflow
Prop. Assessed
Sample
Se, mg/kg
mg/kg
#
"Optimistic
during post
for deformities
IDa
dw
dw
Normal
Case"
swim up test
plus # lost.
SC-001
3.6
0.76
63
115
0.548
SC-002
4.1
0.94
72
113
0.637
SC-003
3.7
0.83
131
302
9
0.434
SC-004
4.3
0.92
46
140
0.329
SC-005
3
1.2
23
42
0.548
SC-006
3.1
1.2
457
535
0.854
SC-007
2.7
1
93
137
0.679
SC-008
2.5
0.96
283
359
10
0.788
spc-ooic
0.73
427
570
0.749
SPC-002C
0.73
371
545
0.681
SPC-005C
0.73
400
561
0.713
SPC-006C
0.73
427
556
0.768
CC-150-
0.746
009
8.4
12.8
106
142
CC-150-
0.327
011
5.6
8.4
87
266
CC-150-
0.553
012
6.7
8.5
156
282
CC-150-
0.442
013
5.9
8.4
137
310
26
CC-150-
6
9.1
210
445
0.472
C-74
-------
Sample
IDa
015
CC-150-
016
CC-150-
017
CC-150-
018
CC-150-
020
CC-350-
006
CC-350-
007
CC-350-
008
LSV2C-
002
LSV2C-
003
LSV2C-
004
LSV2C-
005
LSV2C-
008
LSV2C-
010
LSV2C-
012
LSV2C-
016
LSV2C-
017
LSV2C-
019
LSV2C-
020
LSV2C-
021
Whole
body
Se, mg/kg
dw
7
5.6
4.7
7.2
9.2
5.5
8.5
8.9
13.8
17.9
13.6
9.6
22.6
7.2
9.2
13.2
8.6
11.3
20
Egg Se
mg/kg
dw
7.5
6.6
6.9
6.2
14
6.9
9.5
12.8
40.3
36
26.8
17.7
38.8
13.2
13.4
20.5
12.5
11.2
28.1
#
Normal
13
99
195
453
120
68
269
483
2
16
8
147
5
217
440
110
267
240
# Assessed for
deformities.
"Optimistic
Case"
23
163
486
558
386
131
338
544
100
142
149
194
80
554
530
150
390
296
172
# Lost to
overflow
during post
swim up test
43
33
20
28
16
45
19
39
36
Prop. Assessed
for deformities
plus # lost.
0.565
0.607
0.401
0.812
0.311
0.519
0.796
0.888
0.020
0.113
0.054
0.758
0.063
0.392
0.830
0.733
0.685
0.811
0.047
a SC - Saratoga National Fish Hatchery; SPC - Spring Creek Trout Hatchery; CC - Crow Creek; LSV -
Sage Creek
b Test end was 15 days after swim up.
c Arrived as fertilized, eyed-eggs. No whole body Se measurement possible.
C-75
-------
1.0
0.8 -
TO
E
i_
o
z 0.6 -
"5
u_
c
o
¦¦e 0.4 -
o
o.
o
i_
CL
0.2 -
0.0 -
0.0 0.5 1.0 1.5
log(Dg Se/kg dw)
Figure 2. Proportion of normal (free from deformities) larvae plotted
against Se concentrations in eggs, hatch through 15-days post swim up.
Effects were highly variable across the entire background concentration range
(20.5 mg/kg and lower), such that a meaningful ECi0 could not be calculated for
this endpoint.
Survival Endpoint
Selenium concentrations and estimated counts and proportions of larvae
surviving from hatch through 15 days post swim up are included in Table 3.
Estimated counts and proportions were reported for survival through the 15-day
post swim up test because larvae were thinned to a target of 100
individuals/treatment prior to the onset of the post swim up test, and final full test
survival is calculated as the product of survival from hatch to swim up and
survival during the 15-day post swim up test. In the 2014 draft document, ECi0s
were calculated for the worst case (16.78 mg/kg) and optimistic (20.40 mg/kg)
survival scenarios, and these were also reported in the 2015 draft document. For
both scenarios, the assumption was made that fry that failed to swim up would
not have survived, and so the survival for the post swim up portion of the test in
the 5 treatments with the highest selenium concentrations (26.8 mg/kg and
above) was set to zero. The ECi0 of 16.78 mg/kg for the optimistic is nearly
identical to the ECi0 for the worst case survival scenario of 16.76 mg/kg
presented in the response to the FWS review of the Formation Environmental
study (Taulbee et al. 2012), peer reviewed by ERG (2012).
In contrast to the deformity and combined deformity+survival endpoints,
background survival (concentrations up to and including 20.5 mg/kg) was much
less variable. Despite the lower variability among background effect levels, a
careful re-examination of these data following the release of the 2015 draft Se
T
© SC Hatchery
^ SPC Hatchery
Q CC-150
^ CC-350
A LSV-2C
-I-
A
A
A
A
C-76
-------
document determined that a meaningful ECio cannot be calculated by TRAP so
long as the assumption is made that fry failing to reach swim up are assumed to
be dead. This is because TRAP requires at least 2 partial effects to calculate an
ECio, and this dataset has no partial effects, but rather, a background range with
high and relatively stable survival through 20.5 mg/kg, and then no survival at
concentrations of 26.8 mg/kg and above (Figure 3). In order to calculate an ECio
for survival, the assumption regarding fry that failed to swim up was removed. In
addition, in order to remove the uncertainty introduced by the clogged drain
leading to the overflow and loss of fish from some of the treatments in the post
swim up test, the ECio for larval survival was calculated for the much longer
hatch through swim up portion of the test, as described below.
Table 3. Brown trout selenium concentrations and survival data from hatch to test end (15 days
post swim up).
Sample IDa
Whole body
Se, mg/kg dw
Egg Se
mg/kg dw
# Eggs
Hatched
Prop.
Survival.
Hatch to swim
up
Prop survival.
Post swim
up."
Prop survival.
Hatch to endb.
SC-001
3.6
0.76
144
0.951
0.990
0.942
SC-002
4.1
0.94
138
0.978
0.990
0.968
SC-003
3.7
0.83
340
0.982
0.989
0.971
SC-004
4.3
0.92
189
0.868
0.971
0.842
SC-005
3
1.2
70
0.914
1.000
0.914
SC-006
3.1
1.2
564
0.988
0.990
0.978
SC-007
2.7
1
188
0.856
0.970
0.830
SC-008
2.5
0.96
396
0.985
1.000
0.985
SPC-001C
0.73
598
0.987
1.000
0.987
SPC-002C
0.73
20
1.000
1.000
1.000
SPC-003C
0.73
585
0.966
1.000
0.966
SPC-004C
0.73
21
1.000
1.000
1.000
SPC-005C
0.73
589
0.986
1.000
0.986
SPC-006C
0.73
593
0.971
1.000
0.971
CC-150-009
8.4
12.8
173
0.942
0.990
0.933
CC-150-011
5.6
8.4
288
0.993
1.000
0.993
CC-150-012
6.7
8.5
314
0.965
0.990
0.955
CC-150-013
5.9
8.4
402
0.891
0.973
0.866
CC-150-015
6
9.1
479
0.971
1.000
0.971
CC-150-016
7
7.5
89
0.966
1.000
0.966
CC-150-017
5.6
6.6
223
0.969
1.000
0.969
CC-150-018
4.7
6.9
522
0.969
1.000
0.969
CC-150-020
7.2
6.2
584
0.990
1.000
0.990
CC-350-006
9.2
14
432
0.944
0.980
0.926
CC-350-007
5.5
6.9
181
0.950
0.988
0.938
CC-350-008
8.5
9.5
407
0.951
0.986
0.938
LSV2C-002
8.9
12.8
584
0.993
1.000
0.993
LSV2C-003d
13.8
40.3
404
0.079
0.281
0.022
LSV2C-004d
17.9
36
309
0.414
0.477
0.197
LSV2C-005d
13.6
26.8
287
0.387
0.622
0.240
LSV2C-008
9.6
17.7
263
0.989
0.982
0.971
LSV2C-010d
22.6
38.8
108
0.231
0.440
0.102
LSV2C-012
7.2
13.2
591
0.971
1.000
0.971
C-77
-------
Prop.
Survival.
Prop survival.
Whole body
Egg Se
# Eggs
Hatch to swim
Post swim
Prop survival.
Sample IDa
Se, mg/kg dw
mg/kg dw
Hatched
up
up."
Hatch to endb.
LSV2C-016
9.2
13.4
570
0.965
1.000
0.965
LSV2C-017
13.2
20.5
217
0.885
0.963
0.852
LSV2C-019
8.6
12.5
471
0.953
1.000
0.953
LSV2C-020
11.3
11.2
357
0.986
1.000
0.986
LSV2C-021d
20
28.1
424
0.288
0.730
0.210
a SC - Saratoga National Fish Hatchery; SPC - Spring Creek Trout Hatchery; CC - Crow Creek; LSV -
Sage Creek
b Test end was 15 days after swim up.
c Arrived as fertilized, eyed-eggs. No whole body Se measurement possible.d Survived but failed to reach
swim up. Assumed dead in all hatch to 15-day post swim up analysis.
1.2
1.0 -
O)
.E 0.8
>
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3
(/)
C
o
'-e
o
Q_
O
0.6 -
0.4 -
0.2 -
0.0
w;
A
®
SC Hatchery
~
SPC Hatchery
¦
CC-150
CC-350
A
LSV-2C
—i—
0.0
—I—
0.5
1.0
1.5
log(Dg Se/kg dw)
Figure 3. Proportion of larval survival plotted against log transformed Se
concentrations in eggs, hatch through 15-day post swim up. Larvae from the
five highest Se concentration treatments failed to reach swim up and were
assumed to not have survived in the wild.
Assessment of Overflow Loss During 15-dav Post Swim Up Feeding Trial
In the 2015 draft Se document, an assessment was made to determine whether the
loss of fish from the overflow event during the 15-day post swim up portion of
the test was related to survival or to Se treatment concentration measured during
the first portion of the test. In this assessment, data were examined from the
perspective of whether the overflow loss of brown trout during the second stage
of the test could reflect dead, dying, or weak organisms. This was done to
examine the hypothesis proposed in the U.S. FWS review that fish lost to
overflow were either dead or dying.
C-78
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First, the relationship between larval survival in the first and second stages of the
test (hatch to swim up, 15 days post swim up) were compared for all treatments
where larvae successfully reached the swim up stage (Figure 4). Overall, survival
in the second stage tracks survival in the first stage (r2=0.6), but survival in the
second stage was noticeably higher in than in the first stage. This result is
consistent with the following statement made by the principle scientist of the
brown trout study in the public comments to the 2014 selenium draft document
submitted for external peer review: "escaped fry were observed swimming in the
water bath where the treatment containers were being held. These fry
congregated near the treatment cells. Dead or dying fish were not observed."
m
bo
1.005
1
0.995
0.99
0.985
0.98
"1 0.975
0.97
0.965
0.96
$
s
I
3
E
••p
&
f
0.84 0.86
0.88 0.9 0.92 0.94 0.96 0.98
Brown trout survival during 1st stage
1.02
Figure 4. Relationship between survival during the first and second portions
of the test. All treatments where larvae successfully reached swim up (Se
concentrations of 20.5 mg/kg and lower).
Second, the relationship between larval mortality in the first stage and overflow
loss in the second stages of the test (hatch to swim up, 15 days post swim up)
were compared separately for all treatments (field and hatchery) and for all field
collected treatments (Figure 5). As with figure 4, these correlations were made
for treatments where larvae successfully reached the swim up stage. In these
instances, there is no apparent relationship between health, as reflected by
mortality in the first stage, and overflow loss in the second stage, whether
considering all individuals or wild-only: r2 for both graphs is 0.0. The lack of a
relationship in these correlations suggests that overflow loss has a likelihood of
being a random noise variable.
C-79
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s.
%
0.6
0.5
oj 0.'
W>
0.3
0.2.
0.1
0
0.02 0.04 0.06 0.08 0.1 0.12
Brown trout mortality during 1st stage
0.14
0.16
0.6
8.
e
0.5
eM 0.'
(30
0.3
0.2.
0.1
0 • •#
0 0.02 0.04 0.06 0.08 0.1 0.12
Brown trout mortality during 1st stage
0.14
Figure 5. Relationship between mortality during the first stage of the test
and overflow loss during the second stage of the test. Upper figure - all
hatchery and field treatments. Lower figure - field treatments only. Larvae from
treatment levels 26.8 mg/kg and higher, which failed to swim up, were excluded.
Finally, the relationship between overflow loss and selenium concentrations in
eggs was examined (Figure 6). As with previous correlations, only larvae from
treatments where individuals reached swim up were considered.
Figure 6 shows a clear difference between hatchery (far left) and field treatments,
but across the concentration range for the offspring of field collected fish there is
no apparent relationship between overflow loss and Se concentration. Within the
field treatments, the r2 of the correlation between Se concentration and overflow
loss is 0.01. Although there are no known genetic differences between hatchery
C-80
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and wild fish, if leaving the aquarium required swimming over the rim, one
might speculate that previous generations of hatchery fish might have developed
a tolerance to remaining in conditions that might seem crowded to wild
organisms. (That is, however, purely speculative.) Otherwise, the difference
between hatchery and wild fish would seem only to reflect a random artifact,
since the Se concentrations at which the wild fish displayed high overflow losses
are low.
§>
0.6
0,5
S 0.4
00
c
•c
% 0.3
0.2
0.1
0
10 15
Egg Concentration, mg Se/kg dw
20
25
Figure 6. Relationship between egg Se concentration and overflow loss
during the second stage of the test. Larvae from treatment levels 26.8 mg/kg
and higher, which failed to swim up, were excluded.
In summary, the positive correlation between survival during the hatch to swim
up portion of the test and survival during the 15-day post swim up portion of the
test, combined with the lack of a correlation between mortality during the hatch
to swim up portion of the test and overflow loss during the second stage of the
test, suggests that the overflow loss likely represents a random technician error
not related to the health of the individuals lost. The relationship between
selenium egg concentrations and overflow loss was lower for the larvae hatched
from hatchery fish compared to the larvae hatched from field collected fish;
however, among field treatments ranging from 6.0-20.5 mg/kg there was no
correlation, further supporting the hypothesis that the overflow event was a
random occurrence unrelated to the health of larval fish.
The results of the above assessment of the overflow event strongly suggest that
the overflow event was a random technician error unrelated to selenium toxicity,
and that the "optimistic" scenario is also likely more realistic.
Survival Endpoint - ECm for the first portion of the test
Because larval survival was measured at the end of the first portion of the test
(hatch to swim up), an alternative approach to measuring survival would be to
C-81
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calculate the brown trout ECio for survival for only the first portion of the test.
Selenium concentrations and counts of total larvae and larvae that survived the
first portion of the test are included in Table 4. The hatch to swim up portion of
the test was much longer than the second portion (88 days on average compared
to 15 days), and more importantly, it avoids the experimental confound
introduced by the loss of fish during the overflow event. With this approach, the
second portion of the test would be rejected as inconclusive due to the laboratory
accident.
Unlike survival, deformities could not be analyzed for the first portion of the test
because of a bias introduced during the thinning process prior to the initiation of
the 15-day post swim up portion of the test. During the thinning process, visibly
deformed larvae were selectively removed, so that the fish used in the 15-day
post swim up test were less likely to have been deformed. Because of this
selection bias, only survival could be evaluated from hatch to swim up.
Nevertheless, survival appears to be as sensitive an endpoint as deformities or
survival+deformities, as all endpoints exhibit background effects (with differing
levels of variability) through 20.5 mg/kg, and severe effects at concentrations
between 26.8-40.3 mg/kg.
In contrast to survival endpoints measured from hatch through 15 days post swim
up, survival for all treatments were included, including larvae from the five
treatments of 26.8 mg/kg and higher, where larvae failed to reach swim up. This
avoids any potential inconsistency stemming from not knowing whether small
percentages of individuals did not swim up in other treatments. In contrast to the
previous ECio calculations, this approach is free from all assumptions about
individuals lost in the lab accident. In the 2015 draft document, an ECio of 18.09
mg/kg was calculated for this endpoint in TRAP, and this ECi0 was used as the
GMCV for Salmo. During a subsequent review, this ECio was determined to be
inappropriate, because it is lower than the 20.5 mg/kg concentration, which with
88.5% survival falls within the variability of the 32 data points at lower
concentrations. Compared to the average survival for all 33 background
concentration treatments, the survival at 20.5 mg/kg represents an approximately
8% effect.
In order to calculate an ECio that would not fall below the background
concentration of 20.5 mg/kg, a weighted least squares linear regression was
calculated in TRAP, using a threshold sigmoid model (Figure 7). The model was
weighted using the standard deviation of the 33 background concentrations (all
concentrations between 0.73-20.5 mg/kg), and the residual standard deviation of
the five concentrations between 26.8-40.3 mg/kg. This was done to provide less
weight to the more variable, and more uncertain, high Se treatments relative to
the less variable background treatments. The ECio for survival using the
weighted regression model is 21.0 mg/kg.
One issue with the above TRAP analysis is that to fit the 5 higher effects data
well, the EC0 estimate is pushed down to 16.4 mg/kg, below two of the points in
the background range. Also, the fitted curve goes through the data point at 20.5
mg/kg, so that this point is considered to be an ECS. This is not unreasonable
because the response is so steep at concentrations above this point that some
effect at this point is plausible. Nevertheless, this point is within the range of the
C-82
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background and there are insufficient data to say that this concentration is an
effect level. Thus, to accept this analysis and use the ECio from this curve
requires making a slightly conservative risk management decision that the point
at 20.5 mg/kg should be treated as having some effect.
>
(f)
c.
o
o
CO
100
Q.
E
(f)
|m*
80
o
"co 60
X
40
20
-V
10
20
50
100
Selenium in Egg (mg Se/kg dw)
Figure 7. Brown trout survival, hatch to swim up. ECio of 21.0 mg/kg
calculated using a weighted nonlinear regression model.
Table 4. Brown trout selenium concentrations and survival data from hatch to swim up (first
portion of the test).
# Larvae
% Larvae
Whole body
Survived -
Survived -
Se, mg/kg
Egg Se
# Larvae
Hatch to
Hatch to
Sample IDa
dw
mg/kg dw
Hatched
Swim Up
Swim Up
SC-001
3.6
0.76
144
137
95.1
SC-002
4.1
0.94
138
135
97.8
SC-003
3.7
0.83
340
334
98.2
SC-004
4.3
0.92
189
164
86.8
SC-005
3
1.2
70
64
91.4
SC-006
3.1
1.2
564
557
98.8
SC-007
2.7
1
188
161
85.6
SC-008
2.5
0.96
396
390
98.5
SPC-001b
0.73
598
590
98.7
SPC-002b
0.73
20
20
100
SPC-003b
0.73
585
565
96.6
SPC-004b
0.73
21
21
100
SPC-005b
0.73
589
581
98.6
C-83
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# Larvae
% Larvae
Whole body
Survived -
Survived -
Se, mg/kg
Egg Se
# Larvae
Hatch to
Hatch to
Sample IDa
dw
mg/kg dw
Hatched
Swim Up
Swim Up
SPC-006b
0.73
593
576
97.1
CC-150-009
8.4
12.8
173
163
94.2
CC-150-011
5.6
8.4
288
286
99.3
CC-150-012
6.7
8.5
314
303
96.5
CC-150-013
5.9
8.4
402
358
89.1
CC-150-015
6
9.1
479
465
97.1
CC-150-016
7
7.5
89
86
96.6
CC-150-017
5.6
6.6
223
216
96.9
CC-150-018
4.7
6.9
522
506
96.9
CC-150-020
7.2
6.2
584
578
99
CC-350-006
9.2
14
432
408
94.4
CC-350-007
5.5
6.9
181
172
95
CC-350-008
8.5
9.5
407
387
95.1
LSV2C-002
8.9
12.8
584
580
99.3
LSV2C-003
13.8
40.3
404
32c
7.9
LSV2C-004
17.9
36
309
128°
41.4
LSV2C-005
13.6
26.8
287
111°
38.7
LSV2C-008
9.6
17.7
263
260
98.9
LSV2C-010
22.6
38.8
108
25c
23.1
LSV2C-012
7.2
13.2
591
574
97.1
LSV2C-016
9.2
13.4
570
550
96.5
LSV2C-017
13.2
20.5
217
192
88.5
LSV2C-019
8.6
12.5
471
449
95.3
LSV2C-020
11.3
11.2
357
352
98.6
LSV2C-021
20
28.1
424
122c
28.8
a SC - Saratoga National Fish Hatchery; SPC - Spring Creek Trout Hatchery; CC - Crow Creek; LSV -
Sage Creek
b Arrived as fertilized, eyed-eggs. No whole body Se measurement possible.
c Survived, but failed to reach swim up.
C-84
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Whole Body Concentration
The whole-body concentration response curve for survival, hatch to swim up is
shown in Figure 8. These data are not amenable to TRAP modeling, and Figure 8
shows the interpolation procedure, the first interpolation point being an EC0 at
13.2 mg/kg and 96% survival and the second point an LOEC at 13.6 mg/kg and
39% survival. Because the HNOEC (13.2 mg/kg) and LOEC (13.6 mg/kg) are so
close, the chronic value for whole body selenium is the HNOEC of 13.2 mg/kg
dw.
Q_
3
CO
&
o
ro
x
>
'>
3
C
o
o
05
100
80 -
60
40
20
* •
¦
10
I
20
50
Selenium in Whole Body (mg Se/kg dw)
Figure 8. Fraction survival of brown trout larvae as a function of selenium in
eggs.
Effect Concentration: For this study the most appropriate, least confounded endpoint is survival, hatch
to swim up. For egg selenium, ECi0 is 21.0 mg Se/kg egg dw, calculated for
survival from hatch to swim up using a weighted nonlinear regression model.
Expressed as whole body, the chronic value is 13.2 mg Se/kg WB dw.
C-85
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Besser, J.M., W.G. Brumbaugh, D.M. Papoulias, C.D. Ivey, J.L. Kunz, M. Annis, and C.G.
Ingersoll. 2012. Bioaccumulation and toxicity of selenium during a life-cycle exposure with desert
pupfish (Cyprinodon macularius): U.S. Geological Survey Scientific Investigations Report 2012-5033,
30 p. with appendixes.
Test Organism: Desert pupfish (Cyprinodon macularius)
Exposure Route: Dietary and waterborne. Pupfish were fed the oligochaete, Lumbriculus
variegatus, which had been grown on a diet of selenized yeast.
Test Duration: 180 days life cycle, 21 days F1 larvae, 58 days F1 juveniles and adults.
Study Design: Desert pupfish (Cyprinodon macularius), a federally-listed endangered species,
were exposed simultaneously to waterborne and dietary selenium at six exposure
levels (controls and five selenium treatments) in a three-phase life cycle exposure
study. Aqueous exposures were prepared using sodium selenate and sodium
selenite salts at an 85%-15% proportion, respectively. Pupfish were fed the
oligochaete, Lumbriculus variegatus, daily to satiation (25 to 30% rations based
on wet weights). Prior to being fed to the pupfish, the oligochaetes were exposed
to aqueous selenium and fed selenized yeast at appropriate concentrations to
attain the target dietary tissue concentrations. The measured concentrations in
water, oligochaetes (pupfish diet), and pupfish tissues for the control and five
treatments during the life cycle exposures.
Treatment
water
jig/L
oligochaetes
mg/kg dw
pupfish, mg/kg dw
F0WB eggs FiWB
Control
nd
1.6
0.75
1
1.2
Se-1
3.4
5.1
2.5
3
3.4
Se-2
6.2
7.3
3.4
4.4
3.7
Se-3
14
14
6.7
8
6.7
Se-4
26
24
12
13
12
Se-5
53
52
24
27
31
The 85-day Phase 1 exposure was initiated with approximately five week old
juvenile pupfish (F0). Phase 1 consisted of two separate groups with one group
(started two weeks prior to the second group) used for determining survival,
growth and whole body selenium concentrations, and the other group used for
survival assessment and to provide adults for the main reproduction exposure.
Both groups in Phase 1 were similarly exposed to all six treatments, with each
treatment having 8 replicates and 10 fish in each replicate.
At the end of the 85-day Phase 1 exposure, the pupfish were reproductively
mature and were used for the Phase 2 exposure, the main reproduction study. A
preliminary reproduction study was conducted with adults from the first exposure
group of F0 pupfish. These fish were divided into two spawning groups and eggs
were collected on four dates during a 9-day period. The main purpose of the
preliminary study was to confirm the reproductive maturity of the pupfish, but
samples of larvae from this study were used for assessment of deformities. The
main reproduction study in Phase 2 was started with adults from the second F0
exposure. These fish were sorted into spawning groups (1 male and 3 females) in
C-86
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7-L exposure chambers, with eight replicate spawning groups per selenium
treatment. Spawning activity was monitored by removing (and replacing)
spawning substrates from each chamber three times a week (Monday-
Wednesday-Friday). There were 23 egg collection dates during a 60-day period.
All eggs were counted and eggs collected from eight Wednesdays were used for
hatching success, deformities and Fi larval and juvenile growth and survival in
the 58-day Phase 3 exposure. Larvae were examined for developmental
endpoints including edema, delayed development, and skeletal, eye, craniofacial,
and fin deformities.
Effects Data: A summary of the endpoints by each treatment level is shown below.
Table 1. Summary of pupfish toxicity endpoints by exposure treatment (average across all
replicates). There were no statistically significant differences across controls and selenium
amendment treatments for any of the endpoints shown here (1-way ANOVA, a=0.05).
Endpoint" Control Se-1 Se-2 Se-3 Se-4 Se-5
F0 survival, day 28
100
100
100
100
100
98
F0 survival, day 56
100
100
100
100
100
100
F0 survival, day 85
100
100
100
100
100
100
F0 survival, day 150
91
94
94
94
91
97
F0 growth, day 28
213
206
204
198
213
203
F0 growth, day 56
535
526
486
469
509
447
F0 growth, day 85
935
998
941
934
914
1053
F0 growth, day 150
1718
1763
1776
1755
1673
1606
Fl survival, day 30
100
100
100
100
98
98
Fl survival, day 58
100
100
93
90
95
88
Fl growth, day 30
73
73
76
78
77
58
Fl growth, day 58
260
264
286
286
288
255
total number eggs
6845
6331
4143
4386
3337
5225
% reduction eggs
NA
8
39
36
51
24
avg % deformities, main
5.3
2.7
4.9
2.4
11.4
8.1
avg % deformities, preliminary
4.4
8.8
11.6
14.3
10.7
21
aEndpoint units: survival, %; growth, mg wet weight; % reduction eggs is relative to the control.
The authors observed no significant differences in pupfish survival or growth
among treatments. The authors hypothesized the lack of statistically significant
acute effects was because the pupfish in this study were near their chronic
toxicity threshold, as suggested by the (non-significant) mean reductions in
growth (7% in F0 day 150) and survival (12% in F, day 58) in the highest
selenium treatment (Se-5), relative to controls (Table 1).
Egg hatching and larval survival in all selenium treatments (not listed in Table 2)
were within 10 percent of control means, and differences among treatments were
C-87
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not related to selenium exposure. The authors noted that the highest selenium
treatment, Se-5, did have the lowest larval survival (84%) and lowest combined
egg hatching and larval survival (76 percent). The means frequencies of
deformities were higher in the two highest Se treatments (Se-4 and Se-5, Table
1); however % deformities across treatment levels were not statistically
significant (1-way ANOVA, p=0.13; Beckon et al. (2012). However, overall
deformity rates were statistically significantly higher in a preliminary
reproduction than in the main reproduction test. Beckon et al. (2012)
hypothesized that the reason for the difference in deformity rates between the two
tests was related to the time the eggs were collected relative to the time the
respective spawning groups were isolated. Eggs were collected in the preliminary
reproductive study 1-9 days after the spawning groups were isolated, whereas
spawns used to characterize deformities in the main reproduction test were
collected at least 14 days after the onset of spawning. The larvae produced from
the earlier collected eggs may have been exposed to higher selenium
concentrations in the egg. The pattern of a gradual decrease in egg selenium
concentration over time was observed in the life cycle study.
Egg production varied considerably over the 23 collection dates (Table 2 and
Figure 1). Although each of the selenium treatments had a lower total number of
eggs relative to the control, one-way ANOVAs of cumulative egg production did
not indicate significant differences among treatments on either a per-replicate
basis (p=0.34) or on aper-female basis (p=0.20). Similarly, repeated measures
ANOVA indicated no differences between treatments, but the authors indicated
significant differences among sampling dates and significant interactions of
treatment and date. Because of the lower number of eggs in the selenium
treatments and the significance of the interaction of treatment and time, the
authors concluded that pupfish egg production was adversely affected by
elevated selenium exposure and reported significant reductions in egg production
at treatment levels Se-2 through Se-5 (4.4 to 27 mg/kg dw Se in eggs). The
authors recognized that typically larval survival and deformities are the most
sensitive reproductive endpoint for selenium toxicity and not egg production and
suggested more study is needed to confirm the unusual sensitivity of pupfish egg
production to selenium.
C-88
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Table 2. Number of pupfish collected on each sampling date throughout the study, by treatment
level. Values represent the sum of all eggs collected on a given date for a given Se treatment.
Day
Control
Se-1
Se-2
Se-3
Se-4
Se-5
2
136
112
90
67
122
94
4
275
173
123
142
188
162
7
307
273
301
283
160
432
9
265
252
226
169
271
283
11
401
136
424
319
265
380
14
417
359
333
246
198
401
17
448
456
206
163
145
232
21
303
664
404
204
163
400
23
287
205
141
143
177
175
25
340
308
94
143
150
228
28
366
273
103
101
95
181
30
130
164
104
52
82
132
32
323
304
271
78
75
151
35
320
427
81
150
74
223
37
236
176
41
113
38
38
39
326
151
159
184
113
140
42
507
140
55
193
101
140
44
251
133
66
152
69
137
51
380
359
227
338
305
370
53
278
63
38
197
56
188
56
199
478
138
195
238
222
58
202
329
331
410
143
320
60
148
396
187
344
109
196
C-89
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control
Collection day
Figure 1. Pupfish egg production by sampling date
Several findings from the pupfish study put a clear demonstration of effect due to
selenium in question. The fact that the typical sensitive endpoints for selenium,
larval survival and deformities, were not demonstratively responsive to selenium
through the highest treatment level, the fact that the egg production data did not
show significance among treatments alone, and the fact that egg production
increased at the highest selenium treatment level provide sufficient doubt of a
clear effect due to selenium. These issues are discussed below.
Examination of the Repeated Measures Analysis:
Analysis Using the Full Dataset: The effects of selenium treatment and sampling date on pupfish egg
production (eggs per female per day) were reanalyzed. First, the data were
reanalyzed using repeated measures ANOVA. Results of the repeated measures
ANOVA analysis were qualitatively similar to those reported in Besser et al.
(2012) and are shown in the following table.
C-90
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Between Subjects
Source Sum of Sq. df Mean Sq. F-rat. p-value
Se treatment 2,202.6 5 440,5 1.755 0.143
Error 10,543.5 42 251.0
Within Subjects
Source
Sum of Sq.
df
Mean Sq.
F-rat.
p-value
Sampling Date
1,867.5
22
84.89
4.973
<0.001
Se Treatment x Sampling Date
2,566.3
110
23.33
1.367
0.010
Error
15,771.8
924
17.07
As with the results reported in Table 7 of Besser et al. (2012), there was no main
effect of Se treatment (note - for purposes of these analyses and associated text,
"Se treatment" is defined as the control plus the 5 treatments that received Se
amendments), but there was a statistically significant (p<0.05) effect of sampling
date and a significant date by Se treatment interaction. Results were qualitatively
similar because the p-values for Se treatment and sampling day were identical in
both analyses, yet the p-values for the day by Se treatment interaction term were
nearly identical.
A statistically significant sampling date effect means that there were significant
differences in overall egg production on different sampling dates. Daily egg
production per female ranged from 2.176 on day 2 to a high of 7.294 on day 11,
and was variable throughout the study. Of greater interest is the statistically
significant day x Se treatment interaction. What this means is, although there was
not an overall significant effect of Se treatment on egg production per female,
there was a significant Se treatment effect (p<0.05) on egg production per female
on at least one of the 23 sampling dates.
Analysis after Removal of Control Replicate Outlier: Repeated measures ANOVA analysis confirmed
the results reported in Besser et al. (2012). However, as shown on Figure 8b of
Besser et al. (2012), one replicate chamber (replicate g) within the control
treatment had only one surviving female pupfish from day 7 through the end of
the test (day 60), and that replicate also had the highest overall egg production
per female of any test chamber. All replicate chambers in all treatments began
with three female pupfish, and the replicate described above was the only one
with only one surviving female. All three females survived the 60 day test in the
majority of the replicate chambers. In order to determine whether the significant
date by Se treatment interaction was an artifact of this one test chamber, data
were reanalyzed after removing this replicate.
One requirement of repeated measures ANOVA is that the model cannot contain
any missing values. An alternative to repeated measures ANOVA when data are
missing, and the most commonly followed procedure under these circumstances,
is to analyze the data using a mixed model. This was the procedure followed
here.
C-91
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The results of a fully balanced mixed model (no missing data) should be identical
to repeated measures ANOVA. As an initial check, the full dataset was
reanalyzed as a mixed model. Sample chamber was the random effect parameter,
and Se treatment, sampling date, and Se treatment by sampling date were the
fixed effect parameters. As expected, the F-ratios for the effects of selenium
treatment, sampling date, and the sampling date by Se treatment interaction were
identical. Next, the data were reanalyzed after removing data from control
replicate g from all sampling dates. Results of this analysis are reported in the
table below.
Mixed Model - Fixed
Effect
Numerator df
Denominator df
F-ratio
p-Value
Se Treatment
5
902
1.087
0.366
Sampling Date
22
902
6.042
<0.001
Se Treatment x Sampling Date
110
902
1.310
0.023
T
The statistically significant interaction between Se Treatment and Sampling Date
persisted after removal of the potentially anomalous control treatment chamber
with one female pupfish. In other words, even after removing the one potentially
anomalous control replicate, there were still some individual sampling dates
where the effects of Se treatment were statistically significant (p<0.05).
Se Treatment x Sampling Date Interaction: When a significant interaction is
observed in a repeated measures ANOVA, the next recommended step in the
process is to examine each of the repeated measures (sampling dates) separately
to identify those dates where the significant difference in Se treatment level
occurred. When individual dates for the full dataset (including the replicate with
one surviving female) were analyzed separately, there were significant (p<0.05)
effects of Se treatment level on egg production on days 28, 35, 37, 42, and 53 (1-
way ANOVA, df5 42). There were no significant Se treatment effects on the
remaining 18 sampling dates. ANOVA results are summarized in the table
below.
Sampling Date
F-ratio
p-value
28
2.501
0.045
35
2.704
0.033
37
3.351
0.012
42
4.294
0.003
53
3.352
0.012
Because of the large number of comparisons (23 individual ANOVA models for
each sampling date), an alpha of 0.05 is inappropriate for this particular analysis.
This is because an alpha of p<0.05 means that a statistically significant result will
be observed 5% of the time due to chance alone (Type I error). In order to control
for the increased likelihood of a Type I error when making multiple comparisons,
the alpha level of 0.05 was adjusted using Sidak's correction (Abdi 2007). For 23
comparisons and an alpha of 0.05 for one comparison, the adjusted alpha using
Sidak's correction is as follows:
C-92
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1 - CI - G.OSpa = 0,0027
After adjusting alpha to account for the 23 separate sampling dates, there were no
sampling dates with a significant Se treatment effect (p<0.0027). As a result, it
was not necessary to perform post hoc means comparisons tests for any of the
individual sampling dates to determine which Se treatment levels were
significantly different from each other.
Each of the 23 sampling dates for the dataset where the replicate chamber from
the control treatment with one surviving female pupfish was excluded were also
analyzed using one-way ANOVA to determine which sampling dates had
significant Se treatment effects. Significant differences among Se treatment
levels at alpha 0.05 are shown in the table below.
Sampling Date F-ratio p-value
35 2.839 0.027
42 3.164 0.017
53 2.549 0.042
After adjusting alpha to account for the 23 separate sampling dates, there were no
sampling dates with a significant Se treatment effect (p<0.0027). As with the full
dataset, it was not necessary to perform post hoc means comparisons tests for any
of the individual sampling dates to determine which Se treatment levels were
significantly different from each other.
Summary of Repeated Measures Analysis: This analysis demonstrated that although there was a
significant Se treatment by sampling date interaction, regardless of whether or
not the control treatment chamber with one female pupfish was excluded,
differences among Se treatment levels were only observed for a small subset of
the 23 sampling dates. Furthermore, after adjusting alpha to account for multiple
comparisons, one-way ANOVA analyses conducted separately for each sampling
date to locate the source of the Se Treatment x Sampling Date interaction
determined that there were no statistically significant differences among Se
treatment levels on any sampling date, precluding the need to perform post hoc
comparison of means tests to identify significant differences among individual Se
treatments.
Combining Effect Metrics Using a Population Model: To improve the certainty of any conclusions to
be made about the sensitivity of pupfish to selenium, it is also worthwhile to
consider the biological (as opposed to statistical) significance of the observations.
But for total egg production, survival, and deformities, the concentration-
response curves did not show a sufficient concentration-related effect to calculate
an EC10. Nevertheless, because Besser et al. (2012) raised the issue of an
interaction of egg production with time, there is a particular concern that there
could be a delay in egg production that would reduce population growth rate,
even while total numbers of eggs were not significantly affected. This question
was evaluated by constructing a population model corresponding to data
available from the test.
C-93
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This modeling approach allows for combining and properly weighting effects on
egg production, timing of egg production, and survival. Percent hatch and percent
deformities were also considered in alternate calculations. Because the model is
only intended for combining the lab data into a unified concentration-response
curve, it cannot be interpreted as making real-world population predictions. The
relevant data were taken from spreadsheets Besser et al. (2012b and 2012c),
which were provided by Besser.
The reproduction and larval endpoints spreadsheet, Besser et al. (2012b),
presents egg production at 23 time points. This information thus allows for 23
adult life stages, each assigned its own fecundity. Another page of this
spreadsheet provides larval survival data, thus defining survival of the early life
stage. The juvenile and adult survival spreadsheet, Besser et al. (2012b), defines
a survival rate shared by these life stages.
For each treatment, the data from the test thus provide all the needed input for 25
life stages: (1) an embryo-larval stage with its own daily survival probability
(along with hatching and deformity percentages, when considered in alternative
calculations), (2) anon-reproducing juvenile stage sharing its treatment's daily
survival probability with the adult stages, and (3 - 25) 23 short-duration adult
stages each with its own egg production, but sharing its treatment's daily survival
probability with the treatment's other adult stages. Use of the data is detailed
below.
Egg Production: Egg production at the test's 23 observation time points is from
the spreadsheet Besser et al. (2012b), expressed as eggs per female per day. The
intent of Besser et al. (2012) was for each treatment to have eight replicates, and
each replicate was to have one male and three females. Only replicates matching
that design were used. Early in the test Control Replicate "g" ended up with only
one female, and was therefore not used here. Se-1 Replicate "h" and Se-3
Replicates "d" and "h" had been inadvertently stocked with two males and two
females, and were likewise not used here. Table 3 shows the time course of egg
production incorporated into the population model. For each treatment, model
fecundity, m1, for life stages i = 3 - 25, is the observed egg production divided by
2, in order to provide female eggs per female per day.
Percent Hatch: The spreadsheet Besser et al. (2012b) presents percent hatch for
eggs collected at selected time points. Within each treatment these were
averaged. In selenium reproductive studies percent hatch is often treated as a
noise variable unrelated to selenium exposure. Consequently, the population
growth calculations were run with and without including percent hatch. When
hatch was incorporated into the calculation, daily fecundity was reduced by
multiplying by percent hatch.
Deformities: The Besser et al. (2012b) spreadsheet also provides deformity
counts for the study's preliminary test and for its main test. Only the main test
results were used here. Counts were totaled for each treatment, and a percentage
calculated. Population growth calculations were performed both with and without
consideration of deformity percentage. For simplicity when considered, a worst
case assumption was made that deformed individuals do not contribute to the
C-94
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population. Percent deformity was thereby handled in manner parallel to percent
hatch, by multiplying daily fecundity by percent free of deformity.
Table 3. Life stage durations, and observed eggs per female per day at observation time points
for control and selenium treatments, only with replicates having the design three females and one
male. Model fecundity, m, is set at one-half the observed, to yield female eggs per female.
Repro Study
Assigned
Observed Eggs/Female/Day
Observation
Day
Life Stage
Number
Life Stage
Duration
Control
Se-1
Se-2
Se-3
Se-4
Se-5
-
1
35
-
-
-
-
-
-
-
2
85
-
-
-
-
-
-
2
3
2
2.690
2.571
1.875
1.319
2.542
1.958
4
4
2
5.548
4.048
2.563
2.153
3.917
3.375
7
5
3
4.333
4.302
4.181
3.185
2.222
6.000
9
6
2
5.762
5.524
4.708
3.639
5.646
5.896
11
7
2
8.024
3.238
8.833
4.528
5.521
7.917
14
8
3
6.540
4.905
4.625
2.296
2.750
5.569
17
9
3
6.429
7.143
2.861
1.481
2.014
3.222
21
10
4
3.345
7.881
4.208
1.764
1.698
4.167
23
11
2
5.786
4.643
2.938
3.806
3.688
3.646
25
12
2
6.905
7.286
1.958
2.792
3.125
4.750
28
13
3
4.794
4.317
1.431
1.306
1.319
2.514
30
14
2
1.881
3.881
2.167
1.403
1.708
2.750
32
15
2
5.464
7.286
5.646
1.444
1.563
3.146
35
16
3
4.373
7.310
1.132
2.880
1.028
3.097
37
17
2
5.631
4.417
0.927
1.556
0.792
0.792
39
18
2
6.119
3.917
4.240
3.556
2.354
2.917
42
19
3
7.349
2.222
1.056
2.500
1.403
1.944
44
20
2
4.798
3.274
1.719
3.194
1.438
2.854
51
21
7
1.847
2.139
1.571
2.532
2.060
2.202
53
22
2
6.310
1.512
0.823
5.403
1.333
3.917
56
23
3
3.183
7.317
2.076
2.491
3.528
3.083
58
24
2
3.405
7.810
8.469
9.597
3.104
7.656
60
25
2
3.810
8.226
4.115
6.347
2.271
4.271
Total as £ (duration • eggs/f/d) =
281.6
294.3
181.9
174.7
142.0
220.1
Larval Survival: The Besser et al. (2012b) spreadsheet also has data for larval
survival after 14 and 21 days for eggs collected at three time points. The fraction
surviving 21 days was used here. For each treatment, the probability of the early
life stage (i=l) surviving each day equals the fraction surviving for 21 days,
raised to the 1/21 power: ox = erL = (21-d Surv)121, shown in Table 4.
C-95
-------
Juvenile and Adult Survival: A second spreadsheet, Besser et al. (2012c), has
data on juvenile and adult survival after 30 and 58 days. The fraction surviving
58 days was used (Table 4). Parallel to the handling of larval survival, for each
treatment the juvenile-adult daily survival probability, erJA = (58-d Surv)158, as
shown in the table. This value applies to life stages i=2-25 (er2 through a25).
Table 4. Pupfish observed survival and modeled daily survival; fraction hatching and
fraction
"ree of deformity.
Larval
Juv+Adlt
21-d
Daily
58-d
Daily
Fraction
Treat-
Larval
Surv
Juv+Adlt
Surv
Fraction
Free of
ment
Cone
Surv
(oL)
Surv
(oja)
Hatch
Deformity
Control
1
0.9038
0.9952
1.0000
1.0000
0.9023
0.9489
Se-1
3
0.9770
0.9989
1.0000
1.0000
0.9026
0.9727
Se-2
4.4
0.9109
0.9956
0.9250
0.9987
0.8197
0.9563
Se-3
8
0.9600
0.9981
0.9000
0.9982
0.8922
0.9750
Se-4
13
0.9586
0.9980
0.9500
0.9991
0.8988
0.9048
Se-5
27
0.8396
0.9917
0.8750
0.9977
0.9104
0.9174
Formulation of the Population Model: The population growth equation is shown below, in abbreviated
form.
®i.fl FiJ "
CiVi ^3 CI -Fa) 0
0 o3 Vi "ad — >'a)
'^2.5'®'2;S
<7; 5(1 FzsJ
The diagonal of the 25x25 projection matrix has o1 (1-the sub-diagonal has
n,and the top row has n,«?,. All other elements are 0. For life stage i, cr, is the
daily survival probability,is the daily probability of graduating to the next life
stage, and m1 is the fecundity expressed as number of female eggs produced per
female per day, set at one-half the observed eggs/female/day.
The graduation probability, , for individuals in each life stage was calculated as
follows:
mf 1, there would be a slight youthful bias
C-96
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within the life stage, such that slightly more than half would be only 1 day into
the life stage and not ready to graduate, and slightly less than half would be in
their second day and ready to graduate. The above function adjusts for that.1
The projected population growth rate for each treatment was calculated as
follows. The 25x25 projection matrix was placed on an Excel spreadsheet. Each
cell in the diagonal was then modified to subtract the eigenvalue, X, which
represents the population growth rate. That is, each cell in the diagonal was
rewritten as rr,( 1 -y,) - X. The determinant of the 25x25 matrix was then calculated
by function MDETERM. To obtain the population growth rate, Excel's Solver
was then tasked with finding a value for X that yielded a value of zero for the
matrix determinant. In this case,-10"18 < MDETERM < +10"18 was deemed
sufficiently close to zero. Introducing the constraint to look for X values between
1.01 and 1.04 was found helpful for Solver to find the dominant eigenvalue.
When Solver occasionally could not get the determinant within 10~18 of zero,
probably due to a solution oscillation that can occur because the input values y,
are expressed as a function of the solution output X, digits were removed from
Solver's best estimate for X, to provide a new starting value with which Solver
could complete the solution.
Effects on Projected Population Growth Rates: Table 5 and Figure 2 show the model results. Figures
2-B, -C, and -D are almost indistinguishable from Figure 2-A, because hatch and
deformity rates varied so little across treatments. Although population growth
rates at 4.4 - 27 mg Se/kg are less than at 1 - 3 mg Se/kg, the 6-fold increase in
concentration from 4.4 - 27 mg Se/kg yields no change in response.
Consequently, the results do not suggest a selenium-related effect, and no ECi0
can be calculated. Based on the combined influences of egg production and
timing, and survival (with or without percentage hatch and deformities), pupfish
does not appear to be among the most sensitive species.
1 The formula for y is undefined (0/0) under the condition <7=1 and 1=1, so it is not obvious from inspection how it behaves. This
function addresses a model artifact that is called numerical dispersion when it occurs in pollutant transport models. It prevents
overoptimistic rates of moving through the life stages, particularly in the 35-day and 85-day larval and juvenile stages, and allows
a 25-stage model of life duration 180 days to yield precisely the same growth rate as a 180-stage (one day per stage) model,
which was also constructed and checked for comparison. However, in this application where absolute growth rates have no
particular meaning and only relative differences between treatments are of interest, the function does not change the overall
perspective.
C-97
-------
Table 5. Model output: daily population growth rates as X (factor increase) and r (=ln X), for
models that account for survival, fecundity and its timing, and optionally also hatch and/or
deformities. Because X is responding to all the treatment parameters included in the model, its
Treat-
ment
Cone
Factors included in model:
All account f
or survival (cL , Oja
Hatch
and fecundity (m) a
deformity
nd its timing
hatch & deform.
r
R
r
r
Control
Se-1
Se-2
Se-3
Se-4
Se-5
1
3
4.4
8
13
27
1.0337 0.0332
1.0346 0.0340
1.0299 0.0294
1.0285 0.0281
1.0291 0.0287
1.0294 0.0290
1.0330 0.0324
1.0338 0.0333
1.0284 0.0280
1.0277 0.0273
1.0283 0.0279
1.0288 0.0283
1.0334 0.0328
1.0344 0.0338
1.0295 0.0291
1.0283 0.0279
1.0283 0.0279
1.0288 0.0284
1.0326 0.0321
1.0336 0.0331
1.0281 0.0277
1.0275 0.0271
1.0276 0.0272
1.0281 0.0277
C-98
-------
c
o
Q.
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D£
CD
+J
V)
.3*
HE?
<
-t—»
o
-Q
-O
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DC
1.2
1
0.8
0.6
0.4
0.2
0
i o
i
o
o o
A
~ ¦
O
O
O
~ population growth
Oeggs/female-d
O 21-d larval surv
¦ .58-d juv-adlt surv
8
16
32
Egg concentration {mg Se/kg dw)
c
o
Q.
f/)
CD
CC
T?
CD
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p
tT
<
o
-Q
-Q
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o
o
population growth
Oeggs/female-d
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A58-d juv-adlt surv
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)!¦-. free of deformity
8
16
32
Egg concentration {mg Se/kg dw)
c
o
Q.
to
CD
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QJ
4->
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3
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4J
4-*
o
-Q
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0.8 -
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o
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+
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population growth
eggs/female-d
21-d larval surv
58-d juv-adlt surv
—
2 4 8
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t
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32
Egg concentration {mg Se/kg dw)
c
o
Q.
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CD
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1.2
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0.8
0.6 -
0.4 -
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o
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eggs/female-d
21-d larval surv
58-d juv-adlt surv
hatch
free of deformity
8
O
16
32
Egg concentration (mg Se/kg dw)
Figure 2. Abbott-adjusted pupfish response as modeled population growth rate (solid-filled
symbols) and observed eggs per female per day, larval survival, and juvenile and adult
survival (open symbols). Where used in the population model (to modify fecundity),
hatch and deformity are shown as open symbols. Some open-symbol points are
obscured beneath solid-symbol points. (A) Upper left, egg production and survival only,
(B) upper right, adds in influence of percent hatch, (C) lower left, adds in influence of
deformities, and (D) lower right, adds in influence of percent hatch and deformities.
C-99
-------
Isolating the Influence of Timing of Egg Production: By combining survival with egg production and
its timing in the above analysis, the assessment obscures the influence of timing:
the issue that was the main reason for undertaking population modeling in the
first place. The concern is whether selenium exposure could delay reproduction,
thereby yielding reduced population growth. To help isolate the influence on the
timing of egg production, two population model runs were performed where all
treatments were assigned one of two daily survival rates (0.99 or 0.999) spanning
the full range of daily survival rates observed in the 21 and 58 day survival
calculations. That is, with survival held constant, the only factors varying across
treatments were egg production and timing.
The results are shown in the table below. The Abbott-adjusted results are plotted
in Figure 3. Although the relative differences in Figure 3 population growth rates
are subdued compared to the wider variation in egg production, this is merely a
consequence of the predicted population growth rate being more responsive to
survival than to reproduction. It is still apparent that the variations in total egg
production are affecting growth rate. The question to be addressed here is
whether increasing selenium concentration yields a decline in growth rate beyond
the pattern reflecting total egg production.
Population growth rates, as influenced only by differences in egg
production and timing
Treat-
ment
Cone
With only egg production (m) and its timing
variable across treatments
<7=0.999
<7=0.99
r
r
Control
1
1.0339
0.0334
1.0246
0.0243
Se-1
3
1.0338
0.0333
1.0245
0.0242
Se-2
4.4
1.0310
0.0306
1.0217
0.0215
Se-3
8
1.0293
0.0289
1.0201
0.0199
Se-4
13
1.0293
0.0288
1.0200
0.0198
Se-5
27
1.0324
0.0318
1.0231
0.0228
Inspection of Figure 3 indicates that when survival is assigned a constant value
across treatments, the pattern of population growth differences across treatments
does not suggest an additional selenium-accentuated factor depressing population
growth rate. Population growth at 13 and 27 mg Se/kg is slightly higher than
might be expected from total egg production, when compared to lower
concentrations. The lack of influence of selenium exposure on timing of egg
production is also illustrated by comparing each treatment's cumulative
proportion of egg production over the course of the test, as shown in Figure 4.
Although the treatments differ somewhat in the temporal pattern of their egg
production, there is no consistent relationship with selenium exposure.
C-100
-------
T3
f3
O
jn
<
-------
Chronic Value: In other selenium studies, egg production and percent hatch have not generally
been thought to be related to selenium exposure. Although Besser et al. (2012)
noted that repeated measures ANOVA indicated a potential interaction between
selenium treatment and egg production on particular sampling dates, a thorough
examination of the study data from multiple perspectives indicates no statistically
significant or biologically apparent effect of selenium on egg production, timing
of egg production, or percent hatch at or below the highest tested concentration
of 27 mg Se/kg (dw). Likewise there was no discernible effect on deformity
rates.
In the separate tests of F1 larval survival at 21 days and of F1 juvenile-adult
survival at 58 days, the highest treatment, 27 mg Se/kg (dw), displayed lower
survival than any other treatment. Although the reduction was not sufficient to be
statistically significant, Besser et al. (2012) suggest that this is indicative of a
threshold. Note that among toxicity tests in general, the 10% effect level of the
ECio might or might not be statistically significant from the perspective of
hypothesis testing.
Shown below are the survival rates for the 27 mg Se/kg treatment adjusted to the
control (Abbott-adjusted), or similarly adjusted to the average survival at all
lower treatments (some of which had better survival than the controls). Either
way the adjustment is done, results are similar. (These survival data, Abbott-
adjusted, are included in Figure 2.)
27 mg Se/kg treatment:
Larval
Surv at 21
days
Juv-Adlt
Surv at 58
days
adjusted to control
adjusted to all lower treatments
92.9%
89.1%
87.5%
91.6%
The effect level at 27 mg Se/kg was thus 7% - 13% in the above comparisons.
While the concentration response curve is not sufficiently defined to allow
confident assignment of an ECio, the data suggest a chronic value in the general
neighborhood of 27 mg Se/kg.
An effect level of 27 mg Se/kg egg for the pupfish in this study is consistent with
the findings of Saiki et al. (2012a) who evaluated selenium in two related species
in the Salton Sea, California. These authors measured 3.09 to 30.4 mg/kg whole
body Se levels in mosquitofish and sailfin mollies and based on a lack of a
negative relationship with the catch-per-unit-effort deduced these species were
not adversely affected by selenium. They extrapolated the finding of selenium
tolerance to the pupfish based on the results of another study (Saiki et al 2012b)
in which mosquitofish and sailfin mollies accumulated similar levels of selenium
to the pupfish. Note: the ratio of selenium in whole body to egg tissues in the
pupfish was approximately 1:1 in the Besser study (see first table in the pupfish
study summary above).
C-102
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Staub, B.P. W.A. Hopkins, J. Novak, J.D. Congdon. 2004. Respiratory and reproductive characteristics
of eastern mosquitofish (Gambusia holbrooki) inhabiting a coal ash settling basin. Arch. Environ.
Contamin. Toxicol. 46:96-101.
Test Organism:
Exposure Route:
Study Design:
Effects Data:
Eastern mosquitofish (Gambusia holbrooki)
Waterborne and Dietary - field exposed
Fish were collected from a contaminated ash basin (ASH) and a reference pond
(REF)
In July 1999, male eastern mosquitofish were collected from ASH and REF
(n=26, n=20, respectively) for measurement of standard metabolic rate (SMR). In
July 1999, gravid female eastern mosquitofish were collected from ASH and
REF and transported to a laboratory for testing. To ensure all females were
fertilized in the field, all offspring used in testing were limited to three weeks
after collection. (Eastern mosquitofish are live-bearers with a four week gestation
period.) Response variables compared between ASH and REF were (1) SMR of
males, (2) brood size of females, (3) percent of live offspring at parturition, and
(4) trace element concentration in females and offspring.
SMRs of males, brood size of females, and offspring viability were not
significantly different between sites. Average (n=5) concentrations of selenium in
females were 11.85 and 0.61 mg/kg dw in ASH and REF sites respectively. The
average concentrations of selenium in offspring were 15.87 mg/kg dw and below
detection in ASH and REF sites, respectively. The authors point out that the
selenium concentrations are an under-estimate of the field levels since the
females were allowed to depurate during their time in the laboratory prior to
parturition.
Chronic Value:
>11.85 mg Se/kg dw whole body
C-103
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Saiki, M.K., B.A. Martin, and T.M. May. 2004. Reproductive status of western mosquitofish inhabiting
selenium-contaminated waters in the grassland water district, Merced County, California. Arch. Environ.
Contamin. Toxicol. 47:363-369.
Test Organism:
Exposure Route:
Study Design:
Effects Data:
Western mosquitofish (Gambusia afftnis)
Waterborne and Dietary - field exposed
Fish were collected from selenium-contaminated sites and reference sites in the
San Joaquin River watershed.
Western mosquitofish were collected in June and July 2001 from San Luis Drain
(SLD) at Gun Club Road (Se-contaminated site), North Mud Slough at Gun Club
Road (MSN1; reference site); North Mud Slough at State Highway 140 (MSNs;
Se-contaminated site); San Joaquin River at Lander Avenue (SJR; reference site).
20 gravid females from each site were held in the laboratory for two weeks to
quantify live and dead births and to make other measurements. Only 17 females
from SLD were collected. Live and dead fry were visually examined under low
magnification with a binocular microscope for evidence of external abnormalities
(teratogenic symptoms such as spinal curvature, missing or deformed fins, eyes
and mouths and edema).
The percentage of live births was high at both Se-contaminated sites (96.6 to
99.9%) and reference sites (98.8 to 99.2%). There were no obvious anomalies
(e.g., deformities, edema) observed during the study. The concentration of
selenium in 4 postpartum females from the site with the highest selenium
concentration, SLD, ranged from 13.0 to 17.5 mg Se/kg dw (geometric mean of
the high and low is 15.1 mg Se/kg dw. The concentration of selenium of western
mosquitofish collected at each site is in Table D-8.
Chronic Value:
>15.1 mg Se/kg dw whole body
Table D-8. Selenium in whole body samples of western mosquitofish from study sites
Site
N
[Se], mg/kg dw
SLD
8
18.1
MSN2
24
9.31
MSN1
20
2.72
SJR
22
0.907
C-104
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Coughlan, D.J. and J.S. Velte. 1989. Dietary toxicity of selenium-contaminated red shiners to striped
bass. Trans. Am. Fish Soc. 118:400-408.
Test Organism:
Exposure Route:
Test Treatments:
Striped bass (Morone saxitilis; adults from Lake Norman, NC, approximately
250 g each)
dietary only
Treated fish were fed selenium contaminated red shiners (1 g) from Belews Lake,
NC (9.6 mg Se/kg ww or 38.6 mg Se/kg dw based on a mean reported moisture
content of 75.1 percent). Control fish were fed golden shiners from a local bait
dealer (0.3 mg Se/kg ww or 1.3 mg Se/kg dw based on a mean reported moisture
content of 76.3 percent).
Test treatments were as described above. Two tanks contained treated fish (n =
20 fish total), and one tank of fish served as the control (n = 10 fish). Each tank
received a continuous flow of soft well water (hardness and alkalinity approx. 30
mg/L as CaC03) throughout the exposure.
Test Duration:
80 days
Study Design: During the experiment, all striped bass (n = 10 per tank) were fed to satiation
three times per day. Pre-weighed rations of live red shiners (treated fish) and
golden shiners (controls) were added to the tanks and allowed 5 hours to feed.
Uneaten prey was removed and weighed. Composite whole-body samples of
each prey fish were collected at regular intervals throughout the study for whole-
body tissue selenium analysis. The final selenium concentration in epaxial white
muscle was determined for surviving striped bass at the end of the test. Moribund
striped bass were sacrificed so as to obtain muscle tissue samples for selenium
analysis. Samples of liver and trunk kidney of these and the surviving striped
bass were dissected for observations of histopathology.
Effects Data: Striped bass fed selenium-laden red shiners exhibited changes in behavior
(lethargy, reduced appetite), negligible weight gain, elevated selenium
concentrations in muscle, histological damage, and death. Control fish ate and
grew well, and behaved normally. Average selenium ingestion was between 60
and 140 ®g Se/fish per day until day 30. Appetite of the treated fish appeared to
be significantly reduced beyond this point compared to the appetite of the control
group. By day 78, all striped bass fed the Se-laden red shiners either had died or
were moribund and sacrificed for analysis. The final selenium concentration in
muscle of treated striped bass averaged from 3.5 (tank 1) and 4.0 (tank 2) mg/kg
ww, or 16.2 and 18.5 mg/kg dw, respectively, assuming 78.4 percent moisture
content in muscle tissue; default May et al (2000) value for all species. The final
selenium concentration in muscle of control striped bass fed uncontaminated
golden shiners averaged 1.1 mg/kg ww, or 5.09 mg/kg dw (assuming 78.4
percent moisture content in muscle tissue; default May et al (2000) value for all
species).
Chronic Value: The chronic value for percent survival of striped bass relative to final selenium in
muscle tissue after being fed Se-laden red shiners is <16.2 mg/kg dw.
An EC2o value could not be calculated for this data set because the data did not
meet the assumptions required for analysis.
C-105
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Bryson, W.T., W.R.Garrett, M.A. Mallin, K.A. MacPherson, W.E. Partin, and S.E. Woock. 1984.
Roxboro Steam Electric Plant 1982 Environmental Monitoring Studies, Volume II, Hyco Reservoir
Bioassay Studies. Environmental Technology Section. Carolina Power & Light Company.
28-dav Embryo/Larval Study
Test Organism:
Exposure Route:
Study Design:
Bluegill sunfish (Lepomis macrochirus; embryos and larvae)
dietary and waterborne - field exposure
Native adult bluegill were collected from Hyco Reservoir in Person County,
North Carolina and from a nearby control lake (Roxboro City Lake). Hyco
Reservoir is a cooling lake for Carolina Power & Light and receives the
discharge from the ash storage pond. No selenium values were given for Hyco
Reservoir, total selenium was not detected in the control lake (<1 (.ig/L). A mean
selenium for the ash pond effluent from a previous study was 53 (ig/L (N=59;
range 35-80 (.ig/L).
All combinations of crosses between the Hyco and control fish were made using
gametes from the collected fish. Fertilized eggs were exposed in egg cups to 0,
20 and 50 percent ash pond effluent under flow-through conditions. Percent hatch
and swim-up successes were measured. Swim-up larvae were released to
exposure tanks where there were fed zooplankton collected from Hyco and the
control lake. Larvae were observed for 28 days at which time survival and weight
were measured.
Effects Data: Survival to the swim-up stage was different between larvae from Hyco females
fertilized with either male type and those larvae from control females fertilized
with either male type. All crosses involving a Hyco female resulted in larvae
exhibiting 100 percent mortality prior to reaching swim-up. Percent survival
from hatch to 28 days for larvae from control females exposed to control water
and fed control lake zooplankton was only 5 and 12 percent for the two replicates
so no meaningful comparisons can be made to the different dilution exposures or
diet exposure. The mean concentrations of selenium in the ovaries, female liver
and female muscle were 49, 130, and 84 mg/kg dw, respectively.
Effect level: <49, <130 and <84 mg Se/kg dw in adult ovaries, liver and muscle,
respectively
Chronic Value: <49.65 mg Se/kg dw in whole body using the muscle to whole body equation
<84 mg Se/kg dw maternal muscle
<49 mg Se/kg dw ovary
C-106
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Ingestion Study
Test Organism:
Exposure Route:
Study Design:
Bluegill sunfish (Lepomis macrochirus; 30-day old larvae)
Dietary and waterborne - field exposed adults
Juvenile bluegill from crosses with females in 0, 20 and 50 percent ash pond
effluent were transferred to control water and fed zooplankton from either Hyco
or the control lake. Selenium in Hyco and control zooplankton was 45 and 1.9
mg/kg dw, respectively. Duration was not given.
Survival and observations on pathology and morphology were made in the two
diet treatments.
Effects Data: Mortality in larvae fed control zooplankton was 23.7 percent, whereas mortality
in larvae fed Hyco zooplankton was 97.3 percent. There were no differences in
survival (for two diet treatments) in larvae that were raised for the 30 days prior
to the test in different effluent concentrations (0, 20 50 percent). The average
selenium concentrations in the larvae fed control and Hyco zooplankton were 1.9
and 24.7 mg/kg dw, respectively.
Effect level for larval survival: <24.7 mg Se/kg dw in larvae
Chronic Value: None recommended for larval tissue.
C-107
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Bryson, W.T., W.R.Garrett, M.A. Mallin, K.A. MacPherson, W.E. Partin, and S.E. Woock. 1985a.
Roxboro Steam Electric Plant Hyco Reservoir 1983 Bioassay Report. Environmental Services Section.
Carolina Power & Light Company. September 1985.
28-dav Embryo/Larval Study
Test Organism: Bluegill sunfish (Lepomis macrochirus; embryos and larvae)
Exposure Route: dietary and waterborne - field exposed
Resident adult bluegill were collected from Hyco Reservoir in Person County,
North Carolina and from a nearby control lake (Roxboro City Lake). Hyco
Reservoir is a cooling lake for Carolina Power & Light and receives the
discharge from the ash storage pond. For embryo/larval study up to swim-up
stage, control fish were collected from the unaffected portion of Hyco.
Study Design: Repeat of 1982 28-dav Embryo/Larval Study. Three crosses between: Hyco
female and Hyco male; control female with Hyco male; and control female with
control male. Gametes were fertilized and maintained for the 28-day test in ash
pond effluent dilutions of 0, 20 and 50 percent. Percent hatch, percent swim-up
success and survival were measured to 28 days post hatch. Two treatments were
replicated and fed zooplankton collected from Hyco-affected and Hyco-
unaffected (control). Larvae were observed for 28 days at which time survival
and weight were measured.
Embryo/Larval Study up to Swim-up Stage. Five crosses were made between fish
collected from the affected and unaffected areas. Percent hatch, percent swim-up
and survival were measured until swim-up (approximately 3-4 days after hatch).
Effects Data: 28-dav Embryo/Larval Study. All larvae that hatched from eggs obtained from
Hyco females died prior to completing swim-up (see table below).
Effect level (larval survival): <30, <33 and <59 mg Se/kg dw for adult female
bluegill in ovaries, liver and muscle, respectively
C-108
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Summary of 28-day embryo larval study
%
effluent
Parent
source in
cross
MXF
% hatch
% swim-
up
%
survival,
28-days
Adult tissue, mg Se/kg dw
Gonad
Liver
Muscle
M
F
M
F
M
F
0
HXH
92
0
0
33
30
43
33
62
59
20
HXH
98
0
0
33
30
43
33
62
59
20
HXH
92
0
0
33
30
43
33
62
59
50
HXH
97
0
0
33
30
43
33
62
59
0
HXC
89
87
18
33
2.2
43
4.4
62
2.7
20
HXC
96
96
34
33
2.2
43
4.4
62
2.7
50
HXC
60
84
58
33
2.2
43
4.4
62
2.7
0
CXC
79
95
40
nd
2.2
37
4.4
27
2.7
20
CXC
90
96
36
nd
2.2
37
4.4
27
2.7
20
CXC
88
97
25
nd
2.2
37
4.4
27
2.7
50
CXC
72
92
42
nd
2.2
37
4.4
27
2.7
Chronic Value: <36.49 mg Se/kg dw in whole-body using the muscle to whole body equation.
<59 mg Se/kg dw muscle
<30 mg Se/kg dw ovary
Embryo/larval study to swim-up. Percent swim-up of larvae from parents
collected in non-affected Hyco averaged 93 percent, whereas percent swim-up
from larvae collected from affected Hyco was 12 percent. Effect levels were
determined for adult female and larval tissues. Larval tissues were averaged
across effluent concentrations (geometric mean).
Effect level (percent swim-up):
Adult female ovaries: >9.1 mg/kg dw; <30 mg/kg dw
Adult female liver: >26 mg/kg dw, <33 mg/kg dw
Adult female muscle: >25 mg/kg dw, <59 mg/kg dw
Larvae: >12.8 mg/kg dw; <165 mg/kg dw
C-109
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Summary of Embryo/Larval Study up to Swim-up - Affected vs Unaffected Hyco
date
of
fert.
Parents'
capture
location in
Hyco
Percent hatch
Percent swim-up
Selenium in tissue, mg/kg dw
at % effluent
at % effluent
Adult female
0
20
50
0
20
50
Ovary
Liver
Muse
Larvae
6-24
affected
93
98
94
0
0
0
30
33
59
0: 130
20: 120
6-27
affected
99
88
77
0
0
0
30
33
59
0: 130
20:120
6-28
affected
29
34
35
25
14
3
30
33
59
0: 130
20:120
6-28
affected
98
86
91
5
0
0
30
33
59
0: 130
20:120
6-29
affected
88
93
85
59
42
25
30
33
59
0: 130
20:120
7-14
unaffected
92
80
84
79
92
89
9.1
26
25
0: 19
20: 11
50: 10
7-26
unaffected
99
94
93
100
98
98
9.1
26
25
0: 19
20: 11
50: 10
7-27
unaffected
76
84
86
100
89
91
9.1
26
25
0: 19
20: 11
50: 10
Chronic Value: The chronic value estimated for the percentage larvae reaching the swim-up stage
is presented as a range:
>25 mg Se/kg dw (unaffected area) and <59 mg Se/kg dw muscle (affected area)
>30 mg Se/kg dw (unaffected area) and <9.1 mg Se/kg dw ovary (affected area)
C-110
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Bryson, W.T., K.A. MacPherson, M.A. Mallin, W.E. Partin, and S.E. Woock. 1985b. Roxboro Steam
Electric Plant Hyco Reservoir 1984 Bioassay Report. Environmental Services Section. Carolina Power &
Light Company
Ingestion Study
Test Organism:
Exposure Route:
Test Treatments:
Bluegill sunfish (Lepomis macrochirus; juvenile- hatchery raised)
Dietary only
5 diets: Se form (nominal selenium concentration in base diet)
seleno-DL-cystine (5 mg/kg)
seleno-DL-cystine (10 mg/kg)
seleno-DL-methionine (5 mg/kg)
sodium selenite (5 mg/kg)
Hyco zooplankton (5 mg/kg)
Test Duration:
60 days
Study Design: Each treatment contained 40 fish which were maintained in a flow-through
system. Fish were fed at 3 percent of their body weight. Length and weight were
measured on days 30 and 60. Total selenium was measured in liver and whole-
body.
Effects Data: No decreased length or weight in any of the Se-diets relative to the control.
Chronic Value: all values are whole-body
seleno-DL-cysteine: >2.16 mg Se/kg dw
seleno-DL-cysteine-2X: >3.74 mg Se/kg dw
seleno-DL-methionine: >2.46 mg Se/kg dw
sodium selenite : >1.21 mg Se/kg dw
Hyco zooplankton: >2.35 mg Se/kg dw
Because none of the selenium-spiked diet formulations affected growth of
juvenile fish at the concentrations tested, the chronic value selected for this study
is >3.74 mg Se/kg dw for the seleno-DL-cysteine-2X formulation.
Source and Exposure Embryo-Larval Study
Test Organism: Bluegill sunfish (Lepomis macrochirus; Adults from Hyco and a control lake)
Exposure Route: Dietary and waterborne - field exposure
Test Treatments: Four treatments:
Hyco-collected fish exposed to Hyco water in flow through spawning tanks.
Hyco-collected fish in control water in flow through spawning tanks.
Control fish exposed to Hyco water in flow through spawning tanks.
Hyco-collected fish in control water in flow through spawning tanks.
Test Duration: Adult fish were in spawning tanks 4-7 months
C-lll
-------
Study Design:
Eggs from each treatment were observed for percent hatch and percent swim-up.
Effects Data: Fish collected from the control lake did not spawn. Percent hatch and percent
swim-up from Hyco fish in Hyco and control water are given in the table below.
The percent hatch and percent swim-up were >83 and >83 for all the Hyco fish
suggesting no effect for these endpoints.
Source of
parents
Se in parental
liver tissue,
mg/kg dw
Water type
for eggs and
larvae
N
Percent hatch
Percent
swim-up
Hyco
18.6
Hyco
16
86.6
91.1
Hyco
18.6
well water
10
83.8
95.5
Control
13.8
Hyco
a
a
83.3
Control
13.8
well water
12
86.0
97.4
a percent hatch unknown.
Chronic Value: The chronic value for this study is >18.6 mg Se/kg dw liver tissue.
C-112
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Gillespie, R.B. and P.C. Baumann. 1986. Effects of high tissue concentrations of selenium on
reproduction by bluegills. Trans. Am. Fish. Soc. 115:208-213.
Test Organism:
Exposure Route:
Test Treatments:
Study Design:
Effects Data:
Chronic Value:
Bluegill sunfish, wild-caught (Lepomis macrochirus; adults; embryos and larvae)
dietary and waterborne - field exposure
High selenium adult fish were collected (electrofishing and with Fyke nets) from
Hyco Reservoir. Low selenium adult fish were collected from Roxboro City
Lake, Roxboro, NC.
All possible combinations of bluegill parents from Hyco Reservoir and Roxboro
City Lake were artificially crossed in June and July, 1982 and 1983, respectively.
Fertilization success was assessed by stripping subsamples of 100 to 500 eggs per
female and combining them with 2 ml of sperm. All zygotes were reared in
Roxboro City Lake water and percent fertilization was estimated 2-3 hours later
as the proportion of mitotically active zygotes. To estimate hatching success,
gametes were combined as before and subsamples of 100 to 300 embryos per
cross were transferred to egg cups and maintained in closed aquaria receiving re-
circulated Roxboro City Lake water. Percent hatch (approx. 2d at 22 to 25°C)
was based on the number of yolk-sac larvae. In 1982, about 200 embryos from 8
crosses were observed and preserved at intervals up to 40 h after fertilization, and
about 450 larvae were preserved at intervals of 40 to 180 h after fertilization. In
1983, about 1,800 larvae were observed and preserved from 40 to 150 hr from
crosses involving females from Hyco Reservoir, and about 40-300 hr for crosses
involving females from Roxboro City Lake (10 crosses total).
No significant differences were found in percent fertilization or in percent hatch
among parent combinations from the 18 crosses made in June 1982 and July
1983. In contrast, larvae from all crosses involving a Hyco female were
edematous; 100 percent of the larvae were abnormal in 7 of 8 crosses. Note: This
outcome was observed when the same female from Hyco Reservoir was crossed
with males from either Hyco Reservoir or Roxboro City Lake. The range of
selenium concentrations in the ovaries of Hyco Reservoir females used for the
cross experiments was from 5.79 to 8.00 (GM = 6.945 mg/kg ww; n=7). The
reported concentrations of selenium in ovaries and carcasses of females collected
from Hyco Reservoir in 1982 and 1983 were 6.96 and 5.91 mg/kg ww (n=22 and
28, respectively). The reported concentrations of selenium in ovaries and
carcasses of females collected from Roxboro City Lake in 1982 and 1983 were
0.66 and 0.37 mg/kg ww (n=14 and 19, respectively). The mean selenium
concentration in bluegill larvae (n=222) from artificial crosses of parents from
Hyco Reservoir was 28.20 mg Se/kg dw.
<46.30 mg Se/kg dw ovary using 85 percent moisture for ovaries measured in
study.
C-113
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Doroshov, S., J. Van Eenennaam, C. Alexander, E. Hallen, H. Bailey, K. Kroll, and C. Restrepo.
1992. Development of Water Quality Criteria for Resident Aquatic Species of the San Joaquin River; Part
II, Bioaccumulation of Dietary Selenium and its Effects on Growth and Reproduction in Bluegill
(Lepomis macrochirus). Final Report to State Water Resources Control Board, State of California.
Contract Number 7-197-250-0.
Test Organism: Bluegill sunfish (Lepomis macrochirus)', Population A: selenium
bioaccumulation observations used 113 g (range 30-220 g) obtained from
Rainbow Ranch Fish Farm, California. Population B: spawning performance
observations used 106 g (range 65-220 g) females and 164 g (range 80-289 g)
males obtained from Chico Game Fish Farm.
Exposure Route: Dietary only
Dietary
Seleno-L-methionine added to trout chow; the three nominal dietary
concentrations of 8, 18 and 28 mg/kg seleno-L-methionine were measured at 5.5,
13.9, and 21.4 mg/kg Se (moisture content 13 to 16%).
Test Duration: 140 days
Study Design: Population A fish and Population B females were fed nominal dietary treatments
8, 18 and 28 mg/kg seleno-L-methionine; Population B males were fed untreated
diets until the start of spawning. Population A fish were sampled on days 0, 30,
58, 86 and 114 for Se measurement. At least 3 females were sampled each event.
Fish remaining after day 114 were transferred to an outdoor pond fed untreated
diet and sampled on day 144 for depuration analysis.
On day 120 Population B males and females were paired for natural spawning
which had limited success. Fish were maintained in treatment tanks and females
were monitored for egg ripeness. When ripe, females were induced to ovulate
and ova were fertilized in vitro with semen stripped from males. Fertilized eggs
were sampled for fertilization success, Se content, and two live sub-samples for
bioassay, one a 30-day embryo-larval test and another for larval development
during first 5 days after hatching.
Larval development: after hatching, 100 larvae were transferred to beakers and
samples were examined daily for normal, abnormal and dead were recorded.
Larval bioassay: 90 fertilized eggs from each female were placed in groups of
approximately 30 eggs. Larvae and fry were fed rotifers and brine shrimp nauplii
through the 30 day observation.
Effects Data: Selenium concentrations in parental tissues for Populations A and B are given in
Tables 1 and 2, respectively. Treatment effects were only observed on early
development bioassays. In the 5-day larval bioassay, systemic edema and
underdeveloped lower jaw were apparent in all larvae in the 28 mg/kg dietary
treatment by day 3 and complete mortality by day 5, except for two progenies
where 10% of the larvae appeared normal. No abnormalities were observed in
control and 8 mg/kg treatment. 3 of the 6 progenies in the 18 mg/kg treatment
exhibited 10 to 20% larvae with similar abnormalities (Table 3). The average
proportion of larvae with edema were 5% in 18 and 95% in 28 mg/kg, both of
C-114
-------
these were statistically different from the control (0% edema).
For analysis of the effect level determination, 4-day edema observations were
used (Table 4) rather the 5-day data because the latter were difficult to interpret
relative to edema because of almost complete mortality at the highest
concentration (although the 4-day and 5-day edema observations were almost
identical). Of the 33 edema measurements, only 15 could be used because not all
the individual-replicate egg concentrations were reported. Table 4 also shows the
treatment averages, which are only slightly different than the 5-day edema data.
These averages do not match the average of the individual replicates in this table
because they are for all the replicates, not just those with which concentrations
could be paired.
The Se egg and edema data from Table 4 are plotted on Figure 1. The individual
replicates are analyzed using TRAP. TRAP warns about inadequate partial
responses because the partial responses are less than 10% or greater than 90%,
and there are no data between 10 and 90%. However, for this dataset, these
partial responses at both ends, albeit small, are sufficiently informative based on
multiple lines of evidence (e.g., same response on both days 4 and 5, other
endpoints that show effects at treatment 18, and several instances of edema at
treatment 18 in contrast to absolutely none for many observations at any lower
concentration). And because treatment 18 does have an effect of several percent
or so, estimating the ECi0 near these points is defensible; the ECi0 is 22.6 mg/kg
egg. The ECi0 of 22.6 mg Se/kg egg dw was selected for the chronic value
because it was determined using the individual replicates rather than treatment
averages as was done in the previous draft document. The ECi0 of 22.6 mg Se/kg
egg is slightly higher than that in the previous draft which used means rather than
replicate data (Figure 3).
In the 30-day larval survival bioassay, statistical difference was only in the
highest test treatment for survival and growth measurements, length and weight
(Table 5). The proportion of abnormal larvae was higher in the selenium-treated
diets but was not significantly different from the control. The percent of
abnormal larvae in the 18 mg/kg treatment (7.2%) was only slightly higher than
the control (6.3%).
Authors present the effect level for bluegill at the 18 mg/kg dietary treatment
(NOEC 8 mg/kg) based on proportions of edema and delayed resorption of the
yolk sac. The latter endpoint is based on significantly greater yolk area and oil
globule area in the 18 and 28 mg/kg treatments.
The most sensitive endpoint, percent edema, as a function of selenium in
maternal muscle dw, was fitted to a TRAP tolerance distribution analysis using
the individual replicates (Figure 2). The response is steep and the ECio estimate
is 15.7 mg/kg. This basically is setting the ECi0 to the average of the two
replicates with nominally 10% edema (15.4 and 16.6 mg/kg), with 90% edema
occurring at only a slightly higher concentration (17.3 mg/kg).
Chronic Value: ECi0 value (edema) at 22.6 mg Se/kg egg dw or 15.7 mg Se/kg muscle dw
Chronic Value is 22.6 mg Se/kg eggs dw.
C-115
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Table 1. Selenium Concentrations (mg/kg dw) in Bluegills from Population A Day 113 of
Dietary
treatment
Control
8 mg/kg dw
18 mg/kg dw
28 mg/kg dw
Ovary
2.17(0.05)
10.89 (1.83)
26.17(0.07)
40.32 (2.44)
Female liver
2.51 (0.32)
NA
22.75 (2.96)
40.68 (2.14)
Testis
2.65 (0.21)
9.87
16.38 (0.71)
29.70 (5.02)
Male liver
4.10(0.37)
14.32
24.28 (4.54)
52.47 (5.23)
Table 2. Selenium Concentrations (mg/kg dw) in Bluegill Parents (Population B) Used in Larval
Toxicity Tests
Dietary
treatment
Control
8 mg/kg dw
18 mg/kg dw
28 mg/kg dw
Male liver
4.07 (0.23)
6.94 (1.58)
20.46 (3.46)
31.63 (1.75)
Testis
1.87 (0.11)
3.64 (0.47)
9.96 (0.45)
15.25 (0.45)
Female liver
4.00 (0.26)
12.33 (1.09)
25.98 (4.28)
47.60 (4.11)
Female muscle
1.47 (0.14)
5.80 (0.79)
10.41 (2.02)
23.64 (2.04)
Ovary
2.23 (0.11)
6.34 (0.47)
14.10 (2.62)
30.63 (3.23)
Eggs
2.81 (0.14)
8.33 (0.63)
19.46 (3.83)
38.39 (3.14)
Larvae
NA
NA
NA
35.30 (4.16)
Fry
1.48 (0.11)
1.25 (0.02)
1.37 (0.06)
1.46 (0.03)
Table 3. 5-day Larval Development Toxicity Test, average (SD)
Dietary
treatment
Control
8 mg/kg dw
18 mg/kg dw
28 mg/kg dw
Free of Edema, %
100
100
95 (2)*
4.3(2.7)*
C-116
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Table 4. 4-day Edema Observations by Replicate from 5-day Larval Toxicity Test
Treatment/Replicate ID
Se egg, mg/kg dw
Se muscle, mg/kg dw
Percent edema (n=10)
08-2C
3.54
2.25
0
18-4C
3.25
0.95
0
8-1S
11.49
7.07
0
8-2S
8.31
5.80
0
8-6S
6.18
1.41
0
18-1S
8.55
2.75
0
18-3S
22.06
15.44
10
18-6S
30.20
16.58
10
28-1S
44.02
NA
100
28-2S
36.31
31.10
100
28-3S
25.21
17.28
90
28-4S
52.18
27.40
100
28-5S
42.40
24.00
100
28-6S
38.47
24.66
100
28-7S
30.12
17.42
90
Treatment
Se egg, mg/kg dw
treatment avg
Percent edema
treatment avg
C
2.81
--
0 (n=140)
8
8.33
--
0 (n=50)
18
19.5
--
6.67 (n=60)
28
38.4
--
97.1 (n=70)
Table 5. Results from 30-day Embryo-larval Toxicity Test, average (SD)
Dietary treatment
Control
8 mg/kg dw
18 mg/kg dw
28 mg/kg dw
Larval survival, %
71 (8.5)
51.9 (26.5)
64.4 (3.4)
2.5 (3.5)*
Larval length, mm
19.1 (1.2)
19.9 (1.2)
19.3 (0.8)
16.6 (2.5)*
Larval weight, mg
114 (24)
133 (27)
119(16)
81 (37)*
Abnormalities in
larvae, %
6.3 (7.9)
15.0 (5.8)
7.2 (3.1)
25.0 (43.3)
* Statistically significantly different from control
C-117
-------
<0
E
CD
T3
LU
100
80
60
40
20
* ¦
10 20
mg Se/kg egg dw
50
—I
100
Figure 1. Bluegill larvae without edema (percent) as a function of the logarithm of selenium
concentrations in eggs. Triangles denote control, circles treatment 8, squares treatment 18, diamonds
treatment 28. The line denotes TRAP fits based on the individual replicates using the tolerance
distribution option with the log-triangular distribution. ECi0 for replicate data is 22.6 mg Se/kg egg dw.
CO
E
CD
"O
111
3
o
sz
100
80 -
60
40 -
20
10
—r-
20
—i—
50
—i
100
mg Se/kg muscle dw
Figure 2. Bluegill larvae without edema (percent) as a function of the logarithm of selenium
concentrations in maternal muscle. Triangles denote control, circles treatment 8, squares treatment 18,
diamonds treatment 28. The line denotes TRAP fits based on the individual replicates using the tolerance
distribution option with the log-triangular distribution. ECi0 for replicate data is 22.6 mg Se/kg egg dw.
C-118
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MED Toxic Response Analysis Mode! 01/0712015 18:10
120 r
80 -
o
60 -
.2
.4
.8
Q
.O
10
12
1.4
1
.6
Log(mg Se/kg egg dw)
Parameter Summary (Threshold Sigmoid Regression Analysis)
Parameter
Guess
Final Est
StdError
95%LCL
95%UCL
LogX50
1.4428
1.4342
0.0000
1.4342
1.4342
S
5,452
4.712
0.000
4.712
4.712
Y0
88.33
100.00
0.00
100.00
100.00
Effect. Concentration Summary
% Effect Xp Est 95%LCL 95%UCL
50.0 27.18
20.0 22.71
10.0 20.75
5.0 19.460
VED Toxicity ndstisnshij- Analysis Vodei, Vera on f 21
Figure 3. (From previous draft document) TRAP analysis of bluegill larvae without edema
(percent) as a function of the logarithm of selenium concentrations in eggs.
C-119
-------
Hermanutz et al. 1992. Effects of elevated selenium concentrations on bluegills (Lepomis macrochirus)
in outdoor experimental streams. Environ. Tox. & Chem. 11: 217-224
Hermanutz et al. 1996. Exposure of bluegill (Lepomis macrochirus) to selenium in outdoor experimental
streams. U.S. EPA Report. Mid-Continent Ecology Division. Duluth, MN.
Tao, J., P. Kellar and W. Warren-Hicks. 1999. Statistical Analysis of Selenium Toxicity Data. Report
submitted for U.S. EPA, Health and Ecological Criteria Div. The Cadmus Group.
Test Organism: Bluegill (Lepomis macrochirus; 3 to 4-year old adults)
Exposure Route: Dietary and waterborne followed by dietary only
Dietary and waterborne
Selenite was added to artificial streams which entered the food web; thus, fish
were also exposed to selenium in the diet.
Dietary only
Recovering streams exposed bluegill to selenium in prey organisms. Selenite
addition to water was ceased (selenium in water was below detection level).
Study Design: Eight Monticello artificial streams were used for three separate studies between
1987 and 1990.
Table 1. Study Design.
Stream
Study I
Study II
Study III
Dates
BGa put in station 0-2
BG transferred to sta.
6 End of study
9-1-87
5-16-88
8-22-88
10-88
5-89
8-89
11-89
5-90
7-90
1
Unused
Control
Control
2
Unused
2.5 ng/L
Recovering
3
10 ng/L
10 ng/L
Recovering
4
30 ng/L
Recovering
Recovering
5
Control
Control
Control
6
30 ng/L
Recovering
Recovering
7
Control
2.5 ng/L
Recovering
8
10 ng/L
10 ng/L
Recovering
a BG = Bluegill
C-120
-------
The design of the three Hermanutz et al. studies is included in Table 1 and a schematic diagram of an
artificial stream is provided below (Figure 1). For each study, a random sample of 22-50 adult bluegill
were transferred from stations 0-2 (provided temperatures above 4°C during winter) to station 6 (most
suitable for nests) during mid-May for spawning. Spawning activity was monitored in the streams.
Embryo and larval observations were made in situ and in the laboratory from fertilized eggs taken from
the streams and incubated in the lab.
Figure 1. Schematic Design of One of the Artificial Streams in the Monticello Study
Station Number
0
1
2
Adult barrier
3
inlet
I
Adults from fall to
mid-May
Adult barrier -
Adults from mid-
May to end of study
Adult barrier
7
C-121
-------
Table 2. Effects on Progeny - Study Ia
Egg cup observations
treatment
stream
ovary Se (mg/kg ww)
ovary Se
(mg/kg
dw)b
Geomean
ovary Se
(mg/kg
dw)
% hatch
mean ± SD
% survival
to 4th day
mean ± SD
% edema
mean ± SD
% lordosis
mean ± SD
% hem or r
mean ± SD
Early
Final
Geometric
Mean
control
5
NA
0.53
0.53
2.21
0.79
93.3 ±9.1
69.7 ± 13.9
0.1 ±0.2
1.8 ±2.6
0.1 ±0.3
control
7
0.47
0.01
0.07
0.29
10 ng/L
3
4.29
2.53
3.29
13.73
17.71
71.5 ±22.5
28.8 ± 23.1
80 ± 1.0
11.6 ± 15.9
28.5 ±40.6
10 ng/L
8
4.72
6.37
5.48
22.85
30 ng/L
4
3.71
NA
3.71
15.46
15.46
60.3 ±25.8
9.1 ± 12.9
50.3 ±64.1
6.3 ± 1.8
26.8 ±20.2
Nest observations
treatment
stream
ovary Se (mg/kg ww)
ovary Se
(mg/kg
dw)b
Geomean
ovary Se
(mg/kg
dw)
# active
nests
mean ± SD
# embryos
Collected
mean ± SD
% dead
Embryos
mean ± SD
# larvae
Collected
mean ± SD
% dead
Larvae
mean ± SD
Early
Final
Geometric
Mean
control
5
NA
0.53
0.53
2.21
0.79
6.5 ±2.1
1441 ±205
0.9 ±0.03
3947±1888
3.0 ± 1.1
control
7
0.47
NA
0.47
0.29
10 ng/L
3
4.29
2.53
3.29
13.73
17.71
5.0 ±4.2
1282 ±457
3.2 ±2.9
1169±1093
17.0 ± 21.3
10 ng/L
8
4.72
6.37
5.48
22.85
30 ng/L c
4
3.71
NA
3.71
15.46
15.46
1.0 ± 1.4
361 ±510
0.4
157 ±222
12.1
a Selenium concentrations in table were taken from Hermanutz et al. (1996); effect values were taken from Hermanutz et al (1992).
b used 76% moisture for egg/ovary in bluegill (average of Gillespie and Bauman 1986 and Nakamoto and Hassler 1992) to convert egg/ovary ww
to dw
c No active nests, embryos, or larvae found in one of the 30 (ig/L streams. Therefore, N = 1 for % dead embryos and dead larvae in the 30 ng/L
treatment
C-122
-------
Table 3. Effects on Progeny - Study IIa
Egg cup observations
treatment
stream
No. of
trials
%
hatch
%
survival
to 3rd
day
%
edema
%
lordosis
% hem or r
% healthyb
ovary Se (mg/kg
ww)
ovary Se
(mg/kg dw)c
Early
Final
Geometric
Mean
control
1
6
93.0
75.2
0
0
0
97.8
1.02
0.78
0.89
3.72
control
5
5
96.4
71.5
0
0
0
97.9
1.09
0.76
0.91
3.79
2.5 ng/L
2
0
NA
NA
NA
NA
NA
NA
1.82
1.82
7.58
2.5 ng/L
7
4
81.4
71.6
0
0
3.6
92.2
2.02
3.36
2.61
10.86
10 ng/L
3
3
83.3
57.7
100
11.1
49.3
0
8.1
8.10
33.75
10 ng/L
8
2
91.1
57.1
100
18.2
41.1
0
6.96
12.6
9.36
39.02
rec 30 ng/L
4
0
NA
NA
NA
NA
NA
NA
rec 30 ng/L
6
6
92.9
73.0
17.4
0
11.5
70.7
5.87
13.2
8.80
36.68
Nest Observations
Treatment
Stream
#
active
Nests
#
embryos
Collected
% dead
embryos
#larvae
collected
%
dead
larvae
#samples
wlarvae
%
edema
%
lordosis
%
hemorr
ovary Se (mg/kg ww)
ovary Se
(mg/kg
dw)c
Early
Final
Geometric
Mean
control
1
6
2458
0.94
3252
0.03
7
0
0
0
1.02
0.78
0.89
3.72
control
5
9
1329
0
3435
1.05
13
0
0
0
1.09
0.76
0.91
3.79
2.5 ng/L
2
1
0
2497
0.20
3
4.1
25
77.6
1.82
1.82
7.58
2.5 ng/L
7
5
1462
0
4717
0.08
8
0
0
52
2.02
3.36
2.61
10.86
10 ng/L
3
2
672
0
5376
0.50
9
81.4
5.0
55.5
8.1
8.10
33.75
10 ng/L
8
3
931
0.32
750
0.40
4
50
14.7
26.7
6.96
12.6
9.36
39.02
R 30 ng/L
4
0
NA
NA
NA
NA
NA
NA
NA
NA
R 30 ng/L
6
8
646
0
6782
7.8
16
27.3
0
17.1
5.87
13.2
8.80
36.68
a Selenium concentrations in table were taken from Hermanutz et al. (1996); effect values were taken from Tao et al. (1999).
b Among live larvae that survived up to third day after first larvae hatched; assumes the observations of multiple abnormality types always co-
occurred in the same organism. This may overestimate the actual % healthy when this assumption is violated.
c used 76% moisture for egg/ovary in bluegill (average of Gillespie and Bauman 1986 and Nakamoto and Hassler 1992) to convert egg/ovary ww
to dw
R = recovering stream
C-123
-------
Table 4. Effects on Progeny - Study IIIs*
Egg cup observations
treatment
Stream
number of
trials
% hatch
% survival
to 3rd day
% edema
% lordosis
% hemorr
ovary Se
(mg/kg ww)
ovary Se (mg/kg
dw)b
control
1
2
92
58.6
0
0
0
1.2
5.0
control
5
3
76.7
69.2
0
0.9
0.8
0.93
3.88
R2.5 ng/L
2
3
87.3
66
0
0
0
1.84
7.67
R2.5 ng/L
7
6
87.2
76.5
0
0
0
1.97
8.21
R10 ng/L
3
6.25
26.04
R10 ng/L
8
3
75.3
74.5
0
0
0
2.44
10.17
R 30 ng/L
4
5
92
78
3.82
15.92
R 30 ng/L
6
Nest observations
treatment
stream
# active
nests
# samples
with larvae
% edema
% lordosis
% hemorr
ovary Se
(mg/kg ww)
ovary Se
(mg/kg dw)b
control
1
2
5
0
0
0
1.2
5.0
control
5
2
3
0
0
0
0.93
3.88
R2.5 ng/L
2
5
5
0
0
0
1.84
7.67
R2.5 ng/L
7
5
2
0
0
0
1.97
8.21
R10 ng/L
3
2
4
0
0
0
6.25
26.04
R10 ng/L
8
4
4
0
0
0
2.44
10.17
R 30 ng/L
4
9
13
0
0
0
3.82
15.92
R 30 ng/L
6
a The NOAEC for the study are from recovering 30 (.ig Se/L treatment.
b used 76% moisture for egg/ovary in bluegill (average of Gillespie and Bauman 1986 and Nakamoto and Hassler 1992) to convert egg/ovary ww
to dw
R = recovering stream
C-124
-------
Effects Data: Tables 2 through 4 include exposure and effects data for Study I,
II, and III, respectively. Study I & II deformity and survival data reported in the
tables above from the nest and egg in response to Se concentrations in parental
ovaries (mg/kg dw) were compiled in Table 5 for TRAP analysis. Study I effects
data were obtained from Hermanutz et al. (1992), and corresponding Study I
ovary Se concentrations were obtained from Hermanutz et al. (1996). Study II
and III exposure data were obtained from Hermanutz et al. (1996) and effects
data from Tao et al. (1999).
In this study ovary concentrations were measured in an aliquot of females taken
from each treatment. The exposure and effects data are thus not as directly linked
as they would be in field studies of more recent design - where offspring health
can be directly linked to measured tissue concentrations of their female parent.
In a change from the analyses published in drafts of this criterion document,
ovary, muscle, and whole-body concentrations measured too early in the
exposure period (that is, during the month of May, and labeled "early" in Tables
2 and 3) have not been used because they were not sufficiently co-occurrent with
the effects measurements. On the other hand, the data for the Study II recovering
stream and all Study III recovering streams are included in the analyses. For this
analysis, the nest data continue not to be used, because they were less consistent
than the egg-cup data.
ECioS are based on the combined effects on survival and deformities: that is,
reduction in the percentage of individuals surviving and normal. Table 5 shows
the exposure and effects data used. Figures 2 and 3 show the ovary, and whole-
body concentration-response curves and an explanation of how the ECio values
were derived. The same approach was used for the muscle data, that is, an
interpolation using a nonlinear regression threshold sigmoid equation. The
interpolation is based on the threshold sigmoidal model, with the first
interpolation point set to the HNOEC of 11.2 mg/kg muscle and the average
background survival/normal of 69.1% and the second point set to the LOEC of
21.0 mg/kg and a survival/normal of 5.8%. The resulting ECio is 13.4 mg/kg
muscle dw. The ECi0 estimates for the three tissues (below) are slightly different
than the ECi0 values in the previous draft document. The reason for the
difference is the use of the interpolation method in the current version rather than
an inappropriate usage of a TRAP model in the previous document.
Chronic Value: This study's chronic values for bluegill based on percentage
surviving and free of deformities are the following ECi0 values:
Ovary: 14.7 mg Se/kg ovary dw
Muscle: 13.4 mg Se/kg muscle dw
Whole body: 10.6 mg Se/kg WB dw.
C-125
-------
Table 5. Final Exposure Concentrations and Egg Cup Survival and Deformity Rates Used for TRAP Analysis (Studies I, II, & III). The
percent c
eformity is the maximum percentage of the individual deformity types for each treatment.
Tissue concentration
at end of exposure (dw)
Effects data from Hermanutz et
al. (1996) and Tao et al. (1999)
Study
Treatment
(^g/L)
Se ovary
(mg/kg)
Se muscle
(mg/kg)
Se WB
(mg/kg)
%
Survival
%
Deformity
%Normal
+Surviving
I
Control
2.21
2.05
1.546
69.7
1.8
68.4
I
10
16.73
21.03
18.131
28.8
80
5.76
I
30
>251
No data
No data
9.1
50.3
4.52
II
Control
3.25
1.96
1.63
75.2
0
75.2
II
Control
3.17
2.61
1.47
71.5
0
71.5
II
2.5
7.58
6.73
5.40
No data
No data
No data
II
2.5
14
7.13
4.40
71.6
3.6
69
II
10
33.75
36.51
16.47
57.7
100
0
II
10
52.5
55.25
26.79
57.1
100
0
II
R-30
55
39.78
24.29
79
17.4
65.3
III
Control
5.0
3.37
1.27
62.9
0
62.9
III
Control
3.88
3.11
2.66
68
0
68
III
R-2.5
7.67
5.78
4.17
71.3
0
71.3
III
R-2.5
8.21
6.48
4.25
72.2
0
72.2
III
R-10
10.17
11.20
9.29
63.4
0
63.4
III
R-30
15.92
15.12
13.77
81.1
No data
No data
1 No data were recorded for this treatment, but a value 50%
ligher than the 10 (ig/L treatment was added for inclusion in the analysis.
C-126
-------
100 -
mg Se/kg ovary
Figure 2. TRAP interpolation curve for the Table 5 ovary data. Circles denote active aqueous
exposures and stars denote recovery periods. The interpolation is based on the threshold sigmoidal model,
with the first interpolation point set to the HNOEC of 14.0 mg/kg and the average background
survival/normal of 69.1% and the second point set to the LOEC of 16.7 mg/kg and a survival/normal of
5.76%. The resulting ECi0is 14.7 mg/kg ovary dw.
a>
n?
o
c
-Q
<
13
O
sz
TS
sz
CTJ
CD
>
100
80
60
40
20
~
— %
~\
—i—
10
20
—I
50
mg Se/kg whole body dw
Figure 3. TRAP interpolation curve for the Table 5 whole body data. Circles denote active aqueous
exposures and stars denote recovery periods. The interpolation is based on the threshold sigmoidal model,
with the first interpolation point set to the HNOEC of 9.3 mg/kg whole body and the average background
survival/normal of 69.1% and the second point set to the LOEC of 16.5 mg/kg and a survival/normal of
0%. The resulting ECi0 is 10.6 mg Se/kg whole body dw.
C-127
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Coyle, J.J., D.R. Buckler and C.G. Ingersoll. 1993. Effect of dietary selenium on the reproductive
success of bluegills (Lepomis macrochirus). Environ. Toxicol. Chem. 12:551-565.
Test Organism:
Exposure Route:
Test Duration:
Study Design:
Bluegill sunfish (Lepomis macrochirus; two-year old pond-reared adult fish and
resultant fry)
Dietary and waterborne
Dietary
Seleno-L-methionine added in an aqueous solution to Oregon moist pellets;
moisture content of diet was 25 percent.
Waterborne
Flow through 10 (.ig Se/L nominal, 6:1 ratio of selenate:selenite, 98 percent
purity, adjusted to pH 2 with HC1 to prevent bacterial growth and change in
oxidation states of Se(IV) and Se(VI).
140 days
The experiment consisted of a test control and food control (see Test Treatment
table below) with fish (n=28 initially) in the four remaining treatments fed one of
the four seleno-methionine diets in combination with 10 jj.g Se/L in water.
Spawning frequency, fecundity, and percentage hatch were monitored during the
last 80 days of the exposure period. Survival of resulting fry (n=20) was
monitored for 30 days after hatch. Adults and fry were exposed in separate,
modified proportional flow-through diluters. Fry were exposed to the same
waterborne selenium concentrations as their parents. Adults were fed twice daily
ad libitum. Whole-body selenium concentrations in adult fish were measured at
days 0, 60, and were calculated from individually analyzed carcass and gonadal
tissue (ovaries and testes) at day 140. Eggs not used in percentage of hatch
determinations were frozen and analyzed for total selenium.
Measured Se in:
Test Treatments
1
(test control)
2
(food control)
3
4
5
6
water
(jig Se/L)
0.56
8.4
10.5
10.5
10.1
11.0
diet
(mg Se/kg dw)
0.76
0.76
4.63
8.45
16.8
33.3
C-128
-------
Effects Data: There was no effect of the combination of highest dietary selenium concentration
(33.3 mg/kg dw) in conjunction with exposure to a waterborne selenium
concentration of 11.0 (ig/L on adult growth (length and weight), condition factor,
gonad weight, gonadal somatic index, or reproductive endpoints (i.e., spawning
frequency, number of eggs per spawn, percentage hatch) during the 140-day
exposure (Table 1). The mean corresponding whole-body selenium concentration
in adults exposed to this waterborne and dietary selenium combination was 19
mg/kg dw. Survival of fry from the exposed adults was affected by 5 days post-
hatch. Concentrations of whole-body selenium in adult tissue at day 60 were used
to determine effects in the fry because eggs were taken for the larval tests
beginning at day 60 of the adult exposure.
Table 1. Effects on Adults
Se in diet,
mg/kg dw
Se in water,
l-ig/L
whole-body
Se (140 d),
mg/kg dw
replicate
total no.
spawns
eggs/spawn
hatchability,
%
0.8
0.5
0.8
A
15
14,099
94.5
B
10
5,961
90.5
0.8
7.9
1.0
A
12
9,267
89.5
B
11
9,255
84.5
4.6
10.5
3.4
A
20
9,782
86.5
B
12
13,032
96.5
8.4
10.5
6.0
A
2
10,614
96.5
B
9
7,995
90
16.8
10.1
10
A
13
10,797
83
B
13
9,147
91.5
33.3
10.1
19
A
14
8,850
80
B
4
8,850
80
In the 30-d survival after hatch test, there was complete mortality after one week
at the highest exposure and no significant differences in survival at lower
concentrations. Table 2 provides the survival data at 5 days post hatch used in the
analysis of the effect concentration. The day 5 data are given in Table 2 because
this was the only day in which control survival was over 90%, with the control
and all the treatments showing substantial and increasing toxicity over the next 4
days.
Because the survival in the fifth treatment was about 5% below the average of the
lowest four and because the highest treatment still had some survivors, this
C-129
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provided two partial effects for TRAP to fit a curve. However, the legitimacy of
this depends on the lower survival in the fifth treatment actually being a
significant Se effect, rather than reflecting random variation of background
survival. Because there were multiple spawns with 200-500 total larvae tested for
each survival value above, this might be expected to be a real effect, but there is
insufficient data reported to test this. However, from day 6 through day 30,
survival at the fifth treatment was above that in the first and third treatments,
indicating this is not an effect level. These later data establish that the highest
treatment is best considered an ECioo and the fifth treatment an EC0. So an
interpolation was done using 42 mg/kg as an ECioo, resulting in a slope of 7.6 and
an ECio of 26.3 mg/kg. The interpolation between the EC0 and ECioo resulted in a
slightly higher ECio in the previous draft document (24.15 mg/kg) which used a
TRAP model to estimate the ECi0. A figure is not provided here because this
interpolation represents a synthesis of the data not tied to the data for a specific
day.
As for the analysis with egg concentrations, the whole-body analysis recognizes
the highest treatment as an ECioo (16 mg Se/kg dry wt whole body) and the
second highest treatment as an EC0 (7.2 mg Se/kg dry wt whole body). The
interpolation method then results in an ECio of 8.6 mg/kg. As for the egg
concentration analysis, no plot is given because the EC0 is not for a specific day
or survival value.
Table 2. Survival of Larvae at Day 5 in the 30-day Post-hatch Test
Se in diet, mg/kg
dw
Se in water, (ig/L
egg, mg/kg dw
adult whole-body
(60 d), mg/kg dw
mean survival,
%
0.8
0.5
1.8
0.9
92
0.8
7.9
1.8
0.9
93
4.6
10.5
7.3
2.9
90
8.4
10.5
13
4.9
95
16.8
10.1
23
7.2
87
33.3
10.1
42
16
7
Chronic Value:
effect level
egg, mg Se/kg dw
whole body, mg Se/kg dw
ECio
26.3
8.6
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Cleveland, L. et al. 1993. Toxicity and bioaccumulation of waterborne and dietary selenium in juvenile
bluegill sunfish (Lepomis macrochirus). Aquatic Toxicol. 27:265-280.
Test Organism:
Life Stage:
Exposure Route:
Bluegill sunfish (Lepomis macrochirus)
juvenile (5 months - waterborne exposure; 3 months - dietary exposure)
waterborne (60-d) and dietary (90-d) - separate exposures
waterborne - 6:1 selenate:selenite at 0.17, 0.34, 0.68, 1.38, 2.73 mg/L; dietary
seleno-L-methionine in Oregon moist at 1.63, 3.25, 6.5, 13, 26 mg Se/kg dw)
Study Design: Fish were exposed using a flow-through diluter. Each test consisted of an
exposure and a depuration phase. Whole body tissue measurements were made at
31 and 60 days of waterborne exposure and at 31, 59 and 90 days of dietary
exposure. Mortality and condition factor, K (weight x 105/length3), were reported
at selected intervals.
Effects Data: The waterborne exposure (see table below) was determined to have an EC2o =
4.07 mg Se/kg dw (1.96-8.44 mg/kg 95% CL). However, because it was a water-
only exposure, it was not considered in the derivation of the FCV. These data
nevertheless provide evidence that exposure route influences the tissue
concentration toxicity threshold, although the mechanistic explanation for this
phenomenon is lacking.
A mortality effect level for the dietary exposure could not be calculated because
the highest selenium whole body concentration (13.4 mg Se/kg dw) only had
17.5% mortality. The middle selenium concentration did have 22.5% mortality.
Cleveland et al. reported a significant decrease in K between 4.7 and 7.7 mg/kg
dw (see table below).
Waterborne Exposure Study
Measured selenium in
water (:g/L)
60-d measured
selenium in whole
body (mg/kg dw)
60-d mortality (%)
Condition factor (K)
20 (control)
1.1
10
1.5
160
2.8
12.5
1.5
330
4
22.5
1.6
640
5.3
52.5
1.5
1120
9.8
70
1.6
2800
14.7*
97.5
NA
*a 30-d measurement because all fish were dead at 60 days in this concentration.
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Dietary Exposure Study
Measured selenium in
food (mg/kg ww)
90-d measured
selenium in whole
body (mg/kg dw)
90-d mortality (%)
Condition factor (K)
0.68 (control)
1
5
1.3
2.3
2.1
7.5
1.3
3.5
3.3
10
1.3
6.6
4.7
22.5
1.3
12.7
7.7
15
1.2
25
13.4
17.5
1.2
Discussion The study demonstrates the influence of exposure route on the potency of a given
tissue concentration, as shown in the figure. The TRAP threshold sigmoid
concentration-response curve for the water-only exposure yields an EC50 of 6.5
mg Se/kg dw WB. In contrast, higher whole-body concentrations acquired via
diet did not yield significant effects and cannot support a TRAP-fitted
concentration-response curve or EC estimate. Examination of the graph indicates
that the water-only concentration-response curve would need to be shifted to the
right a minimum of 4-fold (or possibly more) to be able to fit the (lack of) effects
observed in the dietary study. This supports the decision to derive the criteria
only from studies relying on the environmentally relevant exposure route, diet.
100
90
80
70
* 60
.1 50
>
3
40
to
30
~ Via water exposure, 60-d
¦ Via dietary exposure, 90-d
Model for water exposure
20
1
2
4
8
16
32
Whole Body Concentration, mg Se/kg dw
Survival at 60-days (for water exposure) or 90-days (for dietary exposure) versus
whole-body concentration.
C-132
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Chronic Value: Given (a) the very slight reduction in K (1.3 to 1.2 between 4.7 and 7.7 mg Se/kg
dw WB, with no further reduction at 13.4 mg Se/kg dw WB) and uncertain
relevance of growth data, and (b) no apparent concentration-related effect on
mortality between 4.7 and 13.4 mg Se/kg dw WB, the NOAEC is interpreted to
be 13.4 mg Se/kg dw for this study; and the chronic value is >13.4 mg Se/kg dw
whole body.
C-133
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Lemly, A.D. 1993a. Metabolic stress during winter increases the toxicity of selenium to fish. Aquatic
Toxicol. 27:133-158.
Test Organism:
Exposure Route:
Test Duration:
Study Design:
Effects Data
Chronic Value:
Comments:
Bluegill sunfish (Lepomis macrochirus; juvenile 50-70 mm)
Waterborne and dietary
Water
1:1 selenite:selenate in stock at pH 2; metered in to reach 5 :g/L
Diet
seleno-L-methionine in TetraMin (5 mg/kg dw)
180 days
Fish were exposed (treatment and control) under intermittent flow-through
conditions for 180 days. Tests were run at 4° and 20°C with biological
(histological, hematological, metabolic and survival) and selenium measurements
made at 0, 60, 120 and 180 days. Fish were fed at a rate of 3% body weight per
day. All treatments were initiated at 20°C and then decreased in the cold
treatment at a rate of 2°C per week for 8 weeks to reach 4°C and then maintained
at that temperature for the remainder of the 180 days.
In the 20°C test, fish accumulated 6 mg/kg dw selenium (whole-body) with no
significant effect on survival (4.3% and 7.4% mortality in control and treatment,
respectively). In the 4°C test, fish exposed to selenium accumulated 7.9 mg/kg
dw (whole-body) selenium and had significant mortality after 120 (33.6%) and
180 days (40.4%) relative to control (3.9%). Several hematological
measurements were significantly different in both the warm and cold selenium
exposures relative to controls. Both warm and cold selenium treatments also had
greater 02 consumption than controls. Fish lipid content in the cold Se treatment
decreased more than the cold control; lipid content did not decrease in either the
warm control or the warm Se treatment (see summary tables below). The results
suggest significant mortality occurs in juvenile bluegill during winter months
when tissue concentrations reach 7.91 mg/kg dw and lipid levels decrease to 6
percent.
20°C, >6 mg Se/kg whole-body; 4°C, <7.91 mg Se/kg dw whole body
See "Comparison of the Cold-Temperature Bluegill Juvenile-Survival Studies" in
this appendix after presentation of the Mclntyre et al. (2008) study.
C-134
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Mean Concentration of Selenium in Tissues, Cumulative Survival*, Percent Lipid Content and Oxygen Consumption in Juvenile
Bluegill
day
cold - Se control
cold + Se
warm - Se control
warm + Se
Sea
Surv.
%
lipid,
%
o2b
Sea
Surv.
%
lipid,
%
o2b
Sea
Surv.
%
lipid,
%
o2b
Sea
Surv.
%
lipid,
%
o2b
0
1
100
13.2
98
1
100
13.2
98
1
100
13.2
98
1
100
13.2
98
60
1
97.1
12.5
58
5.8
92.9
10
63
1.2
95.7
13.3
98
5.8
100
13.3
103
120
1.1
97.1
11.5
57
7.9
66.4
6
81
1.1
95.7
13.4
100
6
96.7
13.4
120
180
1.4
97.1
10.5
57
7.9
59.6
6
78
1.2
95.7
13.6
100
6
92.6
13.5
120
a whole body Se tissue concentration, mg/kg dw
b oxygen consumption, mg/kg/hr
* Cumulative Survival: In this experiment, 240 juvenile bluegill were placed in three 400-L fiberglass tanks, 80 in each, and exposed to
each control and treatment for a period of 180 days. Ten fish were removed at random from each treatment replicate on days 0, 60, 120,
and 180 for selenium, histological, hematological, and metabolic measurements.
Replicate and Average Whole-body concentrations (mg/kg dry weight) of selenium in juvenile bluegill*
day 0
day 60
day 120
day 180
replicat
e
1
2
3
mean
1
2
3
mean
1
2
3
mean
1
2
3
mean
c+Se
0.87
1.21
0.95
1.01
6.30
5.49
5.76
5.85
8.36
7.31
7.85
7.84
7.53
8.01
8.19
7.91
w+Se
1.17
0.96
0.90
1.01
5.61
6.19
5.43
5.74
6.37
5.92
5.50
5.93
5.48
5.72
6.02
5.74
c-Se
0.89
0.89
0.97
0.97
1.01
1.01
1.10
1.10
w-Se
0.99
0.99
1.12
1.12
0.99
0.99
0.96
0.96
* Each value is for a composite sample made from 5 fish.
C-135
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The Kaplan-Meier estimator was used to calculate survival at time t
5(0
where r(t,) is the number of fish alive just before time i.e. the number at risk, and d, is the number of
deaths in the interval /, = 11,. I, 11. The 95% confidence interval for such estimate (Venables and Ripley
2002) was computed as
expi - H (t) exp
± k,
s-e-(^(0)
H(t)
where
r(t,)
and j # i
C-136
-------
The following table lists the estimates of survival in the cold + Se treatment at 60, 120 and 180 days. The term n.event is the number of
deaths at a given interval; n.risk is the number of organisms alive at the beginning of the interval; survival is computed by the Kaplan-
Meier estimator.
Time
n.risk
n. event
survival
std.err
lower 95% CI
upper 95% CI
60
210
15
0.929
0.0178
0.884
0.956
120
165
47
0.664
0.0350
0.590
0.728
180
88
9
0.596
0.0381
0.517
0.666
Hematological Measurements in Juvenile Bluegill Sunfish (indicates significantly different from control)
Warm Exposure
day 0
day 60
day 120
day 180
blood parameter
warm-Se
warm+Se
warm-Se
warm+Se
warm-Se
warm+Se
warm-Se
warm+Se
total erythrocyte, 106/ml
2.95
2.92
2.96
2.93
2.99
2.95
2.96
2.89
% mature
85
86
86
93*
86
94*
85
94*
nuclear shadows, 104/ml
0.95
0.86
0.97
2.05*
0.83
2.38*
0.91
2.30*
total leucocytes, 104/ml
17.22
17.41
16.90
17.55
16.73
17.62
17.05
17.36
% lymphocytes
23
25
20
23
19
26
21
22
% neutrophils
15
13
14
15
17
19
17
16
hematocrit, %
37
36
37
29*
36
29*
38
28*
MCHC (mean corpuscular hemoglobin
conc.)
23
25
25
19*
25
18*
25
17*
Cold Exposure
day 0
day 60
day 120
day 180
blood parameter
cold-Se
cold+Se
cold-Se
cold+Se
cold-Se
cold+Se
cold-Se
cold+Se
total erythrocyte, 106/ml
2.91
2.93
2.97
2.90
3.01
2.95
3.00
2.99
C-137
-------
% mature
84
82
87
95*
85
96*
85
97*
nuclear shadows, 104/ml
0.86
0.84
0.83
2.30*
0.89
2.49*
0.90
2.36
total leucocytes, 104/ml
16.48
16.88
16.79
16.91
16.80
16.74
16.96
16.63
% lymphocytes
17
16
16
17
19
15
19
18
% neutrophils
13
12
15
11
15
12
12
14
hematocrit, %
39
37
40
30*
41
28*
39
27*
MCHC (mean corpuscular hemoglobin
conc.)
26
25
25
18*
22
17*
23
17*
MCV (mean corpuscular volume)
182
171
188
146*
180
135*
185
130*
C-138
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Mclntyre et al. 2008. Effect of Selenium on Juvenile Bluegill Sunfish at Reduced Temperatures. US
EPA, Health and Ecological Criteria Division. EPA-822-R-08-020
Test Organism: Bluegill sunfish (Lepomis macrochirus); juvenile; average length 47 mm,
average weight 1 g
Exposure Route: Waterborne and dietary
Water
1:1 selenite:selenate; For exposure systems (ES) 1 and 3, fish were exposed to a
control and a series of 6 nominal concentrations, 1.25, 2.5, 5, 10, 20 and 40 |_ig
Se/L. For ES2, fish were exposed to a control and one nominal concentration, 5
!_ig Se/L.
Diet
For ESI and ES3, fish were fed a series of six concentrations of selenium and a
background control in Lumbriculus variegatus. The measured selenium
concentrations in the L. variegatus treatments in ESI were: 2.3 (control), 4.5, 5.3,
7.5, 14.2, 25.7 and 34.9 mg Se/kg dw; in ES3: 2.2 (control), 4.2, 5.0, 7.2, 15.2,
25.4 and 46.7 mg Se/kg dw. Fish were fed worms at a rate of 4% of the current
biomass in each fish tank. Selenium was accumulated in L. variegatus by feeding
the worms in separate tanks a series of six concentrations of selenized-yeast
diluted with nutritional yeast: 1.7, 3.3, 6.7, 13.3, 26.7 and 53.5 mg Se/kg dw.
Control worms were fed nutritional yeast only. Each tank was additionally
exposed to the associated aqueous concentration selenium, e.g., the worms fed
the 1.7 mg Se/kg dw selenized yeast were exposed to 1.25 :g Se/L, the worms fed
the 3.3 mg Se/kg dw selenized yeast were exposed to 2.5 :g Se/L, and so on.
For ES2, fish were fed TetraMin spiked with seleno-L-methionine at a nominal
concentration of 5 mg/kg dw and at a rate of 3% of the current biomass in each
tank.
Test Duration: 182 days
Study Design: Juvenile bluegill were exposed concurrently to selenium using three separate
exposure systems, ESI, ES2 and ES3. In ESI and ES3, 100 fish were exposed to
each of 6 selenium treatments (low through high treatments are referred to as
Treatments 1 through 6) and two controls in 200 L carboys under flow-through
conditions. Each treatment consisted of an aqueous selenium concentration and
an associated dietary selenium concentration, e.g., the fish in the lowest ESI
treatment were exposed to 1.25 :g Se/L and fed worms containing 4.5 mg Se/kg
dw (see Exposure Route for other treatment concentrations). Temperature was
controlled in each system through the immersion of the carboys in a temperature-
controlled water bath and by controlling the temperature of the dilution water
being added to the carboys. The temperature in ESI was maintained at 20°C for
the first 30 days of exposure, and then decreased 2°C/week until it reached 4°C
(test day 79) at which point temperature was maintained until test termination
(test day 182). The only difference between ESI and ES3 was temperature was
decreased 2°C/week until it reached 9°C (test day 65) at which point temperature
was maintained until test termination (test day 182).
The exposure of ES2 was similar to ESI and ES3 in that 100 juvenile bluegill
were exposed to treatment in 200 L carboys under flow-through conditions. The
C-139
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ES2 selenium treatment consisted of two replicates of 5 |_ig Se/L waterborne and
5 mg Se/kg dw diet (Tetramin). Two controls were maintained with ES2. The
temperature regime for ES2 was identical to ES1.
Observations on fish behavior and mortality were checked daily. Total selenium
was measured in each fish tank weekly and selenium speciation was measured
monthly in each fish tank. Whole body total selenium was measured in the
worms from each tank (2 replicate 5 g samples) on test days 0, 30, 60, 112 and
182 and in the bluegill from each tank (3 replicates of 3-fish composites - total 9
fish) on test days 0, 7, 30, 60, 112 and 182. The standard length and weight of
each fish was measured on each sample day. Lipid content was measured in fish
at day 0 and from each treatment at test termination.
Effects Data: Selenium increased in bluegill as the exposure concentrations increased (see
following table). No meaningful mortality was observed in ES2. The number of
fish that died in ES2 during the 182 day test was two fish in one treatment
replicate and none in the other treatment replicate; no deaths were reported in
ES2 controls. Significant mortality of juvenile bluegill was observed in ESI and
ES3. After 182 days, a total of 24 and 68 fish died in Treatments 5 and 6,
respectively in ESI; and a total of 38 and 61 fish died in Treatments 5 and 6,
respectively in ES3. See table below for mortalities in all treatments. Estimates of
bluegill survival were adjusted for the removal of individuals from the test
population. Individuals were removed from the experiments before test
completion, for sampling tissue concentrations or because they suffered
accidental deaths unrelated to selenium toxicity. For such data, it was necessary
to account for the reduction in number of individuals at risk of death due to
selenium over time. If r(t,) is the number of individuals at risk just before time t,
and d, is the number of deaths in the interval, /, = 11,. I, ,). then survival (5) at time
t can be estimated as
The product (P) was calculated for each period in which one or more deaths
occur. The equation is the Kaplan-Meier estimator (Venables and Ripley 2002).
This correction was applied to calculate the proportion of survival in treatments
with ten or more deaths (10% mortality). The table below provides the adjusted
proportion and surviving bluegill in each treatment along with the concentration
of selenium in bluegill at test termination. The values in this table were used to
calculate the EC2o and ECi0 values using the TEAM software. Growth and lipid
content of the bluegill was not negatively affected by the selenium exposures.
C-140
-------
Measured total selenium concentrations in bluegill sunfish for all treatments and controls in Exposure System 1, 2 and 3.
Total Selenium in Whole Body Bluegill Tissue, mg/kg dw
Control
Treatment 1
Treatment 2
Treatment 3
Treatment 4
Treatment 5
Treatment 6
ESI
Average
Test Day
Average (SD)
Average (SD)
Average (SD)
Average (SD)
Average (SD)
Average (SD)
(SD)
0
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
7
2.43 (0.31)
2.48 (0.11)
2.43 (0.18)
2.64 (0.06)
2.72 (0.07)
3.27 (0.27)
4.27 (0.44)
30
2.10(0.21)
2.85 (0.10)
3.10(0.04)
2.94 (0.13)
4.24 (0.22)
6.62 (0.23)
10.21 (0.36)
60
2.11 (0.02)
2.70 (0.20)
3.07 (0.05)
3.69 (0.25)
5.21 (0.30)
8.62 (0.45)
12.66 (0.45)
112
1.98 (0.04)
3.16(0.11)
3.41 (0.08)
3.99 (0.26)
6.42 (0.05)
11.60 (0.43)
182
2.08 (0.10)
2.56(0.21)
3.15 (0.25)
4.02 (0.21)
6.72 (0.09)
10.71 (0.55)
Control
Treatment 1
Treatment 2
Treatment 3
Treatment 4
Treatment 5
Treatment 6
ES3
Average
Test Day
Average (SD)
Average (SD)
Average (SD)
Average (SD)
Average (SD)
Average (SD)
(SD)
0
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
7
2.50(0.10)
2.60 (0.29)
2.38 (0.10)
2.82 (0.20)
3.19(0.33)
4.29 (0.20)
6.13 (0.62)
30
2.24 (0.41)
2.44 (0.26)
2.70 (0.16)
3.13 (0.10)
3.95 (0.16)
6.06 (0.36)
11.07 (0.92)
60
2.70 (0.22)
2.88 (0.08)
3.04 (0.39)
3.79 (0.24)
5.54 (0.21)
9.50(0.91)
15.14 (0.96)
112
2.16(0.14)
2.49 (0.10)
3.10(0.12)
3.64 (0.16)
6.54 (0.21)
11.50 (0.25)
17.24 (0.30)
182
1.67 (0.21)
3.20 (0.27)
3.83 (0.47)
5.48 (0.24)
9.38 (0.63)
16.01 (0.30)
ES2
Control
5A
5B
Test Day
Average (SD)
Average (SD)
Average (SD)
0
1.93 (0.21)
1.93 (0.21)
1.93 (0.21)
7
2.19(0.19)
3.55 (0.25)
3.08 (0.50)
30
2.49 (0.15)
7.05 (0.76)
7.51 (1.18)
60
1.53 (0.03)
8.23 (1.55)
8.09 (0.67)
112
1.57(0.01)
8.97 (1.28)
9.45 (1.73)
182
1.38 (0.06)
9.41 (1.63)
10.61 (0.38)
C-141
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Total number of deaths in ESI and ES3 Treatments throughout the experiment's duration (182
days). Both ESI and ES3 had two control tanks.
Treatment
ESI
ES3
Control (#1, #2)
0,7
1, 1
1
5
0
2
1
1
3
0
0
4
3
3
5
24
38
6
68
61
The concentration of selenium in bluegill and the adjusted proportion of surviving fish at the end of
the 182 day exposure.
ESI ES3
Treatment
[Se]tlssUe, mg/kg dw
surv
[Se]tlssUe, mg/kg dw
surv
control
2.08
0.962
1.67
0.988
1
2.56
0.988
3.20
1.000
2
3.15
0.984
3.83
0.988
3
4.02
1.000
5.48
1.000
4
6.72
0.962
9.38
0.960
5
10.71
0.497
16.01
0.435
6
12.66
0.075
17.24
0.168
Chronic Value: The NOAEC for bluegill in ES2 was calculated as the geometric mean of the
concentration of bluegill in the two replicates at the end of the exposure period,
9.992 mg Se/kg dw whole body. The chronic value for ES2 is therefore >9.992
mg Se/kg dw whole body. The EC2o and ECi0 values for ESI and ES3 are given
in the following table.
ESI (4°C)
ES3 (9°C)
Whole body
Whole body
EC2o mg Se/kg dw
9.78
14.64
ECio mg Se/kg dw
9.27
14.00
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Comparison of the Cold-Temperature Bluegill Juvenile-Survival Studies of Lemly (1993a) and
Mclntyre et al. (2008)
The Lemly (1993a) and Mclntyre et al. (2008) cold-temperature juvenile bluegill studies are summarized
on the previous pages. This discussion compares and contrasts these studies.
Both studies indicated that juvenile bluegill are more sensitive to selenium at lower temperature than at
higher temperature. For a 4°C temperature regime, the ECi0 of 9.27 mg Se/kg dw WB obtained with
Mclntyre's selenized yeast-worm-fish dietary bioaccumulation system is somewhat similar to the
threshold of 5.85 mg Se/kg dw WB estimated from the time course of bioaccumulation and mortality in
Lemly's single treatment with seleno-L-methionine in TetraMin. These chronic values differ by a factor
of 1.58.
The difference in diet does not appear to explain the modest difference in results; however, since
Mclntyre's other 4°C experiment (Exposure System ES2), which used Lemly's seleno-L-methionine in
TetraMin diet, experienced no significant toxicity, whereas Lemly's similarly exposed fish experienced
40 percent mortality by the end of the test. In addition to the difference in observed mortalities, Lemly's
bluegill in the 4°C selenium exposure decreased in both lipid content and body condition over the 180
days whereas no decreases in these measurements were observed in the Mclntyre et al. study, although
the fish used in both studies were of comparable size and body condition at test initiation: 47 mm average
standard length (range 44 to 54 mm) and a body condition index (100 x fish weight/standard length) of
3.2 in ES2 compared to 50 to 70 mm total length and a body condition factor of 3.9 in Lemly.
There are several possible reasons why such results could differ between studies. (1) ES2 maintained
exposure at 20°C for the first 30 days of exposure before decreasing the temperature compared to 7 days
in the Lemly study. (2) Lemly measured 02 consumption by removing and reintroducing test fish to the
test tanks, which was not done by Mclntyre et al. (3) The two studies differed in photoperiod - Lemly
"began with a 16:10 h light/dark photoperiod which was gradually reversed to 10:16" (sic) whereas
Mclntyre et al. used a fixed photoperiod of 16:8. (4) Some genetic differences between the tested batches
of organisms may be expected, reflecting different origins, despite the similarities in their starting size
and condition.
The modification to maintain 20°C for 30 days was to allow a longer period of time for the fish to
accumulate selenium during a warmer condition prior to decreasing the temperature. This did result in
shortening the exposure in ES2 at 4°C by 19 days (103 days at 4°C) compared to 122 days at 4°C in
Lemly's study. However, as the majority of deaths in Lemly's study occurred between in the middle 60
days of the 180-day test, the slightly shorter cold period in the Mclntyre study would not explain the
differences in mortalities.
As stated above, Lemly removed fish (N = 15) from each treatment for oxygen consumption
measurement and then returned these fish to the exposure tanks. There is the possibility that the fish
removed from the cold plus selenium treatment were sufficiently stressed by the exposure conditions that
the additional handling stress contributed to the mortality observed in this treatment. Between test days 60
and 180, 56 fish died Lemly's cold plus selenium treatment. Even if stress due to handling affected all the
fish used in the oxygen consumption measurements (up to 30 fish), it does not explain all the mortality
that was observed and therefore does not explain the difference between the two studies.
Both Lemly (1993) and Mclntyre et al. (2008) showed reduced survival of juvenile bluegill exposed to
elevated selenium under lab-simulated winter conditions, albeit at somewhat different concentrations. But
only Lemly, not Mclntyre et al., found the decreased survival to be accompanied by loss of lipid and body
C-143
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condition. It was hypothesized that the decrease in ECio observed by Lemly (1993) in the cold water
treatment between 60-180 days was attributed to "winter stress syndrome" (WSS). WSS is hypothesized
to occur in warmwater fish species because the presence of a stressor places additional metabolic costs on
exposed organisms. These stresses can be better tolerated during periods of warm weather and active
feeding. However, during the winter months, feeding and activity levels decrease but the metabolic costs
of the stressor remain. As a result, fishes deplete their lipid stores, resulting in lower condition factors and
increased susceptibility to mortality (Lemly 1996). Lemly noted three conditions that must be met
simultaneously in order for WSS to occur: 1) a significant metabolic stressor must be present, 2) cold
water temperatures must be present, and 3) fish must respond by reducing activity and feeding (Lemly
1996).
Several other studies have reported decreased feeding and activity levels for several fish species.
McCollum et al. (2003) observed decreased overwinter feeding, and subsequent weight loss, of white
crappie. Parrish et al. (2004) observed overwinter weight loss among mature, but not juvenile, salmon in a
laboratory study in experimental raceways. Current speed, and by extension prey delivery rate, was the
most important factor regulating overwinter feeding and growth. Eckmann (2004) observed overwinter
reductions in feeding, weight, and lipid levels in yellow perch, but not in ruffe. Sogard and Olla (2000)
observed walleye pollock could mitigate the effects of overwinter lipid depletion by moving to colder
waters, where reduced metabolism allowed them to conserve energy. In all of these studies, fish continued
to feed during the winter, but feeding rates decreased. The increase in weight among ruffe was attributed
to its ability to feed on benthos in the dark during the winter months, suggesting that feeding reduction
during winter may be more pronounced for species dependent on vision to feed. This was supported by
Bennett and Janz (2007a), who observed that burbot, which rely primarily on smell while feeding on
benthic invertebrates, experienced significant overwinter increases in weight and lipids in all sites, while
northern pike, which rely primarily on vision while feeding on zooplankton, experienced slight but non-
significant increases in weight and length.
WSS has not been definitively confirmed or refuted, although it has been investigated in the field. Bennett
and Janz (2007a) observed no evidence of WSS for juvenile northern pike or burbot. Lengths, weights,
and lipids increased for both species, particularly the olfactory feeding burbots, in the spring compared to
the previous fall. Overall weights and lipids were higher in the low and high exposure lakes than the
reference lake, possibly because of nitrogen limitation in the reference lake coupled with relatively low
stressor concentrations in the exposed lakes. In a separate study, overwinter weights and lipids remained
similar or increased in northern pike and burbot at both reference and exposure sites, while overwinter
weights and lipids decreased at the exposure site for slimy sculpin (Bennett and Janz 2007b). However,
this study neither supports nor refutes the WSS hypothesis, because stressor concentrations at the
exposure site were not significantly different than at the reference sites, and the weight decrease in
sculpin was attributed to higher turbidity at the exposure site, which inhibited food acquisition. In a final
field test of WSS fathead minnow, creek chub, and white suckers were collected from reference and
exposure sites (Driedger et al. 2009). Stressor levels at exposure sites were high, as whole body Se
concentrations in fathead minnow ranged from 11-42 mg/kg dw. All three species either gained or
maintained weight overwinter at all sites, indicating that active feeding occurred overwinter. Overall
weights at exposure sites were higher, likely because of nutrient limitation at the reference sites, which
confounded the ability to fully test the WSS hypothesis.
These results suggest that fish species responses to cold temperatures vary by species and environment.
Many species lose weight, but this can be partially explained by the impact of low light levels on
consumption levels, especially in northern latitudes where overwinter light limitation is pronounced. Field
tests found no evidence of WSS, but were confounded by low stressor levels, nutrient limitation at
reference sites, or both.
C-144
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It may then be questioned whether the fixed photoperiod alone could account for the differences in the
results of the two studies. More explicitly, did the longer light period in Mclntyre et al. photoperiod allow
the fish to feed more than the fish exposed to the shorter light period in the Lemly study, such that lipid
and body condition in the Mclntyre et al. fish were maintained and therefore not susceptible to "winter
stress syndrome." The effects of photoperiod on fish and other ectotherms are well-documented.
Temperature-independent seasonal changes in fish have been reported for growth and food conversion
efficiency (Biswas and Takeuchi 2003; Jonassen et al. 2000; Simensen et al. 2000), feeding behavior
(Volkoff and Peter 2006), metabolic rate (Evans 1984), and reproduction (Koger et al. 1999; Scott 1979).
Some of these studies have found conflicting results on the effect of photoperiod on growth (Fuchs 1978;
Jonassen et al. 2000; Simensen et al. 2000). Coupled with temperature being a dominant factor in
controlling physiological functions in temperate-zone fish as indicated by a 3 to 4-fold fluctuation in
metabolic activities over 10°C (Brett 1970; Fry 1971), it is difficult to use literature findings to explain
the difference in the two bluegill studies. In field studies of fish at northern latitudes (Eckmann 2004),
reduced light resulted in weight loss not though a bioenergetics interaction with cold temperatures, but by
inhibiting feeding ability of visual, but not non-visual predators. If this mechanism applies to bluegill,
then photoperiod is less likely to play a major role in the difference in results, as the overwinter light:dark
cycle (8:16) should have been sufficiently long for the bluegill in Lemly (1993) to feed.
Observational recordings of the feeding behavior in Mclntyre et al. noted that in both control replicates
and in both treatment replicates the feeding of the juvenile bluegill went from active to not active on test
day 78 when temperatures were decreased from 6.6 to 5.8°C. The feeding observations are reflected in a
gradual slight decrease in the body condition factor (K) after test day 60 in the figure below. Although
food intake was not quantified during the study, the lack of growth indicated in K suggests feeding
markedly decreased as the temperature declined, as shown in the figure. Body condition decreased much
more in the Lemly's cold plus selenium exposed fish after test day 60 (approximately 50%) but K in his
cold-without-selenium exposure decreased only slightly, similar to Mclntyre et al. Therefore it is not
possible to determine if the greater decrease in K and in lipid content in Lemly's cold plus selenium
treatment was due to decreased feeding because of a shorter photoperiod or because the bluegill fish
population used in his study were more sensitive to selenium in cold conditions. Mclntyre et al. obtained
bluegill from Osage Catfisheries in Missouri whereas Lemly collected fish from ponds (assumed to be
near Blacksburg, Virginia, not stated in paper). The fish obtained from Missouri, a location with colder
winters than Virginia, may have been better adapted for withstanding colder winter temperatures than
Lemly's fish and therefore were less sensitive to "winter stress syndrome" as induced by selenium
exposure. Similarly, different populations of a species can have varying sensitivities to stressors.
Furthermore, the relative difference in the Lemly and Mclntyre et al. results is slightly less than Delos
(2001) found to be typical when equivalent toxicity tests of the same species are compared. There should
thus be no expectation that the two study results should agree more closely than they do.
C-145
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6
22
—i—
50
100
0 Condition Factor (K)
Temperature (°C)
150
h 20
18
M6 o
o
- 14 V
h 12 "I
-------
Carolina Power & Light. 1997. Largemouth Bass Selenium Bioassay- Report. Carolina Power & Light
Company, Environmental Services Section, 3932 New Hill, North Carolina. December 1997
Test Organism: Largemouth bass (Micropterus salmoides)
Exposure Route: Laboratory; dietary exposure only; DL-selenomethionine added to an artificial
diet. Adult largemouth bass obtained from a commercial supplier were fed
several months prior to spawning a series of selenium concentrations in the
artificial diet.
Test duration: Embryo-larval monitoring through swim-up stage.
Study Design: Dietary exposure studies were conducted in 1995 and in 1996. In 1995, the
measured dietary Se concentrations were 0.9 (control), 2.9, 7.5 and 11.2 mg
Se/kg dw: in 1996, they were 26.7, 53.1 and 78.4 mg Se/kg dw. Parent fish were
fed to satiation twice per day. Approximately 100 eggs from each spawn were
transferred to each of 2 to 4 incubation cups. Eggs and larvae were monitored for
mortality and deformities up to the larval swim-up stage. Selenium was measured
in the liver, muscle and gonad tissues of the parent fish. All live deformed larvae
at swim-up stage were considered as mortalities in the analyses.
Effects Data: Over the two year period, 56 successful spawns were obtained across all dietary
treatments. Live larval fish with deformities (kyphosis, scoliosis, jaw gap, and
lordosis) and edema at swim-up stage were considered mortalities for data
analysis. The average concentration of selenium in ovaries ranged from 3.1
mg/kg dw in the control to 77.6 mg/kg dw in the high dietary treatment (Table 1).
Larval survival generally decreased as the selenium concentration in the ovary
increased (Table 1; Figure 1). A plot of the percent survival of larval largemouth
bass as a function of the selenium concentration in the parental female ovary
shows two groups of data; one at background survival with considerable
variability (mean 90.3%, standard deviation 10.9%) and one with <10% survival,
with most of the data being at 0% survival. Due to inadequate partial effects, a
TRAP interpolation was used to estimate an ECi0 value. Based on a risk
management decision that the LOEC cannot be any higher than the lowest
concentration with 0% survival (32.9 mg/kg) and that any ECx should be below
this, this establishes the higher concentration point for the interpolation (an ECioo
of 32.9 mg/kg) and requires that the highest 4 NOECs not be considered in
setting the EC0. The lower concentration point for the interpolation is therefore
set here to 24.6, the next highest NOEC with greater than the average 90.3%
background survival. This results in an ECio of 26.3 mg/kg (and a steep slope of
16).
An ECio for the muscle tissue in Table 1 was not determined due to uncertainty
in the values. The authors of this report also measured selenium in the ovaries
and muscle tissues of largemouth bass collected from Mayo Reservoir (Table 2).
There was a considerable difference in the proportion of selenium in the ovaries
to the muscle tissues between the largemouth bass collected from the bioassay
study and the field collected largemouth bass. The ratio of Se in ovaries to
muscle in the laboratory fish was approximately 3.3 whereas it was 1.1 in the
field collected fish. With the exception of mountain whitefish, the ovary to
muscle ratio observed in the laboratory fish is also considerably higher than other
C-147
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species (see Appendix B Table B-3). Based on this uncertainty in the muscle
concentrations in the laboratory fish, an ECi0 for this tissue was not calculated.
The effect concentration based on the ovary selenium concentrations are not
considered uncertain because these concentrations represent the direct exposure
of selenium to the larvae from which the effect was observed.
Effect
Concentration: 26.3 mg/kg dw in ovaries
Table 1. Selenium concentrations in the diet, ovary and muscle tissues and the percent mortality
and deformities.
Measured Se in
Spawn
diet fed to
No.
Se in parent tissues, mg/kg dw
Larval surviva
0/
, /o
parents,
mg/kg dwa
Muscle
Ovary
Average
Individual
Average
6
1.62
5.38
75.5
12
1.77
7.34
99.7
13
2.01
3.51
96.2
26
2.27
5.74
88.9
0.9 ±0.1
34
1.18
1.58
99.5
(0.7- 1.3)
35
1.28
1.36
3.1
96.8
95.3
3
1.534
2.09
98.8
4
1.583
1.85
100
10 (2F)
1.15
2.11
97
13
1.181
1.86
97.1
14
1.341
1.40
98.4
9
2.075
9.59
84.9
2.9 ±0.5
12
1.853
8.03
OO
00
100
94.8
(2.1-3.8)
15
2.026
9.73
98.5
18
3.134
7.66
95.9
1
2.741
8.43
75
2
3.737
25.15
63.9
5
5.709
15.31
90.6
7.5 ±0.6
7
3.468
1.20
10.8
79.1
85.8
(6.3 - 8.4)
8
2.545
6.78
95
16
7.302
8.25
96.8
19
4.776
10.20
100
6
4.521
35.44
91.5
11.2 ± 1.4
11
6.044
15.08
25.0
77.9
88.7
(9.3 - 14.1)
17
4.882
24.59
96.7
2
7.52
37.14
91.2
5
12.42
44.67
0
11
9.73
34.26
75.9
16
10.1
35.58
0
17
5.74
33.48
9.9
26.7 ± 1.7
19
11.74
48.24
40.0
0
18.3
(23.6-29.5)
36
10.21
35.81
6.3
37
14.12
37.88
0
51
11.68
32.95
0
C-148
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Measured Se in
Spawn
diet fed to
No.
Se in parent tissues, mg/kg dw
Larval surviva
0/
, /o
parents,
mg/kg dwa
Muscle
Ovary
Average
Individual
Average
52
11.16
59.89
0
22
18.15
46.22
0
25
21.07
70.45
0
30
25.02
81.62
0
31
16.63
54.99
0
53.1 ±4.8
32
14.3
53.96
61.0
0
0
(45.5-61.9)
41
17.73
51.48
0
48 (2F)
26.25
84.31
0
50 (2F)
11.66
32.87
0
55
18.36
73.33
0
4 (2F)
12.6
66.81
66
7
17.24
56.98
0
8
20.36
86.49
0
10
19.59
65.99
0
18
22.52
72.35
0
78.4 ±4.3
21
18.58
71.89
77.6
0
5.5
24
22.08
62.44
0
(73.2-87.0)
28
29.15
99.02
0
38
58.2
52.37
0
44
17.7
102.82
0
47
24.14
88.15
0
49
18.94
105.29
0
a ± standard error; range of concentrations in parentheses.
Table 2. Se concentrations in muscle and ovary of field-collected (Mayo Reservoir) female
largemouth bass.
Date
Se Muscle (mg/kg dw)
Se Ovary (mg/kg dw)
Ovary to Muscle Ratio
05/10/95
8.48
14.79
1.74
05/10/95
8.48
14.79
1.74
05/09/95
7.29
8.35
1.15
04/21/94
15
19
1.27
04/20/94
15
15
1.00
04/22/94
12
14
1.17
04/22/94
10
18
1.80
04/25/94
18
15
0.83
04/25/94
18
15
0.83
04/27/94
11
12
1.09
04/27/94
11
9.4
0.85
04/27/94
13
10
0.77
05/04/94
11
11
1.00
Median Ratio 1.09
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CO
>
CO
c
0
y
0
CL
100
80
60
40
20
5 10 20
mg Se/kg ovary
50
100
Figure 1. Largemouth bass larval survival relative to Se in ovary. TRAP interpolation was
used to estimate the ECio value. The higher concentration point for the interpolation was set at
32.9 mg/kg (ECioo) and the lower concentration point for the interpolation was set at 24.6
(NOEC) with greater than the average 90.3% background survival. This results in an ECio of
26.3 mg/kg and a steep slope of 16.
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APPENDIX D: Summary Studies of Non-
Reproductive Effects
D-l
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1.0 Studies of Non-Reproductive Effects
1.1 Acipenseridae
1.1.1 Acipenser transmontanus (white sturgeon)
Juvenile white sturgeon were exposed for 8 weeks to a series of 5 concentrations of seleno-L-methionine
added to an artificial diet (Tashjian et al. 2006). Survival was not affected by selenium treatment with a
mean survival rate of 99% across all groups. Fish fed the highest three dietary treatments of selenium,
41.7, 89.8 and 191.1 mg Se/kg dw, exhibited significant declines in growth assessed by body weight
measurements. The ECi0 for reduction in body weight is 15.08 mg Se/kg dw in whole body or 27.76 mg
Se/kg dw muscle; the EC2o is 17.82 mg Se/kg dw in whole body or 32.53 mg Se/kg dw muscle tissue. The
criterion values derived in this document that are based on reproductive endpoints are protective of the
endpoint measured in this non-reproductive study.
1.2 Cyprinidae
1.2.1 Pogonichthys macrolepidotus (Sacramento splittail)
Teh et al. (2004) exposed juvenile Sacramento splittail (7 months-old) to 8 levels of dietary selenium, 0.4
(no added selenium), 0.7, 1.4, 2.7, 6.6, 12.6, 26.0, and 57.6 mg/kg. Selenium was added to the diet via
selenized yeast which was diluted with Torula yeast (inactive) to attain the target levels. Mortality,
growth, histopathology, deformities and selenium content in muscle and liver were observed or measured
after 5 and 9 months of exposure. The appearance of deformities was the most sensitive endpoint. The
authors determined the occurrence of deformities was higher in fish fed 6.6 and 12.6 mg Se/kg in their
diet; however, such pathology was examined for only 15 of the 120 individuals per treatment, and a
consistent concentration-response relationship did not occur (i.e., no deformities in the high
concentration). The lack of a concentration-response relationship for the incidence of deformities has also
been observed in another study. Crane et al. (1992) exposed a European species of perch, Perca fluviatilis
to three aqueous and dietary selenium treatments in experimental ponds for 288 days up through
spawning. Crane et al. (1992) found an increased occurrence of deformities in embryos and larvae in the
lowest selenium treatment relative to the control, but a decrease in the middle treatment. No hatching
occurred in the high treatment. Teh et al. (2004) proposed several physiological mechanisms to explain
the lack of a dose-response relationship, but it appears that the underlying mechanism is not understood at
this time. Toxicity tests with unusual dose-response relationships are typically not considered for criteria
derivation, but since another assay (Crane et al. 1992) observed a similar relationship, the Teh et al.
(2004) study with P. macrolepidotus is included. Using prevalence of deformities as the endpoint, the
NOEC, LOEC and MATC (chronic value) in muscle tissue are 10.1, 15.1 and 12.34 mg Se/kg dw,
respectively. The critieron value in muscle tissue, based on the reproductive ECi0, is 11.8 mg Se/kg dw.
Appendix C provides further details on the study results and an approximate estimate of their relationship
to egg-ovary and whole-body concentrations. Teh et al. (2004) is the only study in which deformities
developed in fish that were not exposed to selenium from their mothers' ovaries. The selenium criterion
values derived based on reproductive endpoints are protective of the endpoint measured in this non-
reproductive study, considering the non-reproductive muscle MATC of 12.3 mg Se/kg dw is greater than
the reproductive muscle criterion of 11.8 mg Se/kg dw.
1.2.2 Pimephales promelas (fathead minnows)
Non-reproductive chronic values for fathead minnows were derived from two laboratory-based studies.
These studies (Bennett et al. 1986 and Dobbs et al. 1996) involved exposing algae to selenium (either as
D-2
-------
sodium selenite or sodium selenate) in water, and subsequently feeding the algae to rotifers which were in
turn fed to fathead minnows. In the Bennett et al. (1986) study, larval fathead minnows were fed control
rotifers (cultured in chambers without selenium containing algae) or selenium-contaminated rotifers
(cultured in chambers with selenium containing algae previously exposed to sodium selenite in the water)
in three separate experiments lasting 9 to 30 days. The different experiments were distinguished by 1) the
day selenium-laden rotifers were first fed; 2) the day selenium-laden rotifers were last fed; and 3) the age
of larvae at experiment termination. The results from the three experiments reported by Bennett et al.
(1986) were conflicting. Larval growth was significantly reduced at larval whole-body selenium
concentrations of 43.0 mg Se/kg dw in the first experiment and 51.7 mg Se/kg dw in the second
experiment, but was slightly but not significantly reduced at 61.1 mg Se/kg dw in the third experiment
(see Appendix C). Following the approach of Section 7.1.1, the geometric mean of these three values,
51.40 mg Se/kg dw, is the chronic value for this study.
Dobbs et al. (1996) used atest system similar to that of Bennett et al (1986) (described above). Larval
fathead minnows were exposed to the same concentrations of sodium selenate in the water as their prey
(rotifers), but also received additional selenium from the consumption of the selenium-contaminated
rotifers. In this study, the fathead minnows did not grow well at concentrations exceeding 108.1 |_ig Se/L
in water, and they survived only to 11 days at selenium concentrations equal to or greater than 393.0 (ig/L
in the water (75 mg Se/kg dw in the diet, i.e., rotifers). The LOEC for retarded growth (larval fish dry
weight) in this study was <73 mg Se/kg dw tissue.
A third laboratory study, by Ogle and Knight (1989), examined the chronic effects of elevated foodborne
selenium on growth and reproduction of fathead minnows. Juvenile fathead minnows were fed a purified
diet mix spiked with inorganic and organic selenium in the following percentages: 25 percent selenate, 50
percent selenite, and 25 percent seleno-L-methionine. The pre-spawning exposure lasted 105 days using
progeny of adult fathead minnows originally obtained from the Columbia National Fishery Research
Laboratory, as well as those obtained from a commercial fish supplier. After the 105 day exposure period,
a single male and female pair from each of the respective treatment replicates were isolated and inspected
for spawning activity for 30 days following the first spawning event of that pair. There was no effect from
selenium on any of the reproductive parameters measured, including larval survival, at the dietary
concentrations tested (5.2 to 29.5 mg Se/kg dw food). Sub-samples of larvae from each brood were
maintained for 14 days post-hatch and exhibited >87.4 percent survival. The pre-spawning adult fish fed a
mean dietary level of 20.3 mg Se/kg dw exhibited a significant reduction in growth compared to controls
(16 percent reduction), whereas a nonsignificant reduction in growth (7 percent) occurred in the fish fed
15.2 mg Se/kg dw. The chronic value, as determined by the geometric mean of the NOEC and the LOEC
measured at 98 days post-test initiation, was 17.57 mg Se/kg expressed as the above dietary
concentrations, and 5.961 mg Se/kg dw as fathead minnow whole-body tissue. The concentration-
response relationship, as indicated by the study data presented in Appendix E, was uniformly shallow; not
resembling the sharp sigmoidal function characteristic of most selenium response curves.
Since Ogle and Knight reported that food in the higher selenium concentrations remained uneaten and
fish were observed to reject the food containing the higher selenium concentrations, the authors suggested
that the decreased growth was caused by a reduced palatability of the seleniferous food items, which
contained unnatural percentages of inorganic selenium (Fan et al. 2002). This is a common observation
also noted by Hilton and Hodson (1983) and Hilton et al. (1980) and apparent in Coughlan and Velte
(1989). It is here interpreted to be an artifact of unrealistic spiking of the diet with inorganic selenium in
this early experimental protocol. That is, in the real world it is not expected that avoidance of food items
that were unpalatable because of excessive selenium would be either a mechanism by which selenium
causes effects or a mechanism by which organisms can avoid exposure. (See Janz et al. (2010) for a more
complete discussion of selenium's mechanism of toxicity.) Given the no observed effect on larval
D-3
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survival and the apparent non-toxicological effect on growth in the Ogle and Knight study, a chronic
value for this study is not included.
1.3 Catostomidae
1.3.1 Xyrauchen texanus (razorback sucker)
Two non-reproductive endpoint studies have been done with the endangered razorback sucker. In the first
study, Beyers and Sodergren (2001a) exposed larval razorback suckers for 28 days to a range of aqueous
selenate concentrations (6.12, 25.4, 50.6, 98.9, and 190.6 |ig/L) and respectively fed them a range of
selenium in their diet (rotifers containing <0.702, 1.35, 2.02, 4.63, and 8.24 mg/kg dw). Reflecting the
lack of effects on survival and growth in any exposure, the chronic value for this study, based on selenium
measured in the larvae at the end of the test, is >12.9 mg Se/kg dw.
In a second study, Beyers and Sodergren (2001b) exposed larval razorback suckers to a control water and
three different site waters containing varying concentrations of selenium for 28 days. Two treatments
were tested within each water type: fish fed rotifers cultured in the same water type (site diet) and fish fed
rotifers cultured in control water. There were no reductions in survival or growth in fish exposed to both
the site water and site diet compared to fish exposed to control water and control diet. There were,
however, reductions in growth of fish exposed to site water/site food compared to the same site water and
control food. The authors did not attribute the effect on larval growth by the diet to selenium and cited
several lines of evidence, including: (1) there was not a dose-response relationship in the concentration of
selenium in the food (rotifers) and growth, nor in the concentration of selenium in the fish larvae and
growth across the three water types; and (2) water from the De Beque site promoted a significant
reduction in the growth of fish exposed to site water/site food relative to site water/control food, but
contained low levels of selenium in the water (<1 |ig/L) and in food (2.10 mg/kg dw) typically lower than
those that have been found to elicit effects. The chronic value for this study is >42 mg Se/kg dw based on
the whole body concentration of selenium in the larval razorback suckers exposed to North Pond site
water.
Two similar studies were conducted in 1996 and 1997 to determine effects of site water and site food,
both contaminated with selenium, on the razorback sucker (Hamilton et al. 200la,b; published later in a
peer-reviewed journal in 2005, see Hamilton et al. 2005 a,b,c). Both studies show marked effects of
selenium on survival of razorback sucker larvae exposed to contaminated food and to a lesser extent,
contaminated water. Although the data convincingly demonstrate effects to larval survival from exposure
to contaminated food, interpretation of the results, of chronic criterion derivation is complex because of
inconsistencies between: 1) levels of selenium in the food and larvae relative to larval survival; 2) the
time to larval mortality relative to selenium in the diet and selenium in the larvae; and 3) levels of other
inorganic contaminants in food and water (possible organic contaminants were not measured). Summaries
of each of these two studies as well as a third study with razorback suckers (Hamilton et al. 2005d) are
presented in Appendix E.
Due to the confounding results, lack of dose-response within and among related studies, and the
uncertainty of the effect of other inorganic contaminants on larval response to the various dietary and
waterborne treatments, the data from these three studies for razorback sucker (Hamilton et al. 200la,b;
Hamilton et al. 2005d) have not been included. A more detailed explanation of why these studies were not
included is given in Appendix E. Because of the vastly different results between the Beyers and
Sodergren studies and Hamilton et al. studies and the inability to resolve the differences, SMCV and
GMCV were not calculated for the razorback sucker.
D-4
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1.3.2 Catostomus latipinnis (flannelmouth sucker)
Beyers and Sodergren (2001a) exposed flannelmouth sucker larvae to a range of aqueous selenate
concentrations (<1, 25.4, 50.6, 98.9, and 190.6 (ig/L) and fed them a range of selenium in their diet
(rotifers containing <0.702, 1.35, 2.02, 4.63, and 8.24 mg/kg dw, respectively). There were no survival or
growth effects observed after the 28 day exposure. The chronic value based on the concentration of
selenium measured in the larvae exposed to the highest test concentration was >10.2 mg Se/kg dw.
1.4 Salmonidae
1.4.1 Oncorhynchus tshawytscha (Chinook salmon)
Hamilton et al. (1990) conducted a 90-day growth and survival study with swim-up larvae fed one of two
different diets. The first diet consisted of Oregon moist™ pellets where over half of the salmon meal was
replaced with meal from selenium-laden mosquitofish (Gambusia affinis) collected from the San Luis
Drain, CA (SLD diet). The second diet was prepared by replacing half the salmon meal in the Oregon
moist™ pellets with meal from low-selenium mosquitofish (i.e., the same relatively uncontaminated
mosquitofish that were used in the control diet) and spiked with seleno-DL-methionine (SeMe diet).
Analysis of the trace element composition in the two different diets indicated that while selenium was the
most toxic element in the SLD diet, concentrations of boron, chromium, iron and strontium in the high-
selenium mosquitofish replacement diet (SLD diet type) were slightly elevated compared to the
replacement diet. These trace elements were, however, only 1.2 (e.g., iron) to 2.0 times (e.g., chromium)
higher in the SLD diet than the SeMe diet, which contained the following measured concentrations (dry
weight basis) in the food: 10 mg boron/kg, 2.8 mg chromium/kg, 776 mg iron/kg, and 48.9 mg
strontium/kg.
During the test, survival of control Chinook salmon larvae (consuming food at approximately 3 mg Se/kg
dw) was 99 percent up to 60 days post-test initiation. Between 60 and 90 days of exposure, however, the
control survival declined to 66.7% in the SLD test and to 72.5% in the test using the SeMe diet, indicating
compromised health. Therefore, only data collected up to 60 days post-test initiation were considered for
analysis. Nevertheless, there remains the possibility that even at 60 days, the control organisms were not
healthy, although overt signs of stress did not appear until later.
For the SeMe diet, regression analysis of the 60-day growth data yielded a whole-body ECi0 of 7.355 mg
Se/kg dw and an EC2o of 10.47 mg Se/kg dw. For the SLD diet, regression analysis of the 60-day growth
data yielded a whole-body ECi0 of 11.14 mg Se/kg dw and an EC2o of 15.73 mg Se/kg dw. Note: The San
Luis Drain mosquitofish (comprising the Chinook salmon's SLD diet) were not tested for contaminants
other than certain key elements. Because the San Luis Drain receives irrigation drainage from the greater
San Joaquin Valley, there is a possibility that the SLD diet might have contained elevated levels of
pesticides, possibly a confounding factor, although the SLD diet was less toxic than the SeMe diet.
D-5
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1.4.2 Oncorhynchus mykiss (rainbow trout)
Hilton and Hodson (1983) reared juvenile rainbow trout on either a high (25 percent) or low (11 percent)
available carbohydrate diet supplemented with sodium selenite for 16 weeks. Body weights, feed: gain
ratios, and total mortalities were followed throughout the exposure every 28 days. Tissues (livers and
kidneys) were extracted for selenium analysis after 16 weeks. By the end of the exposure, fish fed diets
(low carbohydrate and high carbohydrate) with the highest selenium concentrations (11.4 and 11.8 mg
Se/kg dw food, respectively) exhibited a 45 to 48 percent reduction in body weight (expressed as kg per
100 fish) compared to control fish. The authors attributed such results to food avoidance. With only two
dietary exposure concentrations and a control, these data were not amenable to regression analysis. The
MATC for growth of juvenile rainbow trout relative to the concentrations of selenium in liver tissue of
trout reared on the high carbohydrate seleniferous dietary type is the geometric mean (GM) of 21.00 mg
Se/kg dw liver (NOEC) and 71.7 mg Se/kg dw liver (LOEC), or 38.80 mg Se/kg dw liver. The calculated
MATC for the same group of experimental fish exposed to selenium in the low carbohydrate diet is 43.5
mg Se/kg dw liver tissue, which is the same MATC for trout exposed for an additional 4 weeks based on
the occurrence of nephrocalcinosis in kidneys (see Hicks et al. 1984; Appendix C).
Hilton et al. (1980) employed a similar test design to that of Hilton and Hodson (1983) to examine the
narrow window at which selenium changes from an essential nutrient to a toxicant affecting juvenile
rainbow trout. The food consisted of a casein-Torula yeast diet supplemented with selenium as sodium
selenite. As discussed previously for the Ogle and Knight (1989) study with fathead minnow, this
represents an unrealistic fraction of inorganic selenium in the diet. The experiment lasted for 20 weeks.
During this time, the trout were fed to satiation 3 to 4 times per day, 6 days per week, with one feeding on
the seventh day. Organs (liver and kidney) and carcasses were analyzed for selenium from fish sacrificed
at 4 and 16 weeks. No gross histopathological or physiological effects were detected in the fish, although
trout raised on the highest dietary level of selenium (13.06 mg Se/kg dw food) had a significantly lower
body weight (wet basis), a higher feed:gain ratio, and higher number of mortalities (10.7; expressed as
number per 10,000 fish days). The MATC for growth and survival of juvenile rainbow trout relative to
the final concentrations of selenium in liver tissue is the geometric mean of the NOEC (40 mg Se/kg dw
liver) and the LOEC (100 mg Se/kg dw liver), or 63.25 mg Se/kg dw, both of which hinge on accepting
dietary spiking entirely with inorganic selenium as an acceptable experimental protocol.
The non-reproductive GMCV for Oncorhynchus (both rainbow trout and Chinook salmon) is 9.052 mg
Se/kg dw whole body based on the ECi0 value derived from the Hamilton et al. (1990) study with
Chinook salmon. The NOEC values for the rainbow trout studies conducted by Hilton and Hodson
(1983), Hilton et al. (1980), and Hicks et al. (1984) were not used in the GMCV calculation because of
the large difference between the NOEC and the LOEC values. If adult fish contained whole-body
selenium concentrations equal to 9.052 mg Se/kg dw, their egg-ovary concentrations would be estimated
to be 21.5 mg Se/kg dw when translated using the factor 2.37. The criterion values derived based on
reproductive endpoints are protective of the endpoint measured.
1.5 Moronidae
1.5.1 Morone saxitilis (striped bass)
A non-reproductive chronic value for selenium was determined from a laboratory dietary exposure
conducted using yearling striped bass (Coughlan and Velte 1989). During the experiment, the bass were
fed contaminated red shiners (38.6 mg Se/kg dw whole body) from Belews Lake, NC (treated fish) or
golden shiners with low levels of selenium (1.3 mg/kg dw whole body) purchased from a commercial
supplier (control fish). The test was conducted in soft well water and lasted up to 80 days. During the
experiment, all fish were fed to satiation 3 times per day. Control fish grew well and behaved normally.
D-6
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Treated fish behaved lethargically, grew poorly due to a significant reduction in appetite, and showed
histological damage, all eventually leading to the death of animals. The final selenium concentration in
muscle of treated striped bass averaged from 16.2 to 18.5 mg/kg dw tissue (assuming 78.4 percent
moisture content), which was 3.4 to 3.6 times higher than the final selenium concentrations in control
striped bass, which averaged 5.10 mg/kg dw tissue. The chronic value for this species was determined to
be <16.2 mg Se/kg dw in muscle tissue.
1.6 Centrarchidae
1.6.1 Lepomis macrochirus (bluegill)
Bryson et al. (1985b) conducted juvenile survival toxicity tests using hatchery bluegill and various forms
of selenium spiked to an artificial diet as well as a diet consisting of zooplankton collected from Hyco
Reservoir. There was no effect on length or weight of the juvenile bluegill after 60 days of exposure. The
highest concentration of selenium measured in whole body of the juveniles in these tests was in the
seleno-DL-cysteine-2X treatment (3.74 mg Se/kg dw).
Cleveland et al. (1993) performed a 90-day diet-only laboratory exposure in which juvenile bluegill were
fed a range of selenomethionine concentrations added to Oregon moist™ pellets. The authors observed no
significant effects on survival, but did report a very small but apparently statistically significant decrease
in the condition factor, K, from 1.3 at four concentrations between 1.0 and 4.7 mg Se/kg dw whole body,
to 1.2 at the two concentrations 7.7 and 13.4 mg Se/kg dw whole body. The condition factor (weight x
105/length3) is intended to reflect a fish's reserves. In contrast to the studies of Ogle and Knight (1989),
Hilton and Hodson (1983), and Hilton et al. (1989), which appear to have involved an inorganic selenium
food palatability problem, this study did not use inorganic selenium in the diet. Nevertheless, given that
the reduction in K (1.3 to 1.2) is slight and shows no increasing effect between 7.7 and 13.4 mg Se/kg dw,
thus not yielding a sigmoidal concentration-response curve to support an ECio calculation, the chronic
value for this study was estimated at >13.4 mg Se/kg dw in whole body tissue.
Data from Lemly (1993a) indicate that over-wintering fish may be more susceptible to the effects of
waterborne and dietary selenium due to increased sensitivity at low temperature. The author exposed
juvenile bluegill in the laboratory to a single elevated exposure level, waterborne (1:1 selenite:selenate;
nominal 5 |_ig Se/L) and foodborne (seleno-L-methionine in TetraMin; nominal 5 mg Se/kg dw food)
selenium for 180 days. Tests with a control and the treated fish were run at 4°C and 20°C with biological
and selenium measurements made every 60 days. Survival and whole-body lipid content were unaffected
at 20°C (whole-body selenium concentrations equal to 6 mg/kg dw, the sole treatment exposure) when
compared to control fish. Thus, at 20°C the chronic value for juvenile bluegill exposed to waterborne and
dietary selenium based on survival was >6 mg/kg dw in whole-body tissue. Fish exposed to the
combination low-level waterborne and dietary selenium at 4°C exhibited significantly elevated mortality
(40.4 percent) relative to controls (2.9 percent), and exhibited significantly greater oxygen consumption
and reduced lipid content, which are indicative of stress. At 4°C the chronic value for juvenile bluegill
exposed to waterborne and dietary selenium was <7.91 mg Se/kg dw in whole body based on mortality
and tissue measurements at the end of the test (180 days), and 5.85 mg Se/kg dw in whole body based on
mortality at 180 days and tissue measurements at 60 days. The increase in the concentration of whole-
body selenium between Day 60 and 180 at 4°C was apparently due to reductions in body weight caused
by loss of lipid (comparatively low in selenium) while body burden in other tissues remained relatively
constant. If this concentration of selenium in tissues occurs in sensitive overwintering fish in nature, a
concentration of 5.85 mg/kg dw (the selenium tissue concentration in the 4°C exposure after 60 days) in
fish collected during the summer or fall months could be considered a threshold concentration for the
selenium-sensitive fish during the winter months. Therefore, this study's chronic value for the threshold
concentration prior to winter stress is 5.85 mg Se/kg dw in whole body tissue.
D-7
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Mclntyre et al. (2008) also investigated the toxicity of selenium to juvenile bluegill under cold
temperature conditions in the laboratory. Whereas relative to the control, Lemly (1993a) tested only one
exposure level, 5 mg Se/kg in the diet and 5 |ig Se/L and one low temperature regime, 4°C, Mclntyre et
al. (2008) evaluated a range of diet and water concentrations, two types of diet, and two low-temperature
regimes. The goal of the study was to determine ECi0 and EC2o values for selenium exposure to juvenile
bluegill in 4°C and 9°C low-temperature regimes. Three separate exposure systems were run concurrently
for 182 days. Two systems exposed juvenile bluegill to a series of six aqueous and dietary selenium
treatments and a control; one exposure system (ESI) with a cold temperature regime (4°C), and one (ES3)
with a cool temperature regime (9°C), both using a yeast-worm-fish food chain bioaccumulation system.
That is, graded levels of selenized-yeast in ESI and ES3 were fed to the oligochaete, Lumbriculus
variegatus, which in turn was fed to bluegill. The third exposure system (ES2) used diet and exposure
conditions similar to Lemly's 4°C treatment, i.e., nominal 5 |_ig Se/L in the water and nominal 5 mg Se/kg
dw food (seleno-L-methionine in TetraMin). The cold temperature regime for ESI and ES2 was 20°C for
the first 30 days of exposure, and then decreased 2°C/week until it reached 4°C (test day 79) at which
point temperature was maintained until test termination (test day 182). The cool temperature regime
(ES3) was similar except when the temperature reached 9°C (test day 65), it was maintained until test
termination (test day 182).
At the end of the 182 day exposure in the ES2 (with Lemly's diet and temperature), the bluegill
accumulated an average (geometric mean) whole body concentration of 9.99 mg/kg dw with no
meaningful mortality in the treatment or control. Significant mortality of juvenile bluegill was observed in
the two highest treatments in the cold (ESI) and cool (ES3) Lumbriculus-fed tests. No effects on body
weight or condition factor were observed. The ECi0 and EC2o values for the cold treatment (ES1) are 9.27
and 9.78 mg Se/kg dw in whole body, respectively. The ECio and EC2o values for the cool treatment
(ES3) are slightly higher at 14.00 and 14.64 mg Se/kg dw in whole body, respectively.
The design and the results of the Mclntyre et al. (2008) study have similarities and differences with
Lemly (1993a), as presented in detail with comparisons and contrasts in Appendix C. Both studies found
juvenile bluegill were more sensitive in a cold-temperature regime than in a cool (Mclntyre et al.) or a
warm regime (Lemly). The effect levels determined for the cold temperature regime differed by a factor
of 1.58 (ESI of Mclntyre et al., 9.27 mg Se/kg; Lemly, 5.85 mg Se/kg), a difference rather typical of
chronic studies conducted in different laboratories using different fish populations (Delos 2001) and
similar to the 1.51 factor difference between two ECi0s ofHamilton etal. (1990) for chinook salmon.
The difference in the effect levels of the Mclntyre ES2 exposure (>9.99 mg/kg) and the Lemly study
(5.85 mg/kg) could have been due to the fitness of the fish entering the cold regime. The condition factor,
K, in the ES2 selenium-exposed bluegill increased from 3.2 at the start of the exposure to 5.2 at day 60
(approximately 10°C at day 60) and decreased only slightly through over 100 days of 4°C exposure (see
figure in bluegill summary in Appendix C). In contrast, K in the Lemly selenium-exposed fish decreased
approximately 50% after 120 days of exposure. Shoup and Wahl (2011) conducted an overwinter
exposure study with bluegill in which they fed and starved young of year bluegill (the larger size similar
to the Mclntyre and Lemly fish) under two temperature regimes, 4°C (harsh winter) and 9°C (mild
winter) for 140 days and a 10 h light: 14 h dark photoperiod. The juvenile bluegill in the Shoup and Wahl
study ate in both temperature regimes. The 4°C exposed fish consumed 0.4-0.8% of their body
weight/day and their K was not significantly different at the end of the test compared to the start. The
Shoup and Wahl results only provide an indication that cold-exposed fish under a winter photoperiod feed
and can maintain K.
D-8
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The mortality observed in the Lemly laboratory study does not appear to be consistent with field
observations. The occurrence of mortality in the field at the concentrations Lemly (1993a) reported to
cause mortality in his lab was not observed in the Lemly (1993b) field study of centrarchid deformities in
Belews Lake. In that field study, Lemly (1993b) found larval centrarchid deformities at concentrations
ranging from 12-80 mg Se/kg dw WB. If juvenile mortality occurred at concentrations lower than those
found to induce larval deformities and at concentrations as low as Lemly (1993a) reported in the lab (EC40
= 7.91 mg Se/kg WB), then centrarchids would likely not have been present in Belews Lake. The
observations of Lemly (1993b) are evidence that larval deformity, not juvenile mortality, is the more
sensitive endpoint.
The Crutchfield and Ferson (2000) predictions and field observations of recovery of bluegill at Hyco
Reservoir likewise suggest that significant mortality was unlikely to be occurring at the concentrations
Lemly (1993a) reported to cause substantial mortality. During a time period over which Crutchfield
(2000) indicated dietary invertebrate concentrations exceeded 20 mg Se/kg dw, Crutchfield and Ferson
(2000) indicated that bluegill population growth occurred at rates predicted to be natural for the
unimpaired species. In contrast, if the Lemly (1993a) lab EC40 of 7.91 mg Se/kg dw whole-body were
applicable to this field situation, the mortality associated with the resulting bluegill whole-body
concentrations (25 mg Se/kg dw whole-body, assuming a trophic transfer factor of 1.27) would have
prevented any recovery.
Selenium-induced cold temperature loss of lipid and body condition, a non-reproductive sublethal effect
that Lemly (1993a) observed to accompany juvenile mortality in the laboratory (but which Mclntyre et al.
(2008) did not observe in a similar study) has also not generally been corroborated by field evidence (Janz
2008). Several studies have measured growth and energy storage indicators in juvenile fish just prior to
and just after winter at reference sites and sites with elevated selenium in northern Canada (Bennett and
Janz 2007a, b; Kelly and Janz 2008; Driedger et al 2009; Weber et al. 2008). The growth (length, weight,
condition factor, muscle RNA:DNA ratio, muscle protein) and energy storage (whole body lipids, whole
body triglycerides, liver triglycerides, liver glycogen) indicators for five fish species (northern pike,
burbot, fathead minnow, creek chub, white sucker) measured just after winter were similar or greater than
those measured just before winter at the selenium exposed sites. The slimy sculpin did show a decrease in
whole body triglycerides, but the reduction was similar at exposed and reference sites.
Given the uncertainty in the occurrence of winter stress, the results of all four cold-temperature (4°C and
9°C) juvenile-survival lab studies were combined per the standard procedure described in the U.S.EPA
Ambient Water Quality Criteria Guidelines, to determine the non-reproductive SMCV for bluegill. The
SMCV for the combined 4°C and 9°C tests is 9.33 mg Se/kg dw whole body, based on the four chronic
values: (a) the Lemly (1993a) concentration prior to winter stress (5.85 mg Se/kg dw whole body), (b) the
Mclntyre et al. (2008) ESI ECi0 (9.27 mg Se/kg dw whole body), (c) the Mclntyre et al. (2008) ES2
NOEC (>9.992 mg Se/kg dw whole body), and the Mclntyre et al. (2008) ES3 ECi0 of 14.00 mg Se/kg
dw whole body. This value is not less than the reproductive endpoint-based whole-body criterion
concentration of 8.5 mg Se/kg dw. The studies of Bryson et al (1985b) and Cleveland et al. (1993) were
not conducted at cold temperatures and were thus not used for these SMCV calculations.
D-9
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Table D-l. Freshwater Chronic Values from Acceptable Tests - Non-Reproductive Endpoints (Parental Females Not Exposed).
(Same as Table 6.2 in the main document).
llxposuiv mull'
Toxicologic;!!
Chronic miIiic.
SMCY
c;m( y
Species
Rcld'cncc
iiiid (lui'iilioii
Selenium I'nnii
cmlpoini
niii/kii 12.9 WBb
see text
see text
Xyrauchen texanus
razorback sucker
Beyers and
Sodegren 2001b
dietary and
waterborne (lab)
28 days
water: site waters; diet:
algae exposed to site
water then fed to rotifers
which were fed to fish
NOEC for survival
and growth
>42 WBb
water: selenate;
Catostomus latipinnis
flannelmouth sucker
Beyers and
Sodegren 2001a
dietary and
waterborne (lab)
28 days
diet: algae exposed to
selenate in water then
fed to rotifers which
were fed to fish
NOEC for survival
and growth
>10.2 WB
>10.2 WB
>10.2 WB
D-10
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Species
Keleivnce
l'l\poMirc mule
iiiid (lui'iilioii
Selenium I n nil
Toxicologic;!!
cnripoinl
Chronic \;iluc.
niii/kti 6.0 WB
Lepomis macrochirus
bluegill
Mclntyre et al.
2008
dietary and
waterborne (lab)
182 days
20 to 4°C (ESI)
diet: Lumbriculus fed
selenized-yeast
water: 1:1
selenate: selenite
ECiojuv. survival
ESI
9.27 WB
EC2ojuv. survival
ESI
9.78 WB
dietary and
waterborne (lab)
182 days
20 to 9°C (ES3)
diet: Lumbriculus fed
selenized-yeast
water: 1:1
selenate: selenite
ECiojuv. survival
ES3
14.00 WB
EC2ojuv. survival
ES3
14.64 WB
D-ll
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Species
Reference
l'l\poMirc mule
iiiid (lui'iilioii
Selenium Itiriii
Toxicologic;!!
ciulpoinl
Chronic \;iluc.
niii/kti 9.992 WB
Lepomis macrochirus
bluegill
Bryson et al.
1985b
dietary (lab)
60 days
seleno-DL-cysteine
NOEC for juvenile
growth
>3.74 WBb
Lepomis macrochirus
bluegill
Cleveland et al.
1993
dietary (lab)
90 days
seleno-L-methionine
NOEC for juvenile
survival
>13.4 WBb
All chronic values reported in this table are based on the measured concentration of selenium in whole body (WB), muscle (M) or liver (L)
tissues.
Chronic value not used in SMCV calculation (see text).
Tissue value converted from ww to dw. See Appendix C for conversion.
D-12
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APPENDIX E: Other Data
E-l
-------
1.0 Selenite
Additional data on the lethal and sublethal effects of selenium on aquatic species are presented in
Table E-l. Bringmann and Kuhn (1959a,b, 1976, 1977a, 1979, 1980b, 1981), Jakubczak et al. (1981), and
Patrick et al. (1975) reported the concentrations of selenite that caused incipient inhibition (defined
variously, such as the concentration resulting in a 3% reduction in growth) for algae, bacteria, and
protozoans (Table E-l). Although incipient inhibition might be statistically significant, its ecological
importance is unknown. Albertano and Pinto (1986) found the growth of three red algal species was
inhibited at selenite concentrations that ranged from 790 to 3,958 |ig/L.
2.0 Selenate
Dunbar et al. (1983) exposed fed D. magna to selenate for seven days and obtained an LC50 of
1,870 |ig/L. This value is in the range of the 48-hr EC50s in Table E-l.
Watenpaugh and Beitinger (1985a) found that fathead minnows did not avoid 11,200 |ig/L
selenate during 30-minute exposures (Table E-l). These authors also reported (1985b) a 24-hr LC50 of
82,000 (ig/L for the same species and they found (1985c) that the thermal tolerance of the species was
reduced by 22,200 |ig/L. Westerman and Birge (1978) exposed channel catfish embryos and newly
hatched fry for 8.5 to 9 days to an unspecified concentration of selenate. Albinism was observed in 12.1
to 36.9% of the fry during the five years of such exposures. Pyron and Beitinger (1989) also investigated
fathead minnows, and after a 24-hr exposure, no effect on reproductive behavior was found at 36,000
|ig/L. but when adults were exposed to 20,000 |ig/L selenate for 24-hr, edema was observed for their
larvae.
The respiratory rate of the eastern oyster, Crassostrea virginica, was unaffected by exposure to
selenate at 400 |ig/L for 14 days (Fowler et al. 1981). Embryos of the striped bass were quite tolerant to
selenate in dilute salt water (Klauda 1985a, b). There was a 93% successful hatch of embryos at 200,000
(ig/L, but 50% of 72-day-old juveniles died after four days at 87,000 (ig/L. Exposure of juvenile fish for
up to 65 days to concentrations of selenate between 39 and 1,360 |ig/L caused developmental anomalies
and pathological lesions.
E-2
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Table E-l. Other Data on Effects of Selenium on Aquatic Organisms
Species
Chemical
1 lardness
(in«/l- as
C aC (),)
Duration
lillecl
Concentration''
Reference
FRESHWATER SPECIES
Selenium (IV)
Green alga,
Scenedesmus
quadricauda
Sodium
selenite
-
96 hr
Incipient
inhibition
(river water)
2,500
Bringmann and
Kuhn 1959a,b
Green alga,
Selenastrum
capricornutum
Sodium
selenite
-
72 hr
Decreased dry
weight and
chlorophyll a
75
Foe and Knight,
Manuscript
Green alga,
Selenastrum
capricornutum
Sodium
selenite
-
72 hr
BCF = 12-2 lb
10-100
Foe and Knight,
Manuscript
Green alga,
Selenastrum
capricornutum
Sodium
selenite
-
72 hr
BCF =
11,164°
150
Foe and Knight,
Manuscript
Alga,
Chrysochromulina
breviturrita
Selenious
acid
-
30 days
Increased
growth
320
Wehr and Brown
1985
Red alga,
Cyanidium caldarium
Selenious
acid
-
20 days
Inhibited
growth
3,958
Albertano and
Pinto 1986
Red alga,
Cyanidioschyzon
merolae
Seleniousa
cid
-
20 days
Inhibited
growth
3,140
Albertano and
Pinto 1986
Red alga,
Galdieria sulphuraria
Seleniousa
cid
-
20 days
Inhibited
growth
790
Albertano and
Pinto 1986
Algae (diatoms),
Mixed population
Sodium
selenite
-
18 days
Inhibited
growth
11,000
Patrick etal. 1975
Bacterium,
Escherichia coli
Sodium
selenite
-
-
Incipient
inhibition
90,000
Bringmann and
Kuhn 1959a
Bacterium,
Pseudomonus putida
Sodium
selenite
-
16 hr
Incipient
inhibition
11,400
(11,200)
Bringmann and
Kuhn 1976;
1977a; 1979;
1980b
Protozoan,
Entosiphon sulcatum
Sodium
selenite
-
72 hr
Incipient
inhibition
1.8
(1.9)
Bringmann 1978;
Bringmann and
Kuhn 1979;
1980b;1981
Protozoan,
Microreqma
heterostoma
Sodium
selenite
-
28 hr
Incipient
inhibition
183,000
Bringmann and
Kuhn 1959b
Protozoan,
Chilomonas
Paramecium
Sodium
selenite
-
48 hr
Incipient
inhibition
62
Bringmann and
Kuhn 1981;
Bringmann et al.
1980
E-3
-------
Species
C'lieiniciil
1 hirilness
(111l»/l- ilS
C :¦( ().i)
Diiriilion
lillecl
C'oncenlmlion''
Reference
Protozoan,
Uronema parduezi
Sodium
selenite
-
20 hr
Incipient
inhibition
118
Bringmann and
Kuhn 1980a; 1981
Snail,
Lymnaea stagnalis
Sodium
selenite
-
7.5 days
LT50
3,000
Van Puymbroeck
etal. 1982
Cladoceran,
Daphnia magna
Sodium
selenite
-
48 hr
EC50
(river water)
2,500
Bringmann and
Kuhn 1959a,b
Cladoceran,
Daphnia magna
Sodium
selenite
214
24 hr
LC50
16,000
Bringmann and
Kuhn 1977a
Cladoceran,
Daphnia magna
Sodium
selenite
214
24 hr
EC50
(swimming)
9.9
Bringmann and
Kuhn 1977b
Cladoceran,
Daphnia magna
Sodium
selenite
329
48 hr
96 hr
14 days
EC50 (fed)
710
430
430
Halter etal. 1980
Cladoceran (<24 hr),
Daphnia magna
Sodium
selenite
-
48 hr
21 days
EC50 (fed)
685
160
Adams and
Heidolph 1985
Cladoceran
(5th instar),
Daphnia magna
Sodium
selenite
-
48 hr
LC50 (fed)
680
Johnston 1987
Cladoceran,
Daphnia magna
Selenious
acid
220d
48 hr
LC50 (fed)
1,200
Kimball,
Manuscript
Cladoceran (preadult),
Daphnia pulex
Sodium
selenite
42
24 hr
Did not
reduce oxygen
consumption
or filtering
rate
>498
Reading and
Buikema 1980
Ostracod,
Cyclocypris sp.
Sodium
selenite
100.8
48 hr
LC50
130,000
Owsley 1984
Amphipod,
Hyalella azteca
Sodium
selenite
329
14 days
LC50 (fed)
70
Halter etal. 1980
Amphipod
(2 mm length),
Hyalella azteca
Sodium
selenite
133
48 hr
LC50
623
Brasher and Ogle
1993
Amphipod
(2 mm length),
Hyalella azteca
Sodiumsel
enite
133
10 days
LC50
(fed)
312
Brasher and Ogle
1993
Amphipod
(2 mm length),
Hyalella azteca
Sodium
selenite
133
24 days
LOEC
reproduction
(static-
renewal)
200
Brasher and Ogle
1993
Midge (first instar),
Chironomus riparius
Sodium
selenite
134
48 h
LC50
7,950
Ingersoll et al.
1990
Midge (first instar),
Chironomus riparius
Sodium
selenite
40-48
48 h
LC50
14,600
Ingersoll et al.
1990
Coho salmon (fry),
Oncorhynchus kisutch
Sodium
selenite
325
43 days
LC50
160
Adams 1976
Rainbow trout (fry),
Oncorhynchus mykiss
Sodium
selenite
334
21 days
LC50
460
Adams 1976
E-4
-------
Species
C'lieiniciil
1 hirilness
(111l»/l- ilS
C :¦( ().i)
Duration
lillecl
C'oncenlmlion''
Reference
Rainbow trout (fry),
Oncorhynchus mykiss
Sodium
selenite
334
21 days
Reduced
growth
250
Adams 1976
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
330
5 days
LC50
2,700
2,750
Adams 1976
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
325
48 days
LC50
500
Adams 1976
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
325
96 days
LC50
280
Adams 1976
Rainbow trout
(juvenile),
Oncorhynchus mykiss
Sodium
selenite
-
4 wk
MATC
survival
200
Gissel-Nielsen
and Gissel-
Nielsen 1978
Rainbow trout
(juvenile),
Oncorhynchus mykiss
Sodium
selenite
-
4 wk
MATC
survival
4.7
f-ig/g dw
(whole-body)
Gissel-Nielsen
and Gissel-
Nielsen 1978
Rainbow trout
(juvenile),
Oncorhynchus mykiss
Sodium
selenite
-
4 wk
BCF = 23
100
Gissel-Nielsen
and Gissel-
Nielsen 1978
Rainbow trout
(juvenile),
Oncorhynchus mykiss
Sodium
selenite
-
42 wk
MATC
growth
(dietary only
exposure)
>9.96
(ig Se/g dw
(food)
Goettl and Davies
1978
Rainbow trout
(juvenile),
Oncorhynchus mykiss
Sodium
selenite
-
42 wk
MATC
survival
(dietary only
exposure)
5.34
(ig Se/g dw
(food)
Goettl and Davies
1978
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
135
9 days
LC50
7,020
Hodson et al.
1980
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
135
96 hr
9 days
LC50
(fed)
7,200
5,410
Hodson et al.
1980
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
135
96 hr
9 days
LC50
(fed)
8,200
6,920
Hodson et al.
1980
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
135
41 days
LOAEC
(Reduced
hatch of eyed
embryos)
26
Hodson et al.
1980
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
135
50 wk
Decreased
iron in blood
and red cell
volume
53
Hodson et al.
1980
Rainbow trout
(fertilized egg),
Oncorhynchus mykiss
Sodium
selenite
135
44 wk
BCF = 33.2
BCF = 21.1
53
Hodson et al.
1980
Rainbow trout
(embryo),
Oncorhynchus mykiss
Sodium
selenite
-
120 hr
Did not
reduce
survival or
time to hatch
10,000
Klaverkamp et al.
1983b
E-5
-------
Species
C'lieiniciil
1 hirilness
(111l»/l- ilS
C :¦( ().i)
Diiriilion
lillecl
C'oncenlmlion''
Reference
Rainbow trout,
Oncorhynchus mykiss
Sodium
selenite
-
90 days
Chronic value
for survival
14
Mayer etal. 1986
Rainbow trout
(sac fry),
Oncorhynchus mykiss
Sodium
selenite
272
90 days
LC50
55.2e
Hunn et al. 1987
Rainbow trout
(sac fry),
Oncorhynchus mykiss
Sodium
selenite
272
90 days
MATC
survival
31.48
Hunnetal. 1987
Rainbow trout (egg),
Oncorhynchus mykiss
Sodium
selenite
-
96 hr
BCF = 17.5
BCF = 3.5
0.4
45.6
Hodson et al.
1986
Rainbow trout
(embryo),
Oncorhynchus mykiss
Sodium
selenite
-
96 hr
BCF = 3.1
BCF = 3.0
0.4
45.6
Hodson et al.
1986
Rainbow trout
(sac-fry),
Oncorhynchus mykiss
Sodium
selenite
-
96 hr
BCF = 13.1
BCF = 1.6
0.4
45.6
Hodson et al.
1986
Rainbow trout
(swim-up fry)
Oncorhynchus mykiss
Sodium
selenite
-
96 hr
BCF = 80.3
BCF = 20.2
0.4
45.6
Hodson et al.
1986
Northern pike,
Esox lucius
Sodium
selenite
10.2
76 hr
LC50
11,100
Klaverkamp et al.
1983a
Goldfish,
Carassius auratus
Selenium
dioxide
157
14 days
LC50
6,300
Cardwell et al.
1976a,b
Goldfish,
Carassius auratus
Sodium
selenite
-
10 days
Mortality
5,000
Ellis 1937; Ellis et
al. 1937
Goldfish,
Carassius auratus
Sodium
selenite
-
46 days
Gradual
anorexia and
mortality
2,000
Ellis etal. 1937
Goldfish,
Carassius auratus
Selenium
dioxide
-
7 days
LC50
12,000
Weir and Hine
1970
Goldfish,
Carassius auratus
Selenium
dioxide
-
48 hr
Conditional
avoidance
250
Weir and Hine
1970
Fathead minnow,
Pimephales promelas
Selenium
dioxide
157
9 days
LC50
2,100
Cardwell et al.
1976a,b
Fathead minnow,
Pimephales promelas
Sodium
selenite
329
96 hr
LC50
(fed)
1,000
Halter etal. 1980
Fathead minnow,
Pimephales promelas
Sodium
selenite
329
14 days
LC50
(fed)
600
Halter etal. 1980
Fathead minnow,
Pimephales promelas
Selenious
acid
220d
8 days
LC50
(fed)
420
Kimball,
Manuscript
Creek chub,
Semotilus
atromaculatus
Selenium
dioxide
-
48 hr
Mortality
312,000
Kim etal. 1977
Bluegill,
Lepomis macrochirus
Sodium
selenite
318
48 days
LC50
400
Adams 1976
Bluegill,
Lepomis macrochirus
Selenium
dioxide
157
14 days
LC50
12,500
Cardwell et al.
1976a,b
E-6
-------
Species
C'lieiniciil
1 hirilness
(111l»/l- ilS
C :¦( ().i)
Diiriilion
lillecl
C'oncenlmlion''
Reference
Bluegill (juvenile),
Lepomis macrochirus
Sodium
selenite
16
323 days
MATC
larval survival
(dietary only
exposure)
19.75
(ig Se/g dw
(food)
Woock et al. 1987
Bluegill (juvenile),
Lepomis macrochirus
Sodium
selenite
25
and
200
120 days
No mortality
>10
Lemly 1982
Largemouth bass
(juvenile),
Micropterus salmoides
Sodium
selenite
25
and
200
120 days
No mortality
10
Lemly 1982
Yellow perch,
Perca flavescens
Sodium
selenite
10.2
10 days
LC50
4,800
Klaverkamp et al.
1983a,b
African clawed frog,
Xenopus laevis
Sodium
selenite
-
7 days
LC50
1,520
Browne and
Dumont 1980
African clawed frog,
Xenopus laevis
Sodium
selenite
-
1-7 days
Cellular
damage
2,000
Browne and
Dumont 1980
Selenium (VI)
Alga,
Chrysochromulina
breviturrita
-
-
30 days
Increased
growth
50
Wehr and Brown
1985
Rotifer,
Brachionus
calyciflorus
Sodium
selenate
120
96 hr
EC20 Growth
(dry weight)
42.36
(Hg/g dw)
Dobbsetal. 1996
Snail,
Lymnaea stagnalis
Sodium
selenate
-
6 days
LT50
15,000
Van Puymbroeck
et al. 1982
Cladoceran,
Daphnia magna
Sodium
selenate
129.5
7 days
LC50
(fed)
1,870
Dunbar etal. 1983
Cladoceran (juvenile),
Daphnia magna
Sodium
selenate
-
48 hr
LC50
(fed)
550
Johnston 1987
Cladoceran (5th instar),
Daphnia magna
Sodium
selenate
-
48 hr
LC50
(fed)
750
Johnston 1987
42% of
Cladoceran (5th instar),
Daphnia magna
Sodium
selenate
-
90 hr
organisms had
visible
changes in gut
morphology
250
Johnston 1989
Amphipod
(2 mm length),
Hyalella azteca
Sodium
selenate
133
48 hr
LC50
2378
Brasher and Ogle
1993
Amphipod
(2 mm length),
Hyalella azteca
Sodium
selenate
133
10 days
LC50
(fed)
627
Brasher and Ogle
1993
Amphipod
(2 mm length),
Hyalella azteca
Sodium
selenate
133
24 days
LOEC
reproduction
(static
renewal)
>700
Brasher and Ogle
1993
E-7
-------
Species
C'lieiniciil
1 hirilness
(111l»/l- ilS
C :¦( ().i)
Diiriilion
lillecl
C'oncenlmlion''
Reference
Amphipod
(1-11 days old),
Hyalella azteca
Sodium
selenate
18
(S04=3.4)
10 days
LC50
(fed)
43
Borgmann et al.
2005
Amphipod
(1-11 days old),
Hyalella azteca
Sodium
selenate
124
(S04=32)
10 days
LC50
(fed)
371
Borgmann et al.
2005
Midge (first instar),
Chironomus riparius
Sodium
selenate
134
48 h
LC50
16,200
Ingersoll et al.
1990
Midge (first instar),
Chironomus riparius
Sodium
selenate
40-48
48 h
LC50
10,500
Ingersoll et al.
1990
Rainbow trout
(embryo, larva),
Oncorhynchus mykiss
Sodium
selenate
104
(92-110)
28 days
EC50
(death and
deformity)
5,000
(4,180)
(5,170)
Birge 1978; Birge
and Black 1977;
Birge et al. 1980
Goldfish
(embryo, larva),
Carrassius auratus
Sodium
selenate
195
7 days
EC50
(death and
deformity)
8,780
Birge 1978
Goldfish,
Carassius auratus
Sodium
selenate
-
24 hr
BCF = 1.42
BCF = 1.15
BCF = 1.47
BCF = 0.88
BCF = 1.54
0.45
0.9
1.35
2.25
4.5
Sharma and Davis
1980
Fathead minnow,
Pimephales promelas
Sodium
selenate
337.9
48 days
LC50
2,000
Adams 1976
Fathead minnow,
Pimephales promelas
Sodium
selenate
338
48 days
LC50
1,100
Adams 1976
Fathead minnow,
Pimephales promelas
-
51
30 min
No avoidance
11,200
Watenpaugh and
Beitinger 1985a
Fathead minnow,
Pimephales promelas
-
-
24 hr
LC50
82,000
Watenpaugh and
Beitinger 1985b
Fathead minnow,
Pimephales promelas
-
-
24 hr
Reduced
thermal
tolerance
22,200
Watenpaugh and
Beitinger 1985c
Fathead minnow,
Pimephales promelas
Sodium
selenate
44-49
7 days
Chronic value
- growth
Chronic
value-growth
Chronic
value-survival
1,739
561
2,000
Norberg-King
1989
Fathead minnow,
Pimephales promelas
Sodium
selenate
160-180
24 hr
No effect on
reproductive
behavior
36,000
Pyron and
Beitinger 1989
Fathead minnow,
Pimephales promelas
Sodium
selenate
160-180
24 hr
Edema in
larvae
produced
from adults
exposed to
Selenium VI
20,000
Pyron and
Beitinger 1989
E-8
-------
Species
C'lieiniciil
1 hirilness
(111l»/l- ilS
C :¦( ().i)
Diiriilion
lillecl
C'oncenlmlion''
Reference
Channel catfish
(embryo, fry),
Ictalurus punctatus
Sodium
selenate
90
8.5-9 days
Induced
albinism
-
Westerman and
Birge 1978
Narrow-mouthed toad
(embryo, larva),
Gastrophryne
carolinensis
Sodium
selenate
195
7 days
EC50
(death and
deformity)
90
Birge 1978; Birge
and Black 1977;
Birge et al. 1979a
Organo-selenium
Bluegill (juvenile),
Lepomis macrochirus
Seleno-L-
methionine
16
323 days
MATC larval
survival
(dietary only
exposure)
20.83
(ig Se/g dw
(food)
Woock et al. 1987
Bluegill (juvenile),
Lepomis macrochirus
Seleno-L-
methionine
283
90 days
EC20 survival
(dietary only
exposure)
>13.4
f-ig/g dw
(food)
Cleveland et al.
1993
Bluegill
(2 yr and adult),
Lepomis macrochirus
Selenium
-
field
NOEC
deformities
53.83
(ig Se/g dw
(liver)
Reash et al. 1999
Bluegill
(2 yr and adult),
Lepomis macrochirus
Selenium
-
field
NOEC
deformities
23.38
(ig Se/g dw
(ovaries)
Reashetal. 1999
Redear sunfish (adult),
Lepomis microlophus
Selenium
-
field
LOEC
Adverse
histopathologi
cal alterations
<38.15
(ig Se/g dw
Sorensen 1988
Selenium Mixtures
Phytoplankton,
Mixed population
Selenium
-
field
Reduced
growth rates
18
Riedel et al. 1991
Cladoceran (<24 hr),
Daphnia magna
Selenite-
Selenate
mixture
138
21 days
MATC
growth
115.2
(ig Se/L
Ingersoll et al.
1990
Cladoceran (<24 hr),
Daphnia magna
Selenite-
Selenate
mixture
138
21 days
MATC
productivity
21.59 jxg/g dw
(whole-body)
Ingersoll et al.
1990
Midge (<24-hr),
Chironomus riparius
Selenite-
Selenate
mixture
138
30 days
MATC
emergence
503.6
Ingersoll et al.
1990
Bluegill (juvenile),
Lepomis macrochirus
Selenite-
Selenate
mixture
283
60 days
NOEC
survival
340
Cleveland et al.
1993
Bluegill (juvenile),
Lepomis macrochirus
Selenite-
Selenate
mixture
283
60 days
EC20 survival
4.07
Mg/g dw
(whole body)
Cleveland et al.
1993
E-9
-------
Species
(hemiciil
Snlinily
(ii/kii)
Diimtion
KITecl
('onccnli'iilion
(.uji/l.)'
Reference
SALTWATER SPECIES
Selenium (IV)
Anaerobic bacterium,
Methanococcus
vannielli
Sodium
selenite
-
llOhr
Stimulated
growth
79.01
Jones and
Stadtman 1977
Bacterium,
Vibrio fisheri
Sodium
selenite
-
5 min
50% decrease
in light output
(Microtox7)
68,420
Yuetal. 1997
Green alga,
Chlorella sp.
Sodium
selenite
32
14 days
5-12%
increase in
growth
10-10,000
Wheeler et al.
1982
Green alga,
Platymonas
subcordiformis
Sodium
selenite
32
14 days
23% increase
in growth
100-10,000
Wheeler et al.
1982
Green alga,
Dunaliella primolecta
Sodium
selenite
32
20 days
Increased
growth;
induced
glutathione
peroxidase
4,600
Gennity et al.
1985a,b
Diatom,
Skeletonema costatum
Selenium
dioxide
-
5 days
BCF = 18,000
BCF = 16,000
BCF = 10,000
0.06
0.79
3.6
Zhang et al. 1990
Diatom,
Chaetoceros muelleri
Selenium
dioxide
-
6 days
BCF =
337,000
BCF = 65,000
BCF = 5,000
0.06
0.79
3.6
Zhang et al. 1990
Diatom,
Phaeodactylum
tricornutum
Selenium
dioxide
-
8 days
BCF =
109,000
BCF = 27,000
BCF = 7,000
0.06
0.79
3.6
Zhang et al. 1990
Diatom,
Thallassiosira
aestivalis
Selenium
oxide
29-30
72 hr
No effect on
cell
morphology
78.96
Thomas et al.
1980a
Brown alga,
Fucus spiralis
Sodium
selenite
-
60 days
1355%
increase in
growth of
thalli
2.605
Fries 1982
Red alga,
Porphyridium
cruentum
Sodium
selenite
32
27 days
Increase
growth;
induced
glutathione
peroxidase
4,600
Gennity et al.
1985a,b
E-10
-------
Species
(hemiciil
Snlinily
(ii/kii)
Diimtion
KITecl
('onccnli'iilion
(.uji/l.)'
Reference
Selenium (VI)
Bacterium,
Vibrio fisheri
Sodium
selenate
50% decrease
"
15 min
in light output
(Microtox7)
3,129,288
Yuetal. 1997
Green alga,
Chlorella sp.
Sodium
selenate
32
14 days
No effect on
rate of cell
10-1,000
Wheeler et al.
1982
Green alga,
Chlorella sp.
Sodium
selenate
32
4-5 days
100%
mortality
10,000
Wheeler et al.
1982
No effect on
Green alga,
Dunaliella primolecta
Sodium
selenate
32
14 days
rate of cell
population
growth
10-100
Wheeler et al.
1982
71% reduction
Green alga,
Sodium
32
14 days
in rate of cell
1,000
Wheeler et al.
Dunaliella primolecta
selenate
population
growth
1982
Green alga,
Dunaliella primolecta
Sodium
selenate
32
4-5 days
100%
mortality
10,000
Wheeler et al.
1982
Green alga,
Platymonas
subcordiformis
Sodium
selenate
32
14 days
No effect on
rate of cell
population
growth
10
Wheeler et al.
1982
Green alga,
Platymonas
subcordiformis
Sodium
selenate
32
14 days
16% decrease
in rate of cell
population
growth
100
Wheeler et al.
1982
Green alga,
Platymonas
subcordiformis
Sodium
selenate
32
14 days
50% decrease
in rate of cell
population
growth
1,000
Wheeler et al.
1982
Green alga,
Platymonas
subcordiformis
Sodium
selenate
32
4-5 days
100%
mortality
10,000
Wheeler et al.
1982
Brown alga,
Fucus spiralis
Sodium
selenate
-
60 days
160% increase
in growth rate
of thalli
2.605
Fries 1982
23-35%
Red alga,
Porphridium cruentum
Sodium
selenate
32
14 days
reduction in
rate of cell
population
growth
10-1,000
Wheeler et al.
1982
Red alga,
Porphyridium
cruentum
Sodium
selenate
32
4-5 days
100%
mortality
10,000
Wheeler et al.
1982
E-ll
-------
Species
(hemiciil
Snlinily
(g/kg)
Diimtion
KITecl
(onccnlmlion
(.uji/l.)'
Reference
Eastern oyster (adult),
Crassostrea virginica
Sodium
selenate
34
14 days
No significant
effect on
respiration
rate of gill
tissue
400
Fowler etal. 1981
Striped bass (embryo),
Morone saxatilis
Sodium
selenate
7.2-7.5
4 days
93%
successful
hatch and
survive
200,000
Klauda 1985a,b
Striped bass (larva),
Morone saxatilis
Sodium
selenate
4.0-5.0
4 days
LC50 (control
survival=
77%)
13,020
Klauda 1985a,b
Striped bass (juvenile),
Morone saxatilis
Sodium
selenate
3.5-5.5
9-65 days
Significant
incidence of
development
anomalies of
lower jaw
39-1,360
Klauda 1985a,b
Striped bass (juvenile),
Morone saxatilis
Sodium
selenate
3.5-5.5
45 days
Significant
incidence of
severe blood
cytopathology
1,290
Klauda 1985a,b
a Concentration of selenium, not the chemica
. Units are |_ig selenium/L of water unless noted ot
lerwise.
b Converted from dry weight to wet weight basis (see Guidelines).
c Growth of algae was inhibited.
d From Smith et al. (1976).
e Calculated from the published data using probit analysis and allowing for 8.9% spontaneous mortality.
E-12
-------
3.0 Other Data - Endangered Species
Two similar studies were conducted in 1996 and 1997 to determine effects of site water and site
food, both contaminated with selenium, on the endangered species, razorback sucker, Xyrauchen texanus
(Hamilton et al. 2001 a,b; published later in a peer-reviewed journal in 2005, see Hamilton et al. 2005
a,b,c). Both studies show marked effects of selenium on survival of razorback sucker larvae exposed to
contaminated food and to a lesser extent, contaminated water. Although the data convincingly
demonstrate effects to larval survival from exposure to contaminated food, interpretation of the results in
the context of chronic criterion derivation is complex because of inconsistencies between: 1) levels of
selenium in the food and larvae relative to larval survival; 2) the time to larval mortality relative to
selenium in the diet and selenium in the larvae; and 3) levels of other inorganic contaminants in food and
water (possible organic contaminants were not measured). A summary of each of these two studies is
presented below.
Evaluation of Contaminant Impacts on Razorback Sucker held in Flooded Bottomland Sites Near Grand
Junction , Colorado - 1996 (Hamilton et al. 2001a; also Hamilton et al. 2005 a,b,c)
This study was initiated with 5-day old razorback sucker larvae spawned from adults (first time
spawners) which were previously held (9 months) in three different locations along the Colorado River
that contained varying levels of selenium: Horsethief (the designated reference site which receives water
pumped directly from the Colorado River near Fruita, CO, and where dissolved selenium concentrations
in water ranged from <1.6 to 3.9 (ig/L during the period of exposure), Adobe Creek (low level selenium
contamination - dissolved selenium concentrations in water ranged from 1.5 to 11.6 (ig/L; avg. = 3.8
(ig/L), and North Pond (high level selenium contamination - dissolved selenium concentrations in water
ranged from 3.8 to 19.6 (ig/L; avg. = 9.5 j^ig/L). The selenium content in eggs from three Horsethief
females ranged from 5.8 to 6.6 mg Se/kg dw, and the selenium content in adult muscle plugs at spawning
was from 3.4 to 5.0 mg Se/kg dw. The selenium content in the eggs from three Adobe Creek females
ranged from 38.0 to 54.5 mg Se/kg dw, and the selenium content in adult muscle plugs at spawning was
from 11.5 to 12.9 mg Se/kg dw. The selenium content in the eggs from three North Pond females ranged
from 34.3 to 37.2 mg Se/kg dw, and the selenium content in adult muscle plugs at spawning was from
14.1 to 17.3 mg Se/kg dw. The selenium content in eggs from one of three hatchery brood stock females
was 7.1 mg Se/kg dw, and the selenium content in muscle plugs of two of three hatchery brood stock
females at spawning ranged from 2.6 to 13.8 mg Se/kg dw. The razorback sucker larvae spawned from
fish hatchery brood stock (older, previously spawned females) and held in Colorado River (Horsethief)
water were used as an additional reference group of test fish.
E-13
-------
The experimental groups were subdivided into those receiving reference water (hatchery water;
24-Road Fish Hatchery) or site water (Table E-2). They were further subdivided into those receiving a
daily ration of reference food (brine shrimp) or zooplankton (predominantly cladocerans and copepods)
collected from each site where their parents were exposed for the previous 9 months. A total of 60 larvae
from each of the four adult sources (Horsethief, Adobe Creek, North Pond, Brood Stock held in different
ponds at Horsethief) were exposed to each treatment (2 replicates x 3 spawns x 10 fish/beaker). The
larvae were held in beakers containing 800 ml of test water. Fifty percent of the test water was renewed
daily.
Table E-2. Treatment conditions during the 30-day larval study.
Source of l.anae
Trcalmcnls
Se in food
ilw)
Dissohed Se in
waler
(MJi/U
Horsethief Adults
Reference food: Reference
water
2.7
< 1.6
Reference food: Site water
2.7
0.9
Site food: Reference water
5.6
< 1.6
Site food: Site water
5.6
0.9
Adobe Creek Adults
Reference food: Reference
water
2.7
< 1.6
Reference food: Site water
2.7
5.5
Site food: Reference water
20
< 1.6
Site food: Site water
20
5.5
North Pond Adults
Reference food: Reference
water
2.7
< 1.6
Reference food: Site water
2.7
10.7
Site food: Reference water
39
<1.6
Site food: Site water
39
10.7
Hatchery raised Adults
Reference food: Reference
water
2.7
< 1.6
Reference food: Site water
2.7
0.9
Site food: Reference water
5.6
< 1.6
Site food: Site water
5.6
0.9
Growth, survival and development were evaluated amongst treatment groups for up to 30 days in
the treatment conditions. Each treatment group was fed once daily after renewal. Test waters were
collected every day from each site as grab samples for the renewal. A small portion of this water was
retained at 3- and 7-day intervals for an analysis of total and dissolved selenium concentrations. At
approximately 2-day intervals, aquatic invertebrates and brine shrimp not used for feeding were sieved
from the media for selenium analysis. The number of live fish was recorded daily. After the 30-day
exposure period, the surviving fish were sacrificed and measured for total length. At this same time,
E-14
-------
approximately four fish from each treatment, when available, were collected as a composite sample and
analyzed for total selenium.
After 30 days of exposure in the reference food-reference water treatment, survival of razorback
sucker larvae from brood stock and Horsethief adults (89 and 87 percent, respectively) was slightly higher
than those from Adobe Creek adults (84 percent) and North Pond adults (75 percent). Corresponding
selenium concentrations in larval whole-body tissue were 3.6, 3.3, 7.7 and 9.7 mg Se/kg dw, respectively.
Survival was similar or slightly reduced in larvae from all four sources after 30 days of exposure in the
reference food-site water treatments; corresponding selenium concentrations in larval whole-body tissue
were 5.2, 5.1, 12.7 and 15.2 mg Se/kg dw, respectively. In contrast, none of the larvae spawned from
parents from Horsethief, Adobe Creek, or North Pond survived to 30 days when fed zooplankton
collected from the three sites, irrespective of the water type they were exposed to (i.e., reference or site).
Only the larvae from brood stock adults, which were fed zooplankton from the Horsethief site for this
treatment, survived, and even these larvae suffered substantial mortality (40 and 60 percent respectively).
The mean selenium concentrations in whole-body tissue of larvae from brood stock adults after the 30-
day exposures were 5.4 mg Se/kg dw (site food-reference water treatment) and 6.9 mg Se/kg dw (site
food-site water treatment).
Several inconsistencies were observed that indicate selenium may not be solely responsible for
the effect on larval survival. Larval survival in the Adobe Creek treatment group exposed to reference
water (<1.6 j^ig/L) and reference food (2.7 mg Se/kg dw) was 84 percent, similar to survival of larvae
from brood stock (89 percent). The selenium concentration in the larvae from this Adobe Creek treatment
group after 30 days was higher (7.7 mg/kg dw) than that of the brood stock fish (5.4 mg Se/kg dw) in the
reference water (<1.6 j^ig/L) and site food (5.6 mg Se/kg dw) treatment, which had a 30-day survival of 62
percent. Also, the time to 50 percent mortality between the site food treatments, where most mortality
occurred, was not related to selenium concentration in the diet or in the larvae.
Although the larvae from brood stock held at Horsethief and the larvae from the first-time
spawning adults held at Horsethief that were used for the 9 month exposure received the same site food,
no larvae from the latter group survived the 30 day exposure. Concentrations of selenium in the larvae of
these two treatment groups were essentially the same between days 6 and 12 of the exposure (8.1 to 8.9
mg Se/kg dw). During this same general time frame (6 to 7 days of exposure), larvae from Adobe Creek
and North Pond adults apparently tolerated up to 32 and 39 mg Se/kg dw in tissue, respectively, without
any increase in mortality when exposed to reference food and reference water. Larvae grown out under
hatchery conditions from adults in the Horsethief and Adobe Creek treatments also did not differ in total
deformities compared to larvae from brood stock. There was also no difference between treatments
(brood stock, Horsethief, Adobe Creek, and North pond) in percent egg viability, percent hatchability,
E-15
-------
percent embryos with deformities, and percent mortality of deformed embryos and larvae from a separate
test initiated with eggs in the same study (Hamilton et al. 2005b).
Evaluation of Contaminant Impacts on Razorback Sucker held in Flooded Bottomland Sites Near Grand
Junction , Colorado - 1997 (Hamilton et al. 2001b)
In a similar 30-day larval study conducted by the authors in the following year (1997), razorback
sucker larvae from a single hatchery brood stock female (11 mg Se/kg dw muscle) were subjected to the
sixteen different combined water and dietary exposure conditions described in the earlier (1996) study.
The female parent was held at Horsethief Canyon State Wildlife Area before spawning. The larvae were
held in beakers containing 800 ml of test water as before; fifty percent of the test water was renewed
daily. Specific treatment conditions for the 1997 30-day larval study are listed in Table E-3.
Table E-3. Treatment conditions during the 30-day larval study.
Water Treatments
Se in food
(m»/k» dw)
Se in water
(MS/I.)
Reference food (brine shrimp):
Reference water (24-Road Hatchery)
3.2
< 1
Reference food: Site water (Horsethief)
6.0
1.6
Reference food: Site water (Adobe Creek)
32.4
3.4
Reference food: Site water (North Pond)
52.5
13.3
Horsethief food: Reference water
3.2
< 1
Horsethief food: Site water (Horsethief)
6.0
1.6
Horsethief food: Site water (Adobe Creek)
32.4
3.4
Horsethief food: Site water (North Pond)
52.5
13.3
Adobe Creek food
Reference water
3.2
< 1
Adobe Creek food
Site water (Horsethief)
6.0
1.6
Adobe Creek food
Site water (Adobe Creek)
32.4
3.4
Adobe Creek food
Site water (North Pond)
52.5
13.3
North Pond food
Reference water
3.2
< 1
North Pond food
Site water (Horsethief)
6.0
1.6
North Pond food
Site water (Adobe Creek)
32.4
3.4
North Pond food
Site water (North Pond)
52.5
13.3
After 30 days of exposure in this study, there was also good survival of razorback sucker larvae
fed reference food (brine shrimp) and held in reference water or water from Horsethief (83 and 81
percent, respectively). The survival of these larvae was significantly greater than survival of larvae fed
brine shrimp and held in water from North Pond (52 percent). Corresponding selenium concentrations in
larval whole-body tissue after 10 days were 6.3, 6.7, and 11 mg Se/kg dw, respectively. The average
concentrations of selenium in the water for the three treatments were <1, 1.6, and 13.3 |_ig Se/L. After 30
E-16
-------
days the mean selenium concentrations in these larvae were 5.2, 5.2, and 16 mg Se/kg dw, respectively.
Survival was markedly reduced (0 to 30 percent survival) in the remaining treatments where larvae were
fed zooplankton from the various sites. Complete mortality was experienced by larvae exposed to
Horsethief food and reference water treatment after 30 days.
Similar to the previous study, several inconsistencies in results suggested that selenium may not
have been solely responsible for the effect on larval survival. The most notable inconsistency was that the
greatest effect on larval survival (percent survival or time to 50 percent mortality) was from exposure to
Horsethief food, the food with the lowest selenium contamination.
The authors of the above two studies (Hamilton et al. 200 la,b) make a strong argument that some
of the inconsistency in response observed in their studies between larvae fed reference and site diets may
be related to the difference in arsenic concentration between the two diets. The arsenic concentration
measured in the brine shrimp used in the reference diet was 24 mg total As/kg dw (measured in the
second larval study) versus between 6 and 7.5 mg total As/kg dw measured in the zooplankton from the
various sites. In their publication (Hamilton et al. 2005c), the authors cite several studies reporting an
ameliorating effect of arsenic against the toxicity of a variety of forms of selenium in various animals
(Dubois et al. 1940, Hoffman et al. 1992, Klug et al. 1949, Levander 1977, Moxon 1938, Thapar et al.
1969). In terms of the survival of larvae from Horsethief, Adobe Creek and North Pond adults when fed
the reference diet, the authors propose that the arsenic concentrations in the brine shrimp diet may have
resulted in an antagonistic interaction with selenium and reduced adverse effects in larvae. Such
hypothesis is questionable, because their studies included diets spiked with inorganic arsenic salts,
whereas the arsenic in brine shrimp (and other natural diets), is most likely predominantly organic arsenic
(US EPA 2003). Additionally, in a separate but related study by the same authors (Hamilton et al. 2005d),
larval razorback sucker spawned from one female at the Ouray Native Fish Facility were fed zooplankton
from six sites (SI, S3, S4, S5, SR, and NR) adjacent to the Green River, Utah at four different initial ages
(5, 10, 24, and 28 day old larvae) for 20 to 25 days. The selenium concentrations in zooplankton from the
SI reference site ranged from 2.3 to 3.5 mg Se/kg dw (dissolved Se in water <0.6 to <1.1 (.ig/L). The
concentrations in zooplankton from sites S3 and S4 were slightly higher (range 2.4 to 6.7 mg Se/kg dw;
water, 0.3-0.8 (ig/L), substantially elevated at S5 (12- 26 mg Se/kg dw; water, 0.6-3.1 (.ig/L). and highest
at SR and NR (44-94 mg Se/kg dw; water, 14-107 j^ig/L). All larvae in the test initiated when they were 5
days old (study 1) died after 25 days of exposure. Median time to death was shortest in fish fed
zooplankton from the reference site (SI) and longest for SR and NR. Interestingly, the concentration of
arsenic measured in zooplankton collected from SI was 12 mg As/kg dw, half that of the brine shrimp
used in the above study (Hamilton et al. 2001b), which did not appear to antagonize the toxicity of the
E-17
-------
selenium in the diet in this test. In this and the previous two studies, additional inorganic contaminants
such as vanadium and strontium were elevated in the zooplankton fed to the larval razorback sucker.
E-18
-------
De Riu, D., L. Jang-Won, Huang, S., Monielloa, G., and Hung, S. 2014. Effect of dietary
selenomethionine on growth performance, tissue burden, and histopathology in green and white sturgeon.
Aquat. Toxicol. 148:65-73.
Test Organisms: Green sturgeon (Acipenser medirostris)
White sturgeon (Acipenser transmontanus)
Exposure Route: Dietary only
Three different concentrations of L-selenomethionine were added to an artificial
diet mixture: nominal concentrations of 0 (control), 50, 100, and 200 mg
SeMet/kg (measured: 2.2 mg/kg Se in control diet (no added Se) and 19.7, 40.1
and 77.7 mg/kg Se in the three treatment diets).
8 weeks
Daily rations of the treatment diets (3% BW/d for first 4 weeks and 2% BW/d for
second 4 weeks) were fed to the juvenile sturgeon (approximately 30 g). Each of
the four dietary treatment consisted of 3 replicate 90 L tanks with 25 juveniles in
each tank. Several endpoints were monitored over the 8 week exposure period
including survival, percent body weight increase (% BWI), and hepatosomatic
index (HSI).
White sturgeon had no mortalities through the highest dietary treatment. Green
sturgeon juveniles had 0%, 7.7% and 23.1% mortality with the three dietary
treatments (see table below). %BWI had a greater response to selenium
concentration in juvenile tissues than HSI (see table below). Of note is the
relatively high concentration of Se in the whole body and muscle tissues of the
juvenile sturgeon in the control treatment (both species). The reason for the
relatively high Se control concentrations was not due to accumulation of Se from
the artificial diet because the concentration of Se remained relatively constant
over the 8 week exposure.
Chronic Value: TRAP analysis (threshold sigmoid nonlinear regression) of the green sturgeon
survival data resulted in a whole body ECi0 value of 28.93 mg/kg dw. ECi0
values were lower for % BWI and HSI using TRAP. For % BWI, the whole body
ECio value for green sturgeon was 16.36 mg/kg dw, and for white sturgeon,
23.94 mg/kg dw. For HSI, the whole body ECio value for green sturgeon was
10.86 mg/kg dw (with a very wide 95% confidence interval, 1.842-64.08 mg/kg
dw), and for white sturgeon there were no discernible effects.
Test Duration:
Study Design:
Effects Data:
E-19
-------
Selenium in Juvenile Sturgeon Tissues and Endpoints Measured at end of Eight Week Exposure
Green Sturgeon
Dietary [Se] mg/kg dw
whole body
[Se] mg/kg
dw
muscle [Se]
mg/kg dw
survival
%
%BWI
HIS
2.2 (control)
7.1
8.4
100
6.6
2
19.7
22.8
31.1
100
2.6
1.3
40.1
27.8
37
92.3
0.8
0.8
77.7
34.3
36.8
76.9
-1
0.9
White Sturgeon
Dietary [Se] mg/kg dw
whole body
[Se] mg/kg
dw
muscle [Se]
mg/kg dw
survival
%
%BWI
HIS
2.2 (control)
5.6
9.2
100
4.2
2.6
19.7
20.1
27
100
4.2
3.6
40.1
31.8
41.3
100
2.8
3
77.7
47.1
57.9
100
1
2.2
E-20
-------
4.0 Other Data - Chronic Studies with Fish Species
Some chronic studies met the requirements of an acceptable chronic test but were excluded from
being included in the data set used for criterion derivation for a variety of reasons. Summaries of these
studies are provided below.
E-21
-------
Vidal, D., S.M. Bay and D. Schlenk. 2005. Effects of dietary selenomethionine on larval rainbow trout
(Oncorhynchus mykiss). Arch. Environ. Contam. Toxicol.49:71-75.
Test Organism:
Exposure Route:
Test Duration:
Study Design:
Rainbow trout (Oncorhynchus mykiss)
Dietary only
Selenomethionine was added to dry fish food; the measured dietary
concentrations were 4.6, 12 and 18 p.g Se/g dw. The measured selenium in the
control diet was 0.23 (.ig Se/g dw.
90 days
Each of the three dietary treatments and control had 5 replicates, each replicate
contained 12 to 16 larval rainbow trout that were 27 days old at initiation. Each
fish was fed an average of 10 mg/d for 30 days; 25 mg/d on days 30-60; and 40
mg/d thereafter. Fish were sampled on days 30, 60 and 90 for length, weight,
selenium, hepatic GSH and thiobarbituric acid-reactive substances (TBARS)
measurements.
Effects Data: The authors reported significant decreases in weight and length after the 90-day
exposure (Table E-4). There were no significant differences in the hepatic lipid
peroxidation and hepatic GSH to GSSH ratios among the treatments. The authors
found significant differences in weight and length in the 4.6 and 12 jj.g Se/g dw
dietary treatments, but not the 18 jj.g Se/g dw treatment. Based on larval trout
body burden, the authors reported an LOEC of 1.20 jj.g/g ww, the concentration
of Se in fish fed the 12 (.ig Se/g dw dietary treatment. The Se concentration in
larval rainbow trout associated with the lowest dietary treatment that showed
significant decreases in larval weight and length was 0.58 (.ig Se/g ww or 2.06 |_ig
Se/g dw based on 71.8% moisture in whole body rainbow trout (NCBP).
Chronic Value: The data from this study was not used to calculate a chronic value for selenium
due to several inconsistencies. The significant decreases in length and weight
observed in the two lowest concentrations were not observed in the highest
dietary treatment. The Se concentrations in the larval rainbow trout were
irregular with the 60-day concentrations being considerably higher than the 90-
day concentrations. The authors explain this observation to rapid growth in the
fish causing dilution of the Se body burden. However, the increase in fish weight
from 30 to 60 days was similar to the 60 to 90 day increase and the 60 day Se
concentrations increased from day 30. Also, the Se concentration in the control
fish went from below detection on day 0 to 0.46 jj.g/g ww on day 30; to 1.24 jj.g/g
ww on day 60; and to 0.31 jj.g/g ww on day 90. The 60-day measured Se in the
control fish (1.24 jj.g/g ww) was more than twice the concentration of Se in the
fish with lowest concentration showing effects (0.58 jj.g/g ww).
E-22
-------
Table E-4. Mean (SD) rainbow trout growth after four SeMet dietary treatments.
test day
Treatment,
f-ig/g dw
weight, g
fork length,
cm
[Se] whole body,
JJ.g/g WW
[Se] whole body,
jj.g/g dw**
0
control
0.37 (0.30)
3.14(0.41)
ND
ND
30
control
1.33 (0.92)
4.66 (0.41)
0.46 (0.20)
1.63
4.6
1.25 (0.21)
4.84 (0.29)
1.05 (0.77)
3.72
12
1.33 (0.30)
5.09 (0.46)
1.81 (1.04)
6.42
18
1.31 (0.37)
4.97 (0.50)
1.60 (0.93)
5.67
60
control
2.96 (0.92)
6.91 (0.56)
1.24 (0.54)
4.40
4.6
2.33 (0.63)
6.69 (0.67)
1.70 (0.72)
6.03
12
2.52 (0.38)
6.88 (0.35)
1.83 (0.94)
6.49
18
2.59 (0.24)
6.92 (0.24)
2.62(1.22)
9.29
90
control
5.17(1.09)
7.70 (0.33)
0.31 (0.20)
1.09
4.6
3.45 (0.35)*
6.93 (0.19)*
0.58 (0.21)
2.06
12
3.45 (0.35)*
6.84 (0.68)*
1.20 (0.21)*
4.25
18
3.82 (0.62)
7.37 (0.62)
1.41 (0.27)*
5.00
* Significant
y different than the control.
** ww converted to dw using 71.8% moisture for whole body rainbow trout (NCBP).
E-23
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Pilgrim, N. 2009. Multigenerational Effects of Selenium in Rainbow Trout, Brook Trout, and Cutthroat
Trout. Master's Thesis. University of Lethbridge.
Test Organisms:
Exposure Route:
Test Duration:
Rainbow trout (Oncorhynchus mykiss), cutthroat trout (Oncorhynchus clarkii)
and brook trout (Salvelinus fontinalis)
Dietary only
Selenomethionine added to trout chow and gelatin. Two dietary treatment levels,
nominal Se concentrations, 15 (low) and 40 (high) mg/kg.
Rainbow trout were fed the experimental diets from August - December 2009,
brook trout July - November 2010, and cutthroat trout December 2010 - April
2011.
Study Design: Fish were obtained from a fish hatchery brood stock. Mature females and were
fed the experimental diets in 710 L tanks. Spawning was stimulated by injecting
Ovaprim® into the females. Eggs were fertilized and incubated at the fish
hatchery until the eye spots were visible. A portion of the eyed stage larvae from
each treatment was shipped to the University of Lethbridge Aquatic Research
Facility for the swim-up stage of the experiment conducted in gravel bed flumes.
Endpoints measured included percent survival in the first (spawned eggs to eyed
eggs) and second (eyed eggs to yolk-absorbed fry) stages of development, swim-
up success, and malformations (spinal, craniofacial and finfold deformities and
edema).
Effects Data: Selenium affected larval survival, swim-up success and the percent of
malformations in larvae in one or more of the three species tested (see table
below). Visual inspection of plots of the replicate data in Pilgrim (2009) showed
considerable variation between the endpoints and selenium in eggs. The
distribution of selenium among the tissues was markedly inconsistent with other
studies that have used these species. For example, the amount of selenium in the
eggs was 8 and 18 times greater than the concentration in the respective muscle
tissues in cutthroat and rainbow trout. Median ratios (egg Se:muscle Se)
calculated for rainbow trout (Casey and Siwik 2000; Holm et al. 2005) and
cutthroat trout (Golder 2005; Kennedy et al. 2000; Rudolph et al. 2007) were 1.9
and 1.8, respectively. Due to the considerable variation in the concentration
response of the replicate data and anomalous selenium distribution, these data
were not included in the data set to derive the criterion.
E-24
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Table E-5. Mean selenium concentrations in the diet and selected tissues and selected endpoints
measured in rainbow trout (RN), brook trout (BK) and cutthroat trout (CT).
Adapted from Table 3.1 in Pilgrim (2009).
Tissue, mg/kg ww
Surviva
,%
Swim-up success
Total
malformations,
%
Species
Diet ww
Muscle
Liver
Egg
Stage 1
Stage 2
RBT
1.47
0.21
3.77
1.17
82.36
61.56
57.18
10
12.7
0.51
6.53
4.30
77.86
48.64
73.83
9.86
35.2
0.74
17.21
13.0
54.72
30.33
27.45
29.63
BK
1.47
0.23
0.72
0.81
86.3
82.68
84
21.3
12.7
1.14
7.23
5.01
71.37
88.72
83.42
23.93
35.2
3.41
20.4
8.15
71.37
44.63
50.11
24.23
CT
1.47
0.31
1.00
2.02
61.41
61.87
55.3
6.13
12.7
0.93
6.00
9.80
30.65
14.75
21.71
48.06
35.2
2.05
14.4
18.0
21.99
0
0.08
NA
E-25
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Formation Environmental. 2012. Appendix E - Yellowstone Cutthroat Trout Adult Laboratory
Reproduction Studies. Technical Support Document: Proposed Site-Specific Selenium Criterion, Sage
and Crow Creeks, Idaho. Prepared for J.R. Simplot Company. January 2012.
Test Organism: Yellowstone cutthroat trout (Oncorhynchus clarkii bouvieri)
Exposure Route: Field collected. Adult female and male Yellowstone cutthroat trout were
collected at five field sites from four streams near the Smokey Canyon mine. In
addition Yellowstone cutthroat trout eggs were obtained from a hatchery as
method controls.
Test Duration: Test duration was from hatch through 15 days post swim up, and averaged 55-56
days for larvae hatched from field collected fish and 64 days for larvae hatched
from laboratory collected fish.
Study Design: Eggs were collected from 15 ripe females at five sites from four streams
upstream and downstream of the Smokey Canyon mine. This included one
selenium impacted stream downstream of the mine, Sage Creek (LSV), one site
along Crow Creek upstream of Sage Creek (CC-150) and one site along Crow
Creek downstream of Sage Creek (CC-350), and in sites within the reference
streams Deer Creek (DC), and South Fork Tincup Creek (SFTC). Eggs were
fertilized in the field with milt collected from males collected at the same site as
females. Fertilized eggs were water hardened at the site using stream water, then
placed in oxygenated plastic bags and stored on ice in the dark (cooler) for
transportation to laboratory. In addition, eggs were collected from 16 ripe
females obtained from Henry's Lake hatchery (HL) to serve as method controls.
Hatchery females were stripped of eggs and fertilized by milt from males
obtained from the same hatchery. For field and hatchery fish, Se was measured in
adult fish (whole body) and in eggs of field collected females.
A target of approximately 600 fertilized eggs from each female (were placed in
egg cups for hatching and monitoring. After swim up, remaining fry were thinned
to a target of 100 fry/treatment and monitored for an additional 15 day post swim
up feeding trial.
Endpoints measured in the laboratory were hatch, survival (hatch to swim up, and
hatch through 15 days post swim up), and deformities. Deformities were
combined as assessed as having at least one deformity, or being fully free of
deformities (i.e., normal).
Effects Data: Eggs failed to hatch for one of the field treatments (SFTC-1), and six of the
hatchery treatments, resulting in a final dataset of eggs fertilized from 14 field
collected fish and 10 hatchery fish. Se concentrations in eggs obtained from field
collected females ranged from 11.4 mg/kg in Deer Creek through 47.6 mg/kg in
Crow Creek downstream of Little Sage Creek (Table E-6). Se concentrations in
eggs obtained from Henry's Lake hatchery fish ranged from 0.83 mg/kg - 3.23
mg/kg (Table E-6). Se concentrations in whole body tissue samples obtained
from field collected females ranged from 8.17 mg/kg in Deer Creek through 25.7
mg/kg in Crow Creek downstream of Little Sage Creek (Table E-6). Se
concentrations in whole body tissue samples obtained from Henry's Lake
hatchery fish ranged from 0.23-0.91 mg/kg (Table E-6).
E-26
-------
Table E-6. Yellowstone cutthroat trout selenium concentrations, survival, and deformity data from
hatch to test end.
Sample IDa
Egg Se
mg/kg
WBb Se
mg/kg
# Free
From
Deformities
# Assessed
For
Deformities
# Died
# Survived
# Assessed +
# Died
CC-150/001
17.6
16.3
22
182
33
182
215
CC-350/001
27.9
20.7
14
138
120
138
258
CC-350/002
29.7
19.4
143
602
83
602
685
CC-350/003
22.3
17.0
73
330
36
330
366
CC-350/004
14.6
16.7
149
480
19
480
499
CC-350/005
47.6
25.7
91
392
71
392
463
DC/001
22
8.17
95
275
30
275
305
DC/002
15.4
9.07
133
465
26
465
491
DC/003
11.4
8.63
59
380
39
380
419
DC/004
12.7
16.6
7
38
23
38
61
HL/002
2.03
0.45
5
39
10
39
49
HL/003
2.48
0.44
121
302
19
302
321
HL/004
1.36
0.36
154
416
20
416
436
HL/006
0.83
0.36
21
244
103
244
347
HL/007
2.26
0.44
120
404
18
404
422
HL/008
1.87
0.28
147
412
37
412
449
HL/011
3.23
0.31
69
296
22
296
318
HL/012
1.58
0.23
112
454
27
454
481
HL/013
1.93
0.72
148
483
24
483
507
HL/015
2.06
0.91
0
36
6
36
42
LSV2C/001
40.1
19.4
2
200
536
0
536c
LSV2C/002
30.0
21.0
40
319
105
319
424
LSV2C/003
35.6
18.6
92
487
138
487
625
LSV2C/004
30.5
22.5
107
476
75
476
551
a - CC - Crow Creek; DC - Deer Creek; LSV2C - Sage Creek; HL - Henry's Lake (Hatchery)
b - whole body
c - does not include the 200 fish assessed that were dead prior to assessment, as all fish for that treatment
died during the swim up stage in this sample.
Figure E-l is a plot of % free from deformities versus egg concentration. The
previous draft used TRAP to estimate an effect level for these data but after
further review it was concluded these data just do not demonstrate any clear
effect of Se and therefore inappropriate for analysis by TRAP. There is no
obvious trend, especially one that is substantial relative to the data variability.
The correlation coefficient for these data is not significant and a t-test of the two
data clusters is likewise not significant. The survival data also do not show a
useful trend, especially one suitable for EC 10 estimation. Although no effect
concentration was determined for this test, the data do not contradict the other
cutthroat trout datasets in that there are no effects up to 30 mg/kg and of the three
points in excess of 30 mg/kg, one did show 100% mortality. The data are
consistent with Oncorhynchus not being one of the four most sensitive genera.
E-27
-------
so n
(/) 40 ¦
Q
E
o
M—
-------
Deng, X. 2005. Early life stages of Sacramento splittail (Pogonichthys macrolepidotus) and selenium
toxicity to splittail embryos, juveniles and adults. Doctoral dissertation, University of California, Davis.
Test Organism: Sacramento splittail (Pogonichthys macrolepidotus)
Exposure Route: Dietary only
Four concentrations of selenium in the fish diet (0.6, 17.3, 33.0, and 70.1 mg/g)
were created by mixing different proportions of selenized and Torula yeast. A
different batch of selenized yeast was used in the adult exposure.
Test duration: 24 weeks
Study Design: Fourteen adult fishes were placed in each circular tank (92 cm diameter, 33 cm
height) and fed one of the four diets. Each diet was provided to fishes in three
tanks. The twelve tanks were arranged in three rows. Each row had all four
treatment concentrations with randomly assigned positions. Thus, the experiment
had a randomized block design. Adult splittail fishes were obtained from the
Tracy Pump Station (U.S. Bureau of Reclamation, Tracy, CA). After 12 and 24
weeks of exposure, blood samples were collected, the liver, gonad, kidney and
white muscle were dissected, and liver and gonad were weighed to calculate
hepatosomatic and gonadosomatic indices. Stages of ovarian and testicular
development were determined from histological studies.
Effects Data: No mortality occurred throughout the experiment. Fish in control, 17.3, and 33.0
mg/g treatments exhibited normal behavior. Fish exposed to 70.1 mg/g in did not
consume as much food as fishes exposed to lower selenium concentrations, and
displayed abnormal behaviors. Splittail adults were less sensitive to dietary
selenium than juveniles. Relative to control, no changes in body weight, total
length, GSI, and condition factor were observed in fishes exposed to selenium
concentrations in food up to 33 mg/g. In general, tissue concentrations in fishes
exposed to selenium were higher than in the control, but differences in selenium
concentrations among them were often small and not significant (Table E-7).
Percentages of ovaries with atretic follicles increased with higher concentrations
of selenium in their diet: 30% in control, 45.5% in the 17.3 mg Se/g, and 100% in
the 33.0, and 70.1 mg/g treatments. The average concentration of selenium in
ovaries of fish exposed to 17.3 mg/g in their diet was 6.5 mg/g. This low effect
level, though, is disputable because of the very low number of ovaries analyzed,
the occurrence of atresia in 30% of ovaries in control, and the lack of significant
differences in concentrations of selenium in ovaries among treatments exposed to
elevated levels of this element.
Table E-7. Mean concentration of selenium in ovaries (SE).*
Diet Concentration (mg Se/g)
0.6
17.3
33.0
70.1
[Se] in ovary (mg/g dw)
4.4
(0.57)
6.5
(1.0)
8.3
(0.14)
8.9
(0.46)
* Values estimated from Figure 4 in Deng (2005) (pg. 11
0
E-29
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de Rosemond, K. Liber and A. Rosaasen. 2005. Relationship between embryo selenium concentration
and early life stage development in white sucker. Bull. Environ. Contam. Toxicol. 74: 1134-1142.
Test Organism:
Exposure Route:
Test duration:
Study Design:
White Sucker (Catostomus commersoni)
Field collected.
In June, 2002, eggs were collected from 4 females from Island Lake (exposed
site); milt was obtained from 2 males. Island Lake is downstream from Cluff
Lake uranium mine located in northern Saskatchewan. Selenium concentrations
in Island lake range from 1 to 11 (.ig/L and in recent years have been typically 4-5
(.ig/L. No fish/eggs were collected from a reference site.
Through the end of yolk absorption by the larvae; 33 days post-fertilization.
Individual batches of eggs were fertilized in the field with milt and water-
hardened. Eggs were air transported to the laboratory in Saskatoon for testing.
200 eggs were randomly selected from each clutch and then separated into
groups of 100 which were placed into individual test chambers (n = 8).
On test day 30 (3 days prior to test termination), all fish larvae that exhibited
macroscopic deformities (e.g., kyphosis, lordosis, scoliosis and edema) were
removed, photographed and preserved. At test termination, (day 33), 40 larvae
from each female whites sucker were evaluated for deformities using a
microscope.
Effects Data: Although all four females were collected from the exposed site, selenium
concentrations in eggs were grouped into two low (Fish 2 and 3 in Table E-8)
and two high (Fish 1 and 4 in Table E-8). Larval mortality and developmental
deformities were not related to selenium concentrations in eggs (Table E-8). The
data suggest that embryo/larval effects are not observed at concentrations in eggs
reaching 40.3 mg/kg dw (geometric mean of the two high selenium
concentrations in eggs). However, because a reference condition with low
selenium exposure was not established, it is not appropriate to estimate an effect
concentration for this study. Note: the average percent moisture for the four
clutches of eggs was 92.6%.
Effect Concentration: NA
E-30
-------
Table E-8. Embryo/larval endpoints for eggs from four female white sucker collected from Island
Lake in June 2002.
Measurement
Fish 1
Fish 2
Fish 3
Fish 4
Successfully hatched larvae3
161
140
176
141
Deformed larvaeb
21
25
16
13
Dead larvaec
6
14
6
4
Macroscopic deformities, %
Embryologicald
6.8
6.4
5.7
1.4
Developmental6
6.2
11.4
3.4
7.8
Microscopic deformities, %
Developmental
7.5
5
2.5
7.5
Total developmental deformities, %8
13.7
16.4
5.9
15.3
[Se] eggs mg/kg wwh
2.7
0.7
0.6
3.2
[Se] eggs mg/kg dwh
33.6
9.4
8.4
48.3
a Initial number was 200 per fish
b Total number of deformed larvae throughout study; includes embryological and macroscopic
deformities
c Total number of larvae that died throughout study.
d Percent of curled deformities that appeared in embryonic fish; deformities were evident immediately
after embryos hatched.
e Percent of deformities that were designated developmental; deformities became evident as larvae grew
and absorbed yolk sac (after experimental day 15).
f Percent of microscopic developmental deformities that were evident in the 40 fish examined per
female white sucker.
8 The estimated percentage of offspring that had microscopic and macroscopic developmental
deformities combined.
h Selenium concentration measured in a subsample of embryos collected on test day 0.
E-31
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Ogle, R.S. and A.W. Knight. 1989. Effects of elevated foodborne selenium on growth and reproduction
of the fathead minnow (Pimephales promelas). Arch. Environ. Contam. Toxicol. 18:795-803.
Test Organism: Fathead minnows (Pimephales promelas; juvenile, 59 to 61 d old)
Exposure Route: Dietary only
Purified diet mix spiked with inorganic and organic selenium: 25 percent
selenate, 50 percent selenite, and 25 percent seleno-L-methionine, homogenized
in dextrin.
Test Treatments: Completely randomized block design (2 blocks); 4 replicates per block (n = 8
replicates total per treatment). Actual mean total selenium levels in each
exposure treatment were: 0.4 (control), 5.2, 10.2, 15.2, 20.3, and 29.5 mg/kg dw.
Fish used in the first randomized block (F2 generation fish) were progeny from F,
generation originally obtained from the Columbia National Fishery Research
Laboratory, some of which were used in an initial range-finding experiment. Fish
obtained from a commercial supplier were used in the second randomized block.
The prepared diet was extruded into 1.5 mm pellets which were air-blown dried
to 5 percent moisture content and crushed and sieved so that only particles
retained by an 11.8 mesh/cm sieve were used in the study. The amount of
selenium in water that leached from the food during the experiment averaged
only 0.8 |ag/L.
Test Duration: 105 days, F2 generation (block one) and commercial fish (block two);
14 days F3 generation
Study Design: Ten fish were randomly placed in each cell per block (n = 8x10, or 80 fish total
per treatment). Fish were fed twice daily at 6 percent body weight per day, with
wastes and uneaten food removed 30 min. after each feeding. Test tanks were
flushed with two tank volumes of fresh test water after each feeding (solution
renewal). Growth (as wet weight) was determined every two weeks by bulk
weighing, and one fish from two of the cells per treatment in a given block (n = 4
total per treatment) was removed for selenium (whole-body) analysis. After 105
days of exposure, a single male and female fish from each treatment replicate (n
= 4 breeding pairs per treatment in a given block, or 8 breeding pairs per
treatment total) were placed in 250 ml beakers and inspected for spawning
activity for 30 days following the first spawning event for that pair (each pair
being one replicate). Gonads and muscle tissue were dissected for selenium
analysis from these fish at the end of the 30 days spawning period. The spawning
substrates were inspected daily for eggs to determine fertility and viability.
Samples of not more than 50 eggs from each spawn were incubated in flowing,
aerated water and inspected for percent hatch determination. Ten larvae from
each incubated brood were transferred to separate glass test chambers and
maintained (48 h renewal; fed brine shrimp twice daily) for 14 days to determine
percent larval survival.
Effects Data: There was no effect of selenium on any of the reproductive parameters measured
at the dietary concentrations tested. Percent hatch and percent larval survival
were very high (>87.4 percent) and essentially equal for all of the treatments.
Growth of pre-spawning adults was affected by the selenium exposure (Table E-
9).
E-32
-------
Table E-9. Effects on fathead minnow growth after 98 days of exposure to dietary selenium.
Measured mean selenium in
diet, mg/kg dw
Whole-body selenium,
mg/kg dw
Mean fish weight,
g WW
0.4
1.76
1.30
5.2
2.78
1.24
10.2
3.42
1.20
15.2
5.40
1.21
20.3
6.58
1.09
29.5
7.46
0.94
Chronic Value: An EC value could not be calculated for these data because the data did not meet
the minimum requirements for analysis.
E-33
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GEI Consultants. 2008. Maternal Transfer of Selenium in Fathead Minnows, with Modeling of Ovary
Tissue to Whole Body Concentrations.
Test Organism: Fathead Minnow (Pimephalespromelas)
Exposure Route: Field collected.
Gravid adult fathead minnows were collected from creeks with a wide range of
surface water selenium concentrations near the city of Denver, CO during the
2006 summer breeding season.
Sites
Low selenium exposure:
• Sand Creek at Colfax. In 2002, aqueous selenium averaged 0.9 (ig/L.
Moderate to high selenium exposure:
• Sand Creek downstream of refinery
• East Tollgate Creek
• Mainstem Tollgate Creek
Control fish - no field exposure
• Laboratory-reared fish from Aquatic BioSystems
Test duration: Embryo-larval test was 48 hours post hatch.
Study Design: Field collected adult fish were either field dissected for selenium measurement in
paired tissues or transported live back to the laboratory in coolers with site water.
Fish were transported to the laboratory where mating pairs were bred in
individual chambers containing spawning substrates. Eggs were removed from
the spawning substrate and reared in a standard Falcon dish with lab water. Eggs
were screened under a dissecting microscope for viability. Dead eggs were
removed and numbers recorded on a datasheet. Three separate breeding
experiments were conducted.
Upon hatching, larvae were moved to standard bioassay cups containing lab
water and maintained in the laboratory incubator at 25°C. Larvae were
maintained via static conditions in exposure cups for 48 hours post-hatch without
food to ensure full absorption of the yolk sac before they were fixed in formalin.
Deformity assessment was performed on fixed embryos using a dissection
microscope. Test endpoints consisted of egg production, fertilization success,
mortality, and deformities (includes edema and skeletal, craniofacial and finfold
malformations). The authors used a graduated severity index (GSI) for
deformities in which larvae were scored 0 (normal), 1 (slight), 2 (moderate), and
3 (severe) based on the level of defect.
Effects Data: All fish successfully spawned except those collected from Sand Creek
downstream from the refinery. These fish had visible parasites and were only
used in the ovary-to-whole body selenium analysis. A suite of metal and
metalloids were measured in fish samples from each location. Fish collected from
East Tollgate Creek had higher concentrations of 9 of the 15 metals that were
E-34
-------
measured in fish from at least one site. Aluminum and iron showed the highest
difference with an approximate 10-fold increase in the East Tollgate Creek fish.
Only the first brood of each mating pair was used for the analysis because effects
appeared to be muted in subsequent broods. The lower response in the second
brood was thought to be due to clearing of selenium in the oocytes. There was
poor correlation between egg fertilization (R2 = 0.13) and embryo mortality (R2 =
0.18) data with whole body selenium concentrations in the adult fish (see Table
E-10 for summary data; see Table E-l 1 for individual brood data). Neither the
fraction of embryos surviving nor fertilization rate as a function of the
concentration of selenium in maternal fathead minnows was suitable for
estimating EC values. Although there were low survival and fertilization rates at
some higher selenium concentrations, these responses were quite varied and did
not follow a defined concentration-response relationship (Figure E-2).
Of the 9 broods from fish collected at the three exposed sites only one brood
(from East Tollgate Creek) had deformities greater than 10%. The fathead
minnow females that produced the brood with the greatest number of deformities
and highest GSI also had the second highest concentration of whole body
selenium, 46.4 mg/kg dw (Table E-12; Figures E-3 and E-4). Approximately half
of the larvae from this brood exhibited some sort of malformation. Similar to the
embryo parameters, EC values were not able to be estimated for any of the 4
malformation parameters.
The authors used probit analysis and TRAP to determine effect levels for each of
the embryonic and larval endpoints (Table E-13). Although there is an indication
of effect due to selenium exposure in both the embryonic and larval endpoints,
there is too much variation in the responses observed with the embryos and
insufficient response observed with the larvae to derive a reasonable estimate of
effect levels. Therefore, no effect level was determined for this study.
Effect Concentration: Unable to determine due to high variability or insufficient response.
E-3 5
-------
Table E-10. Mean fathead minnow first brood embryo and larval parameters and adult whole-body
(WB) selenium concentrations (dw) for each site (± 1SE); CON = control, SCC = Sand Creek at
Colfax Avenue bridge, TGC = Tollgate Creek, and ETC = East Tollgate Creek.
Parameter
Site
Con
SCC
TGC
ETC
n (number of breeding pairs)
10
3
3
4
WB Se concentration (mg/kg dw)
2.86 ± 0.18
9.17 ±0.46
35.87 ±3.73
44.53 ±2.41
Egg fertilization (%)
84.75 ±3.32
23.99 ±22.45
63.42 ±31.82
59.6 ±22.26
Embryo mortality (%)
22.03 ± 3.34
89.04 ± 9.70
46.40 ±26.86
50.76 ±23.63
Mean spawn size (# of eggs per spawn)
129 ±23
318 ± 63
162 ±61
317± 158
Total larva evaluated (total # of broods)
957
89
281
254
Mean brood GSI score
4.85 ± 1.22
8.88 ± 8.88
14.88 ±4.63
21.75 ±9.53
Larval craniofacial defects (%)
2.64 ±0.90
4.65 ±4.65
6.26 ±3.63
18.48 ± 13.84
Larval skeletal defects (%)
4.74 ±0.89
9.30 ±9.30
6.21 ± 1.48
19.62 ± 12.11
Larval finfold defects (%)
2.19 ±0.78
4.07 ±4.07
5.71 ±3.08
17.23 ± 14.48
Larval edema (%)
3.89 ± 1.01
5.23 ±5.23
6.26 ±3.63
20.32 ± 12.93
Larval length (mm)
4.90 ±0.05
4.97 ±0.12
4.83 ±0.14
4.90 ±0.07
Table E-ll. Fathead minnow first brood embryo parameters and adult whole-body (WB) selenium
concentrations (dw) for each site (± 1SE); for site acronyms see Table E-9.
Total eggs (total Fert. Rate ((Initial Egg
Maternal WB dead+total Survival Count - 1st day
Se Cone dw hatch+not fraction (total mortalities)/Initial Egg
Brood Code Treatment (mg/kg) hatched) dead/total eggs) Count)
T-la-1
CON
2.90
19
0.79
0.96
T-lf-1
CON
3.24
238
0.77
0.88
T-lf-1
CON
1.94
19
0.63
0.73
T-2a-l
CON
2.25
135
0.98
0.98
T-3a-l
CON
2.71
154
0.68
0.72
T-3b-l
CON
2.64
90
0.90
0.95
T-3d-l
CON
3.67
76
0.70
0.71
T-4d-l
CON
3.43
199
0.85
0.91
T-5d-l
CON
3.33
149
0.73
0.87
T-6d-l
CON
2.52
183
0.76
0.78
T-2b-l
SCC
9.92
395
0.00
0.00
T-4a-l
SCC
8.35
193
0.03
0.03
T-6a-l
SCC
9.25
340
0.30
0.69
T-2a-l
TGC
32.29
132
0.83
0.91
T-3a-l
TGC
43.33
79
0.00
0.00
T-4a-l
TGC
31.99
262
0.77
1.00
T-lf-1
ETC
39.76
141
0.52
0.70
E-36
-------
Total eggs (total Fert. Rate ((Initial Egg
Maternal WB dead+total Survival Count - 1st day
Se Cone dw hatch+not fraction (total mortalities)/Initial Egg
Brood Code Treatment (mg/kg) hatched) dead/total eggs) Count)
T-3b-1 ETC 47.47 208 088 092
T-5a-l ETC 46.37 634 0.07 0.17
Table E-12. Fathead minnow first brood larval malformations and adult whole-body (WB)
selenium concentrations (dw) for each site (± 1SE); CON = control, SCC = Sand Creek at Colfax
Avenue bridge, TGC = Tollgate Creek, and ETC = East Tollgate Creek. ^
Brood
Code
Treatmen
t
Maternal
WB Se
Cone dw
(mg/kg)
Total
Larvae
Spinal
Incidence
%larvae
w/o
spinal
deformity
%larvae
w/o
craniofacial
deformity
%larvae
w/o
finfold
deformity
%larvae
w/o edema
Total
GSI
Score
T-lf-1
CON
1.94
11
9
91
100
100
100
1
T-2a-l
CON
2.25
141
3
97
99
98
96
24
T-6d-l
CON
2.52
117
2
98
99
99
97
16
T-3b-l
CON
2.64
81
4
96
98
99
98
12
T-3a-l
CON
2.71
96
1
99
100
100
100
1
T-la-1
CON
2.90
14
7
93
93
93
93
10
T-lf-1
CON
3.24
189
8
92
98
98
94
53
T-5d-l
CON
3.33
95
4
96
97
99
98
20
T-4d-l
CON
3.43
164
3
97
98
99
96
28
T-3d-l
CON
3.67
49
6
94
92
94
90
29
T-4a-l
SCC
8.35
3
0
100
100
100
100
0
T-6a-l
SCC
9.25
86
19
81
91
92
90
71
T-4a-l
TGC
31.99
190
5
95
97
97
97
41
T-2a-l
TGC
32.29
91
8
92
90
91
90
78
T-lf-1
ETC
39.76
65
5
95
95
98
94
20
T-5a-l
ETC
46.37
39
44
56
54
54
54
152
T-3b-l
ETC
47.47
150
11
89
95
96
91
89
E-37
-------
Table E-13. Authors calculation and comparison of fathead minnow larval deformity ECio
estimates using probit analysis and TRAP.
Effect
Endpoint
Probit Results
TRAP Results
Probit Results
TRAP Results
WB [Se]
mg/kg,
dw (±SE)
WB [Se] mg/kg,
dw (95% CL)
Ovary [Se]
mg/kg,
dw (±SE)
Ovary [Se] mg/kg,
dw (95% CL)
Edema
EC10
39.48 ± 16.21
45.78
(40.95 -51.20)
52.99 ± 19.99
61.43
(55.04-68.55)
Finfold
EC10
68.55 ±27.26
48.31
(39.41 -59.21)
87.95 ±32.16
64.81
(53.01 -79.24)
Skeletal
EC10
27.80 ±9.53
46.08
(41.94 -50.62)
38.67 ± 12.32
61.82
(56.36-67.80)
Craniofacial
EC10
53.86 ± 18.77
47.41
(38.92 -57.76)
70.83 ±22.84
63.56
(52.37-77.16)
All
EC10
16.98 ±5.38
45.50
24.23 ±7.06
61.06
abnormalities
(41.10 -50.37)
(55.26-67.48)
All
EC10
21.35 ±6.45
45.69
30.32 ± 8.51
61.27
abnormalities
(41.10 -50.79)
(55.23 -67.97)
except edema
Figure E-2. The fraction total survival of embryos (top left), fraction of embryos successfully
fertilized (right), survival adjusted for fertilization (bottom) versus maternal whole
body selenium concentration. Bottom figure EC10=35.2 mg/kg Se dw WB.
> 0.8
re 0.80 -
* 0.60 -
5 0.4
0.40 -
Log (maternal whole body [Sel ug/g dw)
0.8 -
0.6
0.4
Log (maternal whole body Se |jg/g dw)
~ \ ~
0.5 1 1.5
Log (maternal whole body [Se] yiglg dw)
E-38
-------
Figure E-3. Percent 2-day post-hatch larvae without edema (A), finfold deformity (B), craniofacial
deformity (C), and spinal deformity (D) relative to maternal whole body selenium
concentration. EClOs: 61.4 - 64.8 mg/kg dw WB.
120
A
100 -
~
~
A
~v
~
~
~ ~
~
~
re
E
80 -
T3
0)
o
5
60 -
40 -
20 -
~
o -
i i i
1
0
0.5 1 1.5
2
Log (maternal whole body [Se] yiglg dw)
120
B
F
100 -
£
80 -
¦O
¦o
a
60 -
~
i<=
o
5
40 -
20 -
o -
i
1
0 0.5 1 1.5
2
Log (maternal whole body [Se] yiglg dw)
120 -
£-100 -
|
| 80-
¦O
re
o 60 -
£
o
| 40-
o
o
Jo 20 "
o -
0 0.5 1 1.5 2
Log (maternal whole body [Se] yiglg dw)
120 -
p 100-
E
£ 80 -
0)
¦a
1 60 -
'a.
(/>
o 40 -
55 20 -
0 -
0 0.5 1 1.5 2
Log (maternal whole body [Se] yiglg dw)
E-3 9
-------
Figure E-4. Percent 2-day post-hatch larvae Graduated Severity Index (GSI) relative to maternal
whole body selenium concentration
(D 60
0.00 10.00 20.00 30.00
Maternal whole body [Se] |jg/g dw)
40.00
50.00
E-40
-------
4.1 Evaluation of zebrafish (Danio rerio) and native cyprinid sensitivity to selenium
Overview:
Two new studies on zebrafish (Danio rerio), Thomas and Janz (2014), Thomas (2014), and
Penglase et al. (2014), were made available to EPA by David Janz, one of the external peer reviewers.
Thomas (2014) and Thomas and Janz (2014) were the original dissertation and peer reviewed paper,
respectively, of the same body of work. The apparent sensitivity of the zebrafish to selenium relative to
other species in the EPA selenium criteria document was the subject of several public commenters, as
well as Dr. Janz in the comments received by EPA.
EPA calculated an EC10 of 7.004 mg Se/kg egg dw, or approximately 3.5 mg/kg whole body)
from the Thomas (2014) and Thomas and Janz (2014) study. EPA was not able to calculate an EC10 from
Pengalese et al. (2014). The Thomas (2014) and Thomas and Janz (2014) study is summarized in the
following section (Part I). Penglase et al. (2014) is summarized in section 7.1.5 of the main document.
EPA noted that the concentration-response curves for both deformities and survival are
anomalously shallow, yielding EClOs far below that of any other sensitive species. The shallow slope
indicates partial effects across the range of test doses, with some individuals being very sensitive, and
others being less sensitive than other test species. A typical test signature of the nutritionally essential
element selenium is that above a particular concentration there is a precipitous increase in adverse effects,
with most test organisms affected within a narrow dose range. Additional issues discovered during the
analysis of available information in the literature and supplied by the investigator raised questions of test
quality that introduced uncertainty in the results reported. This uncertainty, and the fact that zebrafish
may not represent the sensitivity range for cyprinids native to the US (discussed in Part II), led to the
decision to include this study qualitatively in the effects characterization.
The paucity and relative insensitivity of the available data for cyprinids (fathead minnow EC 10 =
< 23.9 mg/kg dw; based on LOEC in ovary) relative to other fish families like centrarchids (sunfish), and
salmonids (trout and salmon) caused additional concern. This led EPA to investigate the field significance
of the zebrafish EC 10 (7.004 mg/kg egg) compared to what we know about cyprinid occurrence in
selenium impacted waters. The available studies with native cyprinids indicate that a variety of native
cyprinid genera (e.g. chubs, shiners, dace) have stable, diverse populations and are reproducing
successfully (based on length frequency data) in selenium impacted waters at whole body concentrations
far exceeding our proposed whole body criterion element of 8.0 mg/kg dw. Taken together, the available
studies (Hamilton et al. (1998), NAMC (2008), Presser (2013), USGS (2012)), indicate that native
cyprinids as a family are not expected to be overly sensitive to selenium when compared with other
families of freshwater fish. This is important because zebrafish are non-native, and have only been
recently discovered in U.S. waters due to accidental introduction.
E-41
-------
EPA believes there is significant uncertainty regarding the actual sensitivity to zebrafish, and
therefore proposes inclusion of the zebrafish studies in the effects characterization section, as well as
inclusion of a comprehensive analysis of the studies as well as the studies on sensitivity of selenium to
native cyprinids (below) in its own technical appendix, and issuing an FRN soliciting additional studies or
information on zebrafish, as well as native cyprinids.
E-42
-------
4.1.1 Part I. Chronic summary of Thomas (2014) and Thomas and Janz (2014)
Thomas, J.K. 2014. Effects of Dietary and in ovo Selenomethionine Exposure in Zebrafish (Danio
rerio). Dissertation. University of Saskatchewan, Saskatoon, Canada.
Thomas and Janz, D.M. 2014. In ovo exposure to selenomethionine via maternal transfer increases
developmental toxicities and impairs swim performance in F1 generation zebrafish (Danio rerio). Aquatic
Toxicol. 152:20-29.
Test Organism:
Exposure Route:
Test Treatments:
Test Duration:
Study Design:
Effects Data:
Zebrafish (Danio rerio)
Dietary only
Selenomethionine spiked into Nutrafin® basic flake food
Control diet (1.3 mg/kg Se dw) and three selenium-spiked diets (3.7, 9.6, and
26.6 mg/kg Se dw).
90 days
Adult zebrafish were fed a control diet (1.3 mg/kg Se dw) and three selenium-
spiked diets (3.7, 9.6, and 26.6 mg/kg Se dw) for 60 days, followed by an
additional 30-40 days with equal rations (2.5%) of control or SeMet-spiked diets
and clean chironomids. After 90 days of feeding exposure, adult fish from each
exposure group were bred 3-4 times and embryos were collected and used to
assess a number of different effects including larval survival and deformities.
Eggs from each treatment were pooled from which replicate samples were
collected for selenium measurement, larval survival and deformity assessment
The authors presented mortality and deformities in the F1 generation graphically
for days up to 6 days post fertilization (dpf). The bar graphics were initially
converted to numeric values using a length measuring tool in GIMP (GNU Image
Manipulation Program). EC 10 values for both mortality and deformities were
very low with deformities being slightly lower. Upon request, the authors
provided a table of the number of deformities in observed in 2-6 days post
fertilization (dpf) fish larvae for each replicate pool of eggs (Table E-14) (David
Janz, pers. comm.). TRAP analysis of these data produced a very low EC10 of
7.0 mg/kg egg Se dw. The concentration-response curve in Figure E-5 is
extremely shallow compared to similar tests on other species, such that the
apparent sensitivity of zebrafish relative to other species depends on what level
of effect is considered. A comparison of egg-ovary zebrafish concentration-
response curves for survival and deformities with well-founded concentration-
response curves for other species is presented in Figure E-6. The shallow survival
and deformity slopes for the zebrafish stand out as atypical for a selenium
response. Note the EC50 values for the zebrafish are very similar to the EC50
values for the majority of other fish species and the zebrafish EC90 is similar to
the EC90 of the least sensitive fish, Dolly Varden.
A GMCV based on this test has not been included in the Sensitivity Distribution
for several reasons. Although the deformity and survival EC50s are within the
range observed for a number of other species, the concentration-response curves
E-43
-------
for both deformities and survival are anomalously shallow, yielding EC 10s far
below that of any other sensitive species (Figure E-6). Furthermore, if the
concentration-response curves are log-symmetrical, as generally has been
assumed in estimating EC 10s, the projected EC90s for zebrafish would place it
among the least sensitive known species, indicating greater variability among
individuals within this one species than among individuals across the entire class
of other fishes represented in the figure. The implication of such a shallow
concentration-response curve is that this species has exceptional genetic diversity
with respect to selenium tolerance, such that populations could adapt to very high
or very low selenium concentrations. The field significance of its exceptionally
low EC 10 is thus uncertain. The low EC 10 might or might not have some
relationship to the selenium deficiency reported by Hook (2008) in substantial
portions of its home range in the Ganges and Brahmaputra basins in India and
Bangladesh.
An assessment of the relative sensitivity of cyprinids using both field and
laboratory data is provided in the following section (Part II).
E-14. Selenium concentrations in zebrafish eggs and t
eformities in 2-6 dpf larvae.
Se in eggs, mg.kg dw
Total
Deformed
% Deformity
1.67
35
0
0.00
1.27
63
5
7.94
1.08
40
2
5.00
5.99
44
6
13.64
7.45
45
3
6.67
6.80
36
4
11.11
12.26
37
11
29.73
10.46
39
13
33.33
15.51
48
18
37.50
38.98
30
21
70.00
36.44
65
40
61.54
26.81
88
41
46.59
E-44
-------
o
-t—»
CO
_£Z
-t—•
to
o
Q.
to
CO
T3
CD
CS
TO
E
i—
o
c
o
¦c
o
Q.
O
0.5 1.0
log (mg Se/kg egg dw)
Parameter Summary:
Parameter Initial
Final
Std. Error 95%LCL
95%UCL
LogX50 1.45
1.4421
0.0408
1.3632
1.5247
Standard Deviation 0.44
0.4421
0.0586
0.3514
0.5964
Y0 0.95
0.9503
0.0184
0.9
0.9799
Effect Concentration Summary:
% Effect ECx
95%LCL
95%UCL
90 65.15
45.28
93.73
50 27.79
23.08
33.47
20 11.12
8.647
14.29
10 7.004
4.884
10.04
5 5.053
3.208
7.958
Figure E-5. Tolerance distribution model (triangular distribution model shape) of the proportion of
normal zebrafish larvae (1-fraction with deformities) vs. the logarithm of concentration of selenium
in zebrafish eggs.
E-45
-------
BrnT-su
RBT-fc
1.3 1.5 1.7
log(mg Se/kg EO dw)
Figure E-6. Thomas and Janz (2014) zebrafish concentration-response curves for deformities and
survival, ZF-d and ZF-s, compared with representative concentration-response curves for other
species spanning the full range of EClOs.
BG-H: bluegill, Hermanutz et al. (1992, 1996); BrnT-su: brown trout survival to swim-up (Formation
2011); DV: Dolly Varden, Golder (2009; RBT-fc: rainbow trout facial-cranial deformities, Holm (2002)
and Holm et al. (2003, 2005); Sturg: sturgeon deformities, Linville (2006).
4.1.2 Part II - Evaluating Sensitivity of Cyprinids (Cyprinidae) to Selenium from Field and
Laboratory Data
Background:
The draft selenium criteria document is based on reproductive effects (mortality deformities) to
larval fish following maternal exposure. These chronic tests are based primarily on species from the
families salmonidae and centrarchidae. There is a paucity of data for a number of fish families used for
development of selenium criteria. This limitation in data is particularly notable for the family cyprinidae
("minnows"), because it is comprised of approximately 180 general and is one of the most diverse
families in North America. A recent toxicity test with zebrafish (Danio rerio), discussed above in Part 1,
indicated that some cyprinids may be markedly more sensitive to the effects of selenium than other fish
families for which toxicity data are available. This study was very different than all previous studies
E-46
-------
examining larval effects in that the slope was very shallow, whereas the slopes for all other species were
steep (see Figure E-6).
This analysis considers the results of the zebrafish laboratory survival study and several field
collection studies, which evaluated cyprinid abundance and diversity in watersheds impacted by selenium,
to compare the sensitivity of the zebrafish evaluated by Thomas (2014) and Thomas and Janz (2014) to
native cyprinid populations. Available water and whole body tissue selenium concentrations (>8.0 mg/kg
dw), were compared to the translated egg-ovary to whole body zebrafish EC 10 values (~ 3.5 mg/kg dw)
to evaluate the relative sensitivity of native cyprinids to the non-native zebrafish test outcome.
Executive Summary:
The occurrence and effect of selenium on native cyprinids were evaluated based on the results of
field studies conducted in four aquatic systems (CO, NC, UT, and WV) having elevated selenium
concentrations. The objective of this evaluation was to compare the sensitivity of native cyprinid
populations with the results of a recent toxicity test with zebrafish (Danio rerio) (Thomas (2014), Thomas
and Janz (2014)) that suggests some cyprinids may be markedly more sensitive to the effects of selenium
than other fish families for which toxicity data are available. The following set of analyses evaluated
studies of widely-distributed native cyprinid species occurring in waters impacted by selenium from
various sources and the relationships between whole body tissue levels, (and water concentrations where
available) and impacts from selenium via toxicity or population metrics.
Cyprinid genera representing many species native to the US were found to be present in waters
with selenium concentrations exceeding the current national criteria value (5fj.g/L). Cyprinid species
present in the four studies examined represent 169 of the approximately 180 species present (at the genus
level) in the United States. Abundance and diversity at sites impacted by selenium (water concentrations
>5.0 (ig/L) were found to be no different than at sites in the Arkansas River, Colorado with low selenium
concentrations (3.0-3.5 (ig/L) watershed, with the exception of one location where extremely high
selenium concentrations (Wildhorse Creek, CO; approximately 413 (ig Se/L) were detected.
Whole body tissue concentrations within several widely distributed cyprinid genera exceeded the
proposed whole body tissue element of 8.0 mg/kg dw and had sustainable reproducing populations, as
indicated by length frequency analysis and occurrence data for the four studies. When evaluated by itself,
the influence of selenium whole-body concentration in reducing family Cyprinidae densities was not
statistically significant (R2 = 0.02; p = 0.51). Rather, substrate characteristics of the waterbodies sampled
had the strongest influence. In contrast, when evaluated by itself, the influence of selenium whole-body
concentration in reducing family Centrarchidae densities was significant (R2 = 0.53; p = 0.02).
E-47
-------
In spite of the potential for confounding factors, GEI (2008) obtained parallel results at a different
location, Dixon Creek and Canadian River in Texas, affected by refiner effluent selenium. Again,
selenium whole-body selenium had no relationship to cyprinid density (R2 = 0.00) but was a significant
negative factor for centrarchid density (R2 = 0.41, p = 0.003). And in the Sand Creek Drainage, CO, GEI
found no negative association between fathead minnow densities and selenium concentrations of 3-26 mg
Se/kg whole-body dw and 8-45 mg Se/kg ovary dw.
These findings suggest that native cyprinids are less sensitive than centrarchids, and are thus
likely to be protected by a national criterion based heavily on centrarchid and salmonid sensitivity. Based
on these available data, native cyprinids appear to have a tolerance to selenium that is greater than
centrarchid and salmonid species, and much greater than indicated by the non-native zebrafish test
outcome. It is therefore expected that the proposed selenium criterion will be protective of native
cyprinids occurring throughout the United States.
Laboratory Exposures:
1. Chronic Toxicity and Hazard Assessment of an Inorganic Mixture Simulating Irrigation
Drainwater to Razorback Sucker and Bonvtail. Hamilton et al. (2000). USGS CERC Laboratory
Toxic effects from inorganics associated with irrigation activities, and possibly contributing to the
decline of endangered fish in the middle Green River, Utah were investigated. Two 90-day chronic
toxicity studies were conducted with two endangered fish, razorback sucker (Xyrauchen texanus) and
bonytail chub (Gila elegans). Swim-up larvae were exposed in a reconstituted water simulating the
middle Green River. The inorganic mixtures were tested at IX, 2X, 4X, 8X, and 16X the measured
environmental concentrations of the evaluated inorganic constituents (2 ug/L arsenic, 630 ug/L boron, 10
ug/L copper, 5 ug/L molybdenum, 51 ug/L selenate, 8 ug/L selenite, 33 mg/L uranium, 2 ug/L vanadium,
and 20 ug/L zinc).
Bonytail chub survival was 95% or greater at 30, 60, and 90 days except for the 16X treatment
(1232 ug/L Se), whereas growth was reduced after 30, 60, and 90 days at the 8X treatment (532 ug/L Se).
Swimming performance of bonytail chub was reduced after 90 days of exposure at the 8X treatment.
Whole-body residues of copper, selenium, and zinc increased in a concentration-response manner, but did
not increase at 90 days of exposure at the 8X treatment for most species tested, and at lower treatment
concentrations for the bonytail chub. Mean whole body selenium residues at the 8X treatment were 23.3,
16.7, and 9.4 mg/kg Se dw at 30, 60 and 90 days respectively. Hamilton et al. (2000) concluded that
adverse effects in bonytail chub were associated with whole-body concentrations of 9.4 to 10.8 mg/kg Se
dw in this study. One key uncertainty is the effect that the combination of toxic elements, in contrast to
selenium alone, had on outcomes measured in this study. However, basing the selenium toxicity
E-48
-------
evaluation on exposure to multiple contaminants is expected to provide a more conservative estimate of
effect on the bonytail chub (Gila elegans) than if selenium is tested alone.
Field Collection Studies
2. Selenium Tissue Thresholds: Tissue Selection Criteria, Threshold Development Endpoints, and
Potential to Predict Population or Community Effects in the Field. Part III: Field Application of
Tissue Thresholds: Potential to Predict Population or Community Effects in the Field. NAMC
Report (2008).
Field studies were conducted by GEI in the Arkansas River, CO mainstem and selected tributaries
between 2005 and 2006 to examine the relationship between selenium concentrations as well as habitat
characteristics in surface waters and cyprinid abundance and diversity in the Arkansas River. The data
collected for the study included:
1) Seasonal fish and macroinvertebrate (not shown) sampling to determine species composition
and the relative abundance of aquatic organisms);
2) Whole-body fish tissue, composite macroinvertebrate tissue (not shown), and water and
sediment (not presented) sample collection for the evaluation of Se concentrations in these
tissues and the evaluation of bioaccumulation pathways; and
3) Physical habitat measurements (not presented), to determine relationships between the
occurrence of biota and their physical environment. Data were collected from fall 2004 to fall
2006 from the Arkansas River, Fountain and Wildhorse Creeks, and the St. Charles River.
Total selenium (dissolved) was measured at 4 sites mainstem and 6 sites on three tributaries of the
Arkansas River watershed near Pueblo Colorado (Table E-15). Multiple site visits (6 to 17) to collect
water for selenium determination were conducted at the 10 sampling stations between 2005 and 2006.
Table E-15. Selenium water column data: Total Selenium (^ig/L, dissolved).
Site
Sampling Duration
2005-06
Sample
Size
Mean [Se]
(Hg/L)
Standard
Deviation
AR (Arkansas River)
AR1 (ARM) Mainstem, in
Pueblo below Whitlock WWTP
8 months
15
7.05
3.69
AR2 (ARE) Mainstem below
Pueblo WW Reclamation
Center and Fountain Creek
12 months
9
10.6
4.06
AR3 (ARB) Mainstem,
downstream of Pueblo
10 months
7
8.72
4.0
AR4 (ARN) Mainstem,
downstream of St. Charles
River
10 months
8
8.81
2.85
E-49
-------
Site
Sampling Duration
2005-06
Sample
Size
Mean [Se]
(ng/L)
Standard
Deviation
Arkansas River Tributaries
WHC (Wildhorse Creek)
6 months
17
418
115
FC (Fountain Creek)
FCP (Upstream)
12 months
9
3.43 (4.9)*
1.05
FC4 (Downstream)
6 months
12
12.1
4.34
SC (St. Charles River)
SCI (Upstream)
6 months
6
3.09 (4.8)*
1.37
SC2 (Mid-Point)
6 months
11
11.7
6.22
SC5 (Downstream)
8 months
13
20.3
13
* Maximum [Se] in FCP and SC
<5.0 ug/L, current selenium criterion
Summary of Selenium Concentrations in Water:
1) Total selenium concentrations exceeded the EPA chronic selenium standard of 5 |ig/L in
surface water samples collected from most locations, with only the upper reaches of the St.
Charles River and Fountain Creek having mean selenium concentrations below the EPA
chronic selenium standard.
2) Selenium concentrations in water samples from Wildhorse Creek were more than 20X greater
than in water samples collected from all other sample locations, with a mean selenium
concentration of418± 115 |ig/L.
3) The minimum concentration measured in water samples from Wildhorse Creek (315 |ig/L) was
approximately 7X greater than the maximum selenium concentration measured at other study
sites (43.6 |ig/L at St. Charles River, SC5).
Selenium in Fish Tissue:
Selenium concentrations in fish tissue (whole body) were measured for three representative
cyprinid species (central stoneroller, sand shiner, red shiner), one catostomid (white sucker), and three
centrarchids (green sunfish, smallmouth bass, and largemouth bass) (Table E-16).
E-50
-------
Table E-16. Mean fish tissue concentrations.
[Average whole
3ody mg/
eg dw estimated by eye from graphs in NAMC (2008)].
Sample Site
ARM
ARN
ARE
ARB
WHC
FCP
FC4
SCI
SC2
SC5
Mean water
[Se] ug/L
7.0
8.8
10.6
8.7
418
3.43
12.1
3.1
11.7
20.3
Cyprinids
Sand Shiner
10
10-21
25
10-17
15-21
Red Shiner
23
42
25
30
Central
Stoneroller
8
10-20
18-47
12
14
5
45
33
Centrarchids
Green Sunfish
12
30
Largemouth
Bass
11-15
14-36
22
26
40
Smallmouth
Bass
7
20
20
Catostomids
White sucker
8-11
10-24
16-18
14-21
32-33
6-10
24
6-14
47
Summary of selenium in fish tissue:
1) The mean concentrations in all cyprinids across all sites was 21.06 mg/kg dwt; SE = 1.38).
2) For comparison, the mean concentration in all centrarchids across all sites was 19.73 mg/kg
dw; SE = 1.32; and the mean concentration in white sucker (catostomids) across all sites was
17.52 mg/kg dw; SE = 1.52.
3) Most mean whole-body Se concentrations were well above the U.S. EPA (2014) proposed
chronic tissue criterion element for whole body of 8.13 mg/kg dry weight.
Comparison to national draft fish tissue criteria:
Given that these are waters known to be impacted by selenium there were only a few fish samples
(Tables E-17, E-18) that were at or below the proposed whole body criteria element of 8.1:
1) The Arkansas River mainstem (mean water [Se] = 7.05 ug/L), had samples from three species
that met the criteria in 2006, central stoneroller, smallmouth bass and white sucker.
2) In the tributaries to the Arkansas River that were sampled, white sucker in both Fountain Creek
(mean water [Se] = 3.43 ug/L) and St. Charles River met the whole body criteria in 2004 and
2005, whereas the only cyprinid to meet the proposed whole body criterion was the central
stoneroller in 2005.
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Cvprinid Abundance and Diversity:
Table E-17. Cyprinid Diversity (native spp. present- excludes carp): NA1V
1C 2008 Study.
Site
fSe] in water ug/L
2005
2006
Arkansas River Mainstem
ARM
7.05
1/6
3/6
ARB
8.72
6/6
5/6
ARN
8.81
5/6
3/6
ARE
10.6
5/6
4/6
Arkansas River Tributaries
Fountain Creek
FCP
3.43
5/6
4/6
FC4
12.1
4/6
6/6
Whitehorse Creek (WHC)
413
1/6
1/6
St. Charles River
SCI
3.09
5/6
5/6
SC21
11.7
4/6
NS
SC5
20.3
6/6
5/6
:SC2 only sampled in 2005
Table E-18. Cyprinid Abundance (native spp. present- excludes carp): NAMC 2008 Study
Site
fSe] in water ug/L
2005
2006
Arkansas River Mainstem
ARM
7.05
8
460
ARE
8.72
643
950
ARB
8.81
697
521
ARN
10.6
446
116
Arkansas River Tributaries
Fountain Creek
FCP
3.43
746
2352
FC4
12.1
1978
1825
Whitehorse Creek (WHC)1
413
926
81
St. Charles River
SCI
3.09
2920
14583
SC22
11.7
2757
NS
SC5
20.3
3102
2568
1 Whitehorse Creek comprised
2 SC2 not sampled in 2006
species, central stoneroller
Summary of cvprinid abundance and diversity:
1) Diversity as well as abundance of cyprinids in the tributaries vs the Arkansas River mainstem
more likely a function of habitat and/or predator density rather than influence of selenium.
2) Several sites on Wildhorse Creek, Fountain Creek, and the St. Charles River, had substantial
changes in the populations of some fish species between sample years 2005 and 2006, with
fish that were present in one year in high numbers and with a variety of age classes, either
E-52
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absent or present in low numbers the other year. These changes are likely to be linked to
higher stream flows present in 2006 and significant habitat changes due to beaver activity at
some sites. Variable population compositions and numbers of cyprinids are not uncommon in
plains streams with highly variable flow regimes and habitat conditions (Schlosser 1987).
3) Based on an evaluation of age class distribution (indicated by length-frequency distribution
data), it was concluded that the following sites had viable and reproducing cyprinid
populations (NAMC 2008:
Arkansas River mainstem: The length-frequency data collected for the fish species at
these sites indicates multiple age groups present for most of the species at the sites.
Fountain Creek - Length-frequency analysis of the flathead chubs indicated that the
populations are reproducing, with juvenile and older adult fish present in relatively high
numbers at both sites and years.
St. Charles River - Length-frequency analysis of the fish populations indicated that sites
had reproducing populations of central stonerollers, fathead minnows, and sand shiners,
with juvenile and adult fish collected during both years (GEI 2007a).
Wildhorse Creek - the age class distribution of central stonerollers was similar between
years, indicating a reproducing population that includes both juvenile and adult fish in
both years, despite the extremely high [Se] in water.
Relevance/Surrogacy of Arkansas River Cyprinids to all Cyprinid Species in US
Cyprinids captured from the Arkansas River are representative of cyprinid species occurring
throughout the US. This conclusion is based on the following lines of evidence:
• Six of the seven cyprinid species (central stoneroller, fathead minnow, flathead chub, longnose
dace, red shiner, and sand shiner) captured from the Arkansas River during this investigation
are native to the United States;
• Four of the six cyprinid species found in the Arkansas River basin (central stoneroller, fathead
minnow, sand shiner and red shiner) are widely distributed throughout the United States (see
species specific distribution maps Attachment 1); and,
• Six of the native species present in the Arkansas River Basin are direct surrogates at the genus
level for the 142 native cyprinids in North America (Table E-19).
E-53
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Table E-19. Cyprinid species surrogacy and occurrence in water for native species inhabiting the
Arkansas River and select tributaries.
Species
Cyprinid group
# of species
represented
by genus
[Se] in
waterbodies
where species
occurred
Average tissue
concentration or
range
Campostoma anomalum
Central stoneroller
stonerollers
5 species
3.1-418 ug/L
5-47 mg/kg dw
Pimephales promelas
Fathead minnow
Blunthead
minnows
4 species
3.1 -20.3 ug/L
No tissue
Platygabio gracilis
Flathead chub
Flathead chub
1 species
3.1 -20.3 ug/L
No tissue
Rhynichthys cataractae
Longnoise dace
dace
9 species
3.1 -20.3 ug/L
No tissue
Cyprinella lutrensis
Red shiner
Satinfin shiners
32 species
3.1 -20.3 ug/L
23-42 mg/kg dw
Notropis stramineus
Sand shiner
Eastern shiners
91 species
3.1 -20.3 ug/L
10-25 mg/kg dw
Summary cyprinid surrogacy:
Cyprinid species collected from the Arkansas River watershed are representative (at the genus
level) of the 142 cyprinid species native to North America. With the exception of one sample location
(Whitehorse Creek), the abundance and diversity of cyprinid species present and the occurrence of
multiple age classes indicates that cyprinids are successfully surviving and reproducing in the Arkansas
River watershed, even with selenium concentrations exceeding 5ug/L in water and 8 mg/kg bw in whole
body fish tissue. North American species not represented at the genera level comprise 54 species (mostly
chubs - 40 species), many of which are geographically isolated.
3. Observations of cyprinids in NC Reservoirs (Hyco Reservoir and Belews Lake) - (located at end
of NAMC 2008 report).
Crutchfield et al. (2000) evaluated long-term water quality data, selenium chemical concentration
data collected for sediment, invertebrate and fish tissues, and invertebrate and fish population data
collected from the Hyco Reservoir to document the recovery of the aquatic community following the
1990 installation of a dry fly ash pollution abatement system. Since 1973, data have been collected from
six locations in the Hyco Reservoir, with varying fly ash exposure. Gamefish including bluegill sunfish
and largemouth bass were reproductively extirpated due to high selenium concentrations prior to
installation of the pollution abatement system. The fish community was dominated by green sunfish
(Lepomis cyanellus), eastern mosquitofish (Gambusia holbrooki), gizzard shad (Dorosoma cepedianum),
and satinfin shiner (Cyprinella analostana). Their main observation was that satinfin shiner was a
dominant cyprinid in the Se limited fish community prior to selenium reduction.
E-54
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Barwick and Harrell (1997) evaluated fish population monitoring and tissue selenium
concentration data to document the recovery of fish populations in Belews Lake for the ten years
following installation of a dry fly ash pollution abatement system. Fish diversity and biomass data were
collected from 1977 to 1994 (with the exception of 1978-1979 and 1982-1983) at two sites on the lake. In
1980 and 1981, fathead minnows (Pimephales promelas) dominated the fish community, representing 62
percent and 81 percent of the biomass, respectively (Barwick and Harrell 1997). By 1984, red shiner
('Cyprinella lutrensis), common carp (Cyprinius carpio), and fathead minnows (Pimephales promelas)
were the dominant cyprinids in the selenium limited fish community prior to selenium reduction. The
authors noted that cyprinid abundance started to decrease as green sunfish, a more Se- tolerant sunfish
recovered in 1989-1990, followed by further decreases in 1990-1994, as channel catfish, bluegill, and
largemouth bass populations increased (Barwick and Harrell 1997).
Young et al. (2010), reviewing the studies of Belews Lake, NC, note that during the period of
maximal selenium inputs, egg and ovary concentrations reached 40-159 mg Se/kg dw. Out of as many as
29 resident species prior to contamination, only catfish and the cyprinids common carp and fathead
minnows remained during the period of maximum impact.
4. Presser, T.S., 2013, Selenium in ecosystems within the mountaintop coal mining and valley-fill
region of southern West Virginia—assessment and ecosvstem-scale modeling: U.S. Geological
Survey Professional Paper 1803. 86 p. http://dx.doi.org/10.3133/ppl803.
USGS sampled southern West Virginia ecosystems affected by drainage from mountaintop coal
mines and valleys filled with waste rock (valley fills) in the Coal, Gauley, and Lower Guyandotte
watersheds during 2010 and 2011. Sampling data from earlier studies in these watersheds (for example,
Upper Mud River Reservoir) and other mining-affected watersheds in WV are also are included to assess
additional hydrologic settings and food webs for comparison.
1) Site-specific fish abundance and richness data documented the occurrence of various species of
chub, shiner, dace, minnow, and central stoneroller (Campostoma anomalum) in the sampled
watersheds.
2) Model species for streams were limited to creek chub (Semotilus atromaculatus) and central
stoneroller. Creek chub was present at all sites during USGS sampling in 2010-2011.
However, both of these species are considered to have high tolerance for environmental
stressors based on results of traditional comparative fish community assessments.
Concentrations of Se in water and whole body tissues of creek chub, blacknose dace, and
stoneroller are shown in Table E-20.
3) The order of abundance for species with greater than 28 individuals was: creek chub, striped
shiner, mottled sculpin, green sunfish, central stoneroller, blacknose dace, bluntnose minnow,
and northern hog sucker. Shiners and darters were prevalent, but bluegill sunfish were absent
during the 2010 survey.
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Table E-20. Se in fish whole body tissue samples: Upper Mud River Basin and Tributaries.
(Compilations of data from different sources presented in (Presser et al. 2013).
Stream Segment
Year
[Se] in water
Mean (Range)
in ug/L
Creek Chub
Mean (Range) in
mg/kg dw
Blacknose
Dace Mean
(Range) in
mg/kg dw
Stoneroller
Mean (Range)
in mg/kg dw
Upper Mud River
2011
10.5, 18.2
9.0 (6.4-11)
Not Sampled
Not Sampled
Upper Mud River 1
2010
Not Sampled
10.3 (9.4-10.9)
Not Sampled
Not Sampled
Lower Mud River
2008
7.9
10.3 (9.4-15.4)
Not Sampled
Not Sampled
2011
5.2, 7
9(6.4-11)
Not Sampled
Not Sampled
Upper Mud River 2
(above Upper Mud
River 1)
2005
9.8 (4-22)1
2.9 (<1-8.7)
Not Sampled
Not Sampled
2006
Not Sampled
5.6 (2.2-10)
Not Sampled
Not Sampled
2007
Not Sampled
7.7 (3.7-10)
Not Sampled
Not Sampled
Berry Branch
2009-
2010
8.3 (1.7-18)2
4.0 (3.3-5.0)
9.6 (7.8-13)
Not Sampled
Stanley Fork
2009-
2010
6.0 (3.0-7.4)3
10.3 (7.2-13)
Not Sampled
Not Sampled
Lower Kanawha
River Watershed
Little Scary Creek
2006
20
Not Sampled
55
Not Sampled
2009
31.4 (23-42)
28 (3-80)
Not Sampled
Not Sampled
Connor Run
2009
47.8 (4-90)
(21-36)
Not Sampled
Not Sampled
Upper Kanawha
River Watershed
Jack's Branch
Mining Complex
Bull push fork
w/pond
2010
9.0-10.0
Not Sampled
66 (19-113)
Not Sampled
Bull push fork
downstream
2010
9.1-10
8.6 (6.2-13)
10.7(5.5-14)
6.9(3.1-17)
Hughes Fork
2005 -
2007
5.3 (2-10)
7.8 (4.1-10.9)
2005
7.9 (2.7-12.9)
2007
Not Sampled
12.4 (0.5-34.5)
2005
Hughes Creek
2010-
2011
2.1-13
9.9 (3.7-17)
16.9 (6.8-25)
9.0(3.6-14)
Big Coal River
Watershed
Beech Creek
2005-
2007
Not Sampled
(3-18)
Not Sampled
Not Sampled
Seng Creek
2005-
2009
27.5 (15-42)
8.2 (4.8-14.7)
Not Sampled
Not Sampled
2011
23.3
8.1 (5.4-10)
Not Sampled
Not Sampled
White Oak Creek
2005-
2007
15.8 (8-27)
5.8 (<1-12.8)
Not Sampled
7.1 (2.5-12.8)
1 Water samples collected between 2005 and 2008.
2 Water samples collected in 2009 and 2010.
3 Water samples collected in 2009 and 2010.
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Study Summary:
Samples in various environmental media (water, sediment, algae, macroinvertebrates, fish) were
collected by USGS (2010-2011), and others (e.g. WVDEP, Potesta) between 2005 and 2011. The stream
segments presented here represent a subset of the stream segments with available data. Only streams with
water [Se] >5.0 ug/L are presented to facilitate comparison with other studies with Se-impacted streams.
Overarching observations include:
1) [Se] in water averaged from 5.3 ug/L - 31.4 ug/L with a high of 90 ug/L (Connor Run, 2009).
2) [Se] in fish tissue: creek chub - averaged from 5.8 mg/kg wb to 28 mg/kg wb, with a
maximum whole body concentration of 80 mg/kg wb (Little Scary Creek, 2009).
3) [Se] in fish tissue: blacknose dace - averaged from 10.7 mg/kg wb to 66 mg/kg wb, with a
maximum whole body concentration of 113 mg/kg wb (Bull push fork w/pond, 2010)
4) [Se] in fish tissue: central stoneroller - averaged from 6.9 mg/kg wb to 12.4 mg/kg wb, with a
maximum whole body concentration of 34.5 mg/kg wb (Hughes Fork, 2005). Note also, that
central stoneroller, although common through stream segments samples, were not ubiquitous,
as was observed in the study conducted by NAMC in the Arkansas River near Pueblo CO.
5. Selenium concentrations in fish tissue collected from the Gunnison River.
httv://vubs. usss. sov/of/2012/1235/ofl2-1235. vdf
Approach: In sampling conducted in summer 2010, muscle tissue plugs were collected from
common carp (Cyprinus Linnaeus), roundtail chub (Gila robusta; listed), and whole body tissue samples
were collected from speckled dace (Rhinichthys osculus) inhabiting critical habitat in the Gunnison River
in Western Colorado (Table E-21). Total selenium in fish muscle plugs (mg/kg dw) for roundtail chub, or
in whole body (speckled dace) was calculated for all tissues. In follow-up sampling conducted in the
summer of 2011, muscle plugs were collected from common carp (Cyprinus Linnaeus), roundtail chub
{Gila robusta; listed), and bonytail chub (Gila elegans, listed) inhabiting critical habitat in the Gunnison
River in Western Colorado.
This study was intended to document any changes in selenium concentration in fish over the last
20 years based on remediation efforts that have been completed to date.
Table E-21. Fish tissue concentrations observed in Cyprinids.
Species
Year
Mean (Range) [Se]
# > muscle = 11*
# > whole body = 8
Roundtail Chub
2010
9.7 mg/kg dw (5.2-32.4)
2/15
2011
7.33 mg/kg dw (5.6-11.2)
1/15
Speckled Dace
2010
7.46 mg/kg dw (5.7-9.7)
6/15
* Muscle plugs were collected since this species is large enough for non-destructive sampling, and b) a
listed species.
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5.0 Other Data - Chronic Studies with Invertebrate Species
A limited number of studies have evaluated the effects of selenite on invertebrate species, an
important prey item for fish and birds as summarized by Debruyn and Chapman (2007). The following
studies with a rotifer, and annelid, and an insect (mayfly) were found suitable for establishing species
sensitivity.
5.1 Rotifers
Dobbs et al. (1996) exposed Brachionus calyciflorus to selenate in natural creek water for 25 days
in a three-trophic level food chain test system. This is one of two laboratory-based experiments (also see
Bennett et al. 1986) that involved exposing algae to selenium (in this case as sodium selenate) in water,
and subsequently feeding the algae to rotifers which were in turn fed to fish (fathead minnows). In this
particular study, the rotifers and fish were exposed to the same concentrations of sodium selenate in the
water as the algae, but received additional selenium from their diet (i.e., the algae fed to rotifers and the
rotifers fed to fish). The overall exposure lasted for 25 days. Rotifers did not grow well at concentrations
exceeding 108.1 |ag Se/L in water, and the population survived only 6 days at selenium concentrations
equal to or greater than 202.4 |_ig Se/L in the water (40 |_ig Se/g dw in the algae). Regression analysis of
untransformed growth data (dry weight) determined 4 day post-test initiation resulted in a calculated ECio
of 37.84 (ig Se/g dw tissue.
5.2 Aquatic Worms
Although not intended to be a definitive toxicity study for this invertebrate, Besser et al. (2006)
evaluated the bioaccumulation and toxicity of selenized yeast to the oligochaete, Lumbriculus variegatus,
which was intended to be used for dietary exposure in subsequent studies with the endangered desert
pupfish, Cyprinidon macularius. Oligochaetes fed selenized-yeast yeast diets diluted with nutritional
yeast (54 to 210 mg Se/kg) had stable or increasing biomass and accumulated Se concentrations as high
as 140 mg/kg dw. The oligochaetes fed the undiluted selenized-yeast (826 jxg/g Se dry wt.) showed
reduced biomass. The effect level is considered >140 mg Se/kg dw.
5.3 Aquatic Insects (Plecoptera: Mayfly)
Conley, J.M., D.H. Funk and D.B. Buchwalter. 2009. Selenium bioaccumulation and maternal transfer in
the mayfly Centroptilum triangulifer in a life-cycle, periphyton-biofilm trophic assay. Environ. Sci.
Technol. 43:7952-7957.
Conley, J.M., D.H. Funk, N.J. Cariello and D.B. Buchwalter. 2011. Food rationing affects dietary
selenium bioaccumulation and life cycle performance in the mayfly Centroptilum triangulifer.
Ecotoxicol. 20:1840-1851.
Conley, J.M., D.H. Funk, D.H. Hesterberg, L-C. Hsu, J. Kan, Y-T. Liu and D.B. Buchwalter. 2013.
Bioconcentration and biotransformation of selenite versus selenite exposed to periphyton and subsequent
toxicity to the mayfly Centroptilum triangulifer. Environ. Sci. Technol. 47:7965-7973.
E-58
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Conley et al. (2009) exposed mayfly larvae (Centroptilum triangulifer) to dietary selenium
contained in natural periphyton biofilms to eclosion. The periphyton fed to the mayfly larvae were
exposed to dissolved selenite (radiolabeled 75Se) in November 2008 (12.6 and 13.9 (ig/L) and in January
2009 (2.4, 2.4, 4.9, 10.3, and 10.7 j^ig/L). Periphyton bioconcentrated Se an average of 1113-fold over the
different aqueous Se concentrations (Table E-22). Twenty 4 to 6-day old mayfly larvae were exposed for
4.5 to 6 weeks to each of the periphyton diets until the larvae eclosed to subimagos. The subimagos were
allowed to emerge to the adult imago stage which deposited their egg masses in Petri dishes. Selenium
was measured in postpartum adults along with their dry weights and clutch size.
E-59
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Table E-22. Selenium concentrations in water exposed to periphyton, periphyton and mayfly adults.
Treatment
Dissolved [Se] exposed
to periphyton, jig/L
[Se] in periphyton,
mg/kg dw
[Se] in mayfly adult,
mg/kg dw
5A
2.4
2.2
4.2
5B
2.4
2.0
5.7
10A
4.9
4.4
9.7
20C
10.3
8.7
16.2
20D
10.7
11.3
27.5
20A
12.6
25.5
56.7
20B
13.9
17.5
34.8
Selenium increased in concentration from periphyton to the adult mayflies (trophic transfer
factor) an average of 2.2-fold (Table E-22). The authors observed a decrease in fecundity as maternal
postpartum Se concentrations increased. Fecundity was also related to growth of the mayflies. The
authors observed a reduction in fecundity for this mayfly when they were fed diets containing more than
11 mg Se/kg dw. This threshold is considered the effect value for this study. Using the trophic transfer
factor of 2.2, the periphyton Se concentration of 11 mg/kg dw translates to an adult mayfly Se
concentration of 24.2 mg/kg dw.
Conley et al. (2011) exposed larval C. triangulifer similar to Conley et al. (2009) to two different
rations of periphyton (lx and 2x) to evaluate the effect of feeding ration on the bioaccumulation and life
cycle performance of the mayfly. Periphyton (on plates) was initially exposed to low (1.1 to 3.4 (.ig/L),
medium (5.9 - 8.9 (ig/L) and high (19.2 - 23.1 (ig/L) selenite. Fifteen 1-2 day-old mayfly larvae were
then fed either 1 plate (lx ration) or 2 plates (2x ration) in bottles containing 1.8 L water to eclosion to
subimagos (25-29 days). Subimagos were induced to emerge to adults in petri dishes and their clutch size
measured through digital imaging. Selenium measurements from this study are given in Table E-23.
Table E-23. Selenium concentrations in water, periphyton and mayfly tissues for two feeding
rations.
(Adapted from Table 1 in Conley et al. 2011)
Feeding ration - Se level
Mean dissolved Se
Mean periphyton, mg
Mean mayfly tissue,
exposed to
periphyton, jig/L
Se/kg dw
mg Se/kg dw
lx - low
1.1
4.2 ± 0.6 (4)
12.8 ±3.6 (28)
lx - medium
5.9
11.9 ±2.1 (4)
31.7 ± 7.5 (15)
lx - high
21.4
27.2 ± 4.2 (4)
68.4 ±24.0 (9)
2x - low
2.7/3.4a
9.5 ±0.9 (3)
14.1 ±3.8 (19)
2x - medium
7.1/8.93
19.9 ± 1.6 (3)
21.6 ±2.8 (22)
2x - high
19.2/23. la
40.9 ± 1.7 (3)
37.3 ±6.7 (13)
a Two values represent two different loading exposures, September and October. The plates were
combined for mayfly exposure.
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Mayflies fed the lx ration had 54% and 72% reductions in survival relative to controls in the
medium and high Se treatment levels, respectively, both significant (p<0.05). The mayflies fed the lx
ration also had significant reductions in fecundity in the low (44% reduction), medium (63% reduction)
and high (77% reduction) Se treatment levels. However, for the mayflies fed the 2x ration, there were no
significant differences between the controls and any of the three Se treatment levels for any of the
endpoints measured including survival and fecundity. The 2x ration mayflies had 60% more biomass than
the lx ration mayflies. This growth difference explains why the lx ration mayflies had higher
concentrations of Se in their tissues. The two different rations resulted in vastly different effect levels for
Se, <12.8 mg/kg dw in the lx ration test and >37.3 mg/kg dw in the 2x ration. It is apparent from this
study that if the mayflies do not obtain sufficient nutrition, they are more sensitive to selenium. Although
reduced feeding levels occur in nature, it is a confounding variable in this study that cannot be used to set
a chronic effect level for selenium.
Conley et al. (2013) evaluated the accumulation of selenite and selenate into periphyton with
subsequent feeding exposure to mayfly larvae. As in his previous studies, C. triangulifer larvae were fed
periphyton previously exposed to different concentrations of selenium. In this study, periphyton plates
were first exposed to low (10 j^ig/L) and high (30 j^ig/L) concentrations of either selenite or selenate and
then fed to mayfly larvae to ecolsion to subimagos. The selenite and selenate treatment exposures resulted
in similar levels of selenium in the subimagos. Since no differences in selenium accumulation was
observed, the selenite and selenate treatments could be pooled for measuring the endpoints, survival and
secondary production (total mayfly biomass produced). Mean selenium concentrations fed the mayflies
were 2.2, 12.8 and 37 mg/kg Se dw in the control, low and high treatments, respectively. Mayfly tissue
(subimago) concentrations (extrapolated from Figure 4a in Conley et al. 2013) were approximately 4-7,
20-35, and 45-75 mg/kg Se dw, in the control, low and high treatments, respectively. The authors reported
significant reductions in survival from the control in the high Se treatment (both pooled data and
individual selenite and selenate treatments) but no significant differences were observed in the low Se
treatments. Secondary production was significantly reduced relative to the control in the high Se
treatment for both selenium species. For the low Se exposure treatment, secondary production was not
significantly different than the control for the selenite treated periphyton exposure, but was for the
selenate and pooled data suggesting an effect level between 20 and 35 mg/kg Se dw. These results as well
as those observed in 2x ration exposures in Conley et al. (2011) where no effects were observed at 37.3
mg/kg Se dw generally support the chronic value determined for Conley et al. (2009) of 24.2 mg/kg Se
dw.
The following invertebrate studies were inconclusive for establishing species sensitivity because
of limitations in the experimental designs, as explained for each.
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5.4 Aquatic Insect (Midge: Chironimids)
Malchow et al. (1995) fed fourth instar Chironomus decorus midge larvae a diet of seleniferous
algae under laboratory conditions for 96 hours. For algae cultured with selenite, a larval tissue
concentration of 4.05 |_ig Se/g dry weight resulted in a 46% reduction in growth relative to the controls. At
a larval tissue concentration of 8.6 (.ig Se/g dry weight, larval growth was reduced by only 39%. Since the
study only reported two exposure concentrations, it is unclear if the tissue effect concentration at 4.05 (.ig
Se/g dry weight is real or an anomaly. Additional exposure concentrations and subsequent effect levels
are needed to resolve this issue.
Malchow et al. (1995) also fed fourth instar Chrionomus decorus midge larvae a diet of algae
cultured with selenate, and the midge larvae were exposed under laboratory conditions for 96 hours. A
dietary exposure of 2.11 |_ig Se/g dry weight significantly reduced larval growth (15% reduction) at tissue
concentrations of 2.55 |_ig Se/g dry weight. At a larval tissue concentration of 6.62 |_ig Se/g dry weight,
growth was reduced 20% relative to the controls. The 15-20% reduced growth at larval tissue
concentrations 2.55 |_ig Se/g dry weight may be statistically significant, but not biologically meaningful.
In addition, exposure to only two selenium concentrations precludes confirmation of a dose-response.
Alaimo et al. (1994) also exposed 2010 midge larvae to selenite diet, but the selenium source was
from field contaminated widgeongrass (Ruppia maritima). Ruppia stems and leaves were collected from
four selenium contaminated evaporation ponds located in the San Joaquin Valley of California. Three-day
old larvae were exposed to each of the four treatment diets (Ruppia from each pond) plus a Cerophyll
control for 14 days (egg to pupation), with the moderately hard reconstituted water renewed at day 7 and
every three days thereafter. The growth (weight) of exposed larvae was significantly reduced in all of the
selenium treatments when compared to the controls. The lowest effect level was observed for the
Westlake pond (primarily selenite), where growth was reduced 40 percent relative to the controls at a
larval tissue concentration below the detection level (1.0 ppm dry weight, or 1.0 |_ig Se/g dry weight).
These results are suspect because the field collected Ruppia likely contained contaminants other than
selenium, the control organisms were fed a different diet (Cerophyll), and the single concentration
exposure is difficult to defend.
6.0 Other Data - Field Study West Virginia Impoundments
In response to the USEPA (2004) draft whole fish tissue criterion for selenium, the West Virginia
Department of Environmental Protection (2010) initiated a study to assess selenium bioaccumulation
among fishes residing in the State's lakes and streams. A focus of the study was the collection and
evaluation of bluegill, Lepomis macrochirus, larvae (ichthyoplankton) from selected waterbodies since
E-62
-------
2007, based on concerns regarding fish population health at locations subjected to elevated selenium
inputs, particularly during the more sensitive developmental life stages of fishes (e.g. yolk-sac larvae).
Also, in 2009, WVDEP began acquiring data about selenium concentrations within fish eggs of various
species within reference and selenium-impacted waters. WVDEP also conducted deformity surveys of
adult fishes in selenium enriched waters as well as at reference locations in 2008-2009.
WVDEP scientists found that larval deformity rates were variable throughout the study duration
but were nonetheless correlated with waterborne selenium exposure. Reference locations produced age-
based larval bluegill subsamples (24-168 hours) with low deformity rates (0 - 1.27%); whereas, locations
with seleniferous inputs exhibited bluegill deformity rates ranging from 0% to 47.56% in developmental
stages up to 312 hours. Maximum deformity rates among staged bluegill subsamples as determined
through these evaluations were 19.28%, representing specimens collected from selenium-enriched waters.
Concentrations of selenium within fish eggs also varied according to study location and ranged from <0.8
mg/kg dry weight among bluegill eggs at the control site to 64.62 mg/kg dry weight among largemouth
bass, Micropterus salmoides, eggs collected from selenium-enriched waters. Searches for more mature,
yet developmentally-deformed fishes revealed increased deformity rates (14%) among largemouth bass
residing in a selenium impacted reservoir as compared to deformity rates among largemouth bass found in
the reference lake (0%). The data on egg selenium concentrations are not adequate for constructing a
concentration-response curve. Nevertheless, the overall deformity rate in the contaminated Upper Mud
River Reservoir was 5% among 10,000 individual fish, average egg selenium concentration 9.8 mg/kg
dw. The overall deformity rate in the reference Plum Orchard Lake was 0.5% among 13,000 individuals,
average egg selenium concentration nondetectable or <0.8 mg/kg dw.
E-63
-------
7.0 Other Data - Nutritional Deficiency/Sufficiency Studies
Containing Measured Selenium in the Diet and Whole
Body Fish Tissue
Ingested dietary dose studies in fish designed to identify nutritionally deficient and/or
nutritionally sufficient selenium doses in fish food or prey primarily describe selenium effects on growth,
with survival reductions and effects on antioxidant enzyme activity also occasionally reported. A number
of the dietary studies have measured a range of dietary doses that maximize fish growth, as opposed to a
single dietary dose associated with nutritional sufficiency for growth. Regardless of whether nutritionally
sufficient dietary doses are reported as a single concentration or as a range of concentrations, reduced
growth or survival is observed at both lower dietary doses (nutritional deficiency) and at higher dietary
doses (toxicity).
Although dietary doses are normally presented as selenium concentrations in food, expressed in
terms of mg/kg Se in the diet, several studies have also concurrently presented nutritionally
deficient/sufficient Se levels in terms of the whole body Se concentration in the fish. These studies permit
a comparison of nutritionally deficient/sufficient whole body Se residues in fish to the national criterion
for Se in whole bodies of fish. When combined with measured whole body fish tissue residues associated
with toxicity, a complete picture of the range of Se residues in whole body fish tissue associated with
nutritional deficiency, nutritional sufficiency and toxicity emerges.
Eight fish species have information on both nutritionally deficient dietary doses and whole body
concentrations of selenium measured in the same study (Table E-24). Six of the eight species are native to
North America. Nutritionally deficient dietary doses of Se range between 0.03 mg/kg dw in Atlantic
salmon (Salmo salar, Poston et al. 1976) associated with reduced survival to 1.4 mg/kg dw in Atlantic
cod (Gadus morhua, Hamre et al. 2008), also associated with reduced survival. Whole body Se residues
identified as nutritionally deficient range between 0.64 mg/kg dw in Malabar grouper (Epinephelus
malabaricus) associated with suboptimal weight gain and feed efficiency (Lin and Shiau 2005) and 4.72
mg/kg dw in North African catfish (Clarias gariepinus), also associated with suboptimal weight gain
(Abdel-Tawwab et al. 2007). The whole body Se residues associated with growth and/or survival
reductions due to nutritional deficiency of the six North American species (Prussian carp, Han et al. 2011;
common carp, Gaber 2007; Atlantic cod, Hamre et al. 2008; Coho salmon, Felton et al. 1990; cobia, Lin
et al. 2010; Atlantic salmon, Poston et al. 1976) all range between 1.0 and 2.7 mg/kg dw.
Ten fish species have information on both nutritionally sufficient dietary doses and whole body
concentrations of selenium measured in the same study (Table D-23). Eight of the 10 species are native to
North America. Nutritionally sufficient dietary doses of Se for the North American resident species, all
but one of which are based on maximum growth of fish, range between 0.1 mg/kg dw in hybrid striped
E-64
-------
bass (Jaramillo 2006) and 6.6 mg/kg dw in rainbow trout (Hilton and Hodson 1983). Several studies have
identified a range of dietary doses and associated whole body residues that maximize growth and survival
relative to that of fish fed lower dietary doses and which subsequently contain lower whole body selenium
residues. Whole body Se residues associated with nutritional sufficiency based on maximal growth and/or
survival of all North American species except for hybrid striped bass (Jaramillo 2006) range between 0.2
- 3.63 mg/kg dw (Table D-23). For hybrid striped bass, Jaramillo (2006) observed that maximum weight
gain occurred in selenite supplemented diets containing 1.19 mg/kg dw Se, which resulted in whole body
Se residues of 5.13 mg/kg dw. Jaramillo (2006) also exposed hybrid striped bass to seleno-DL-
methionine supplemented diets containing 0.90 mg/kg dw, which resulted in the maximum weight gain of
all seleno-DL-methionine supplemented diets tested, and a whole body Se residue of 7.2 mg/kg dw.
The nutritional sufficiency study of Rider et al. (2009) with rainbow trout is unique in that it
determined dietary and whole body selenium requirements for both stressed and unstressed fish. Rider et
al. (2009) observed that rainbow trout stressed by a combination of low water levels in holding tanks and
twice daily handling of fish by 30 second aerial exposure in dip nets resulted in a higher nutritional
requirement for selenium than was observed in fish not subjected to the stress routine. They concluded
that trout exposed to physical stressors could benefit from an additional 0.3 - 2.0 mg/kg dw additional
selenium supplementation over and above the Se content of nutritionally Se sufficient diets for fish not
undergoing stress.
The fish with the highest known nutritional requirement for selenium is the non-North American
resident North African catfish (Clarias gariepinus). Abdel-Tawwab et al. (2007) determined in a 12 week
study with fingerlings that Se dietary doses of 1.04 mg/kg dw and 3.67 mg/kg dw were associated with
suboptimal and maximum weight gains of the catfish, respectively. Catfish survival was 100% in both the
Se-deficient and Se-sufficient dietary dose exposures during the 12 week study period. The respective
whole body selenium tissue residues at the end of the 12 week study were 4.72 mg/kg dw in the Se-
deficient fish and 15.43 mg/kg dw in the fish fed the nutritionally sufficient Se diet. North African catfish
(Abdel-Tawwab et al. 2007) is the only known fish species with an identified whole body nutritional
requirement for Se higher than the national aquatic life criterion for whole body Se in fish.
E-65
-------
Table E-24. Studies with both empirically measured selenium dietary doses and whole body residues associated with nutritional deficiency
and sufficiency in fish.
Speck's
l.ifesliitie /
Si/o \\ el
Ml
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(liii'iilion
ln»eslc(l
(licliin dose
So m»/k»
(In «l.
So chcmiciil
form
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hody So
niii/kii
(In \\l
Deficiency
til'
Siilficicno
Deficiency sy niploms
liiisis lor sufficiency
(lelei'iniiiiilion
Reference
Malabar grouper
(.Epinephelus
malabaricus)
Juvenile
12.2 g
8 weeks
0.21
Basal diet
0.64
Deficiency
Suboptimal weight gain
and feed efficiency
Lin and Shiau
2005
Prussian carp
(Carassius gibelio)
Juvenile
2.74 g
100 days
0.47
Seleno-
methionine
1.0
Deficiency
Suboptimal growth,
feeding rate and feed
conversion rate
Han et al.
2011
Common carp
(Cyprinus carpio)
Juvenile
26.9 g
120 days
0.04
Basal diet
1.04
Deficiency
Reduced growth and
survival
Gaber 2007
Atlantic cod (Gadus
morhua)
Larvae 0.16
g
(estimated
from dry wt
of larvae
23 days
1.4
Basal diet
1.1
Deficiency
Larval survival 32%
lower compared to larvae
fed selenium-enriched
diet
Hamre et al.
2008
Cobia (Rachycentron
canadum)
Juvenile
6.27 g
10 weeks
0.21 -0.62
0.21 = Basal
diet, 0.62 =
seleno-DL-
methionine
1.13 -
2.11
Deficiency
Statistically significantly
reduced specific growth
rate and survival
Liu et al.
2010
Coho salmon
(Oncorhynchus kisutch)
Smolt 22.7
g
Hatchery
reared
0.7-0.9
Not given
1.974
Deficiency
Survival of hatchery
reared smolts 1.5 - 2.Ox
lower than wild smolts
Felton et al.
1990
Atlantic salmon (Salmo
salar)
Fry 0.1 g
4 weeks
0.03-0.04
Basal diet
2.7
Deficiency
Decreased survival
relative to fry fed diet
supplemented with 0.1
jxg/g Se and 0.5 IU/g
vitamin E
Poston et al.
1976
North African catfish
(Clarias gariepinus)
Fingerling
68.6 g
12 weeks
1.04
Organic Se
4.72
Deficiency
Suboptimal weight gain
and specific growth rate
Abdel-
Tawwab et al.
2007
Rainbow trout
(iOncorhynchus mykiss)
Juvenile
0.6 g
16 weeks
0.6-6.6
Selenite
Na2Se03-5H20
0.2 - 1.0
Sufficiency
No deficiency or toxicity
signs on growth
Hilton and
Hodson 1983
E-66
-------
Spooios
l.ifoshiiio /
Si/o \\ o(
Ml
l'l\|)OMIIV
(lii rill i«ui
Injioslod
(lioliin dose
So m»/k»
(In m(.
So ohomioiil
l'o nil
\\ liolo
hod\ So
niii/kii
(In mi
IkTiciono
or
Siifl'iciono
l)ofioiono\ s\ mpionis
liiisis lor sulTiciono
(lolormi ii;i 1 ion
Roforonoo
Atlantic salmon (Salmo
salar)
Parr 4.5 g
8 weeks
1.2
Basal diet
0.58 -
0.70
Sufficiency
No deficiency signs on
growth, survival or
glutathione peroxidase
activity
Lorentzen et
al. 1994
Rainbow trout
{Oncorhynchus mykiss)
Juvenile
26.3 g
11 weeks
0.77
Basal diet
0.9
Sufficiency
Optimal growth, survival
and antioxidant status
Rider et al.
2009
Malabar grouper
(.Epinephelus
malabaricus)
Juvenile
12.2 g
8 weeks
0.77
Seleno-
methionine
0.92
Sufficiency
Maximal weight gain and
feed efficiency
Lin and Shiau
2005
Atlantic salmon (Salmo
salar)
Parr 4.5 g
8 weeks
3.4
Selenite
Na2Se03-5H20
1.13
Sufficiency
No deficiency signs on
growth, survival or
glutathione peroxidase
activity
Lorentzen et
al. 1994
Common carp
(Cyprinus carpio)
Juvenile
26.9 g
120 days
0.24-0.32
Selenite
Na2Se03-5H20
1.23 -
1.29
Sufficiency
Maximal growth and
survival
Gaber 2007
Rainbow trout
(iOncorhynchus mykiss)
Juvenile
26.3 g
11 weeks
2.3-3.9
Selenite
Na2Se03-5H20
1.6-2.8
Sufficiency
Optimal growth, survival
and antioxidant status
Rider et al.
2009
Prussian carp
(Carassius gibelio)
Juvenile
2.74 g
100 days
1.23-2.77
Seleno-
methionine
1.7-3.4
Sufficiency
Maximal growth, no
effect on survival, no
increase in oxidative
stress
Han et al.
2011
Hybrid striped bass
(wiper, Morone
chrysops x Morone
saxatilis)
Juvenile
2.94 g
12 weeks
0.10
Basal diet
2.01
Sufficiency
Minimum dietary
requirement for
acceptable survival and
growth
Jaramillo
2006
Atlantic salmon (Salmo
salar)
Parr 4.5 g
8 weeks
3.1
Seleno-
methionine
2.06
Sufficiency
No deficiency signs on
growth, survival or
glutathione peroxidase
activity
Lorentzen et
al. 1994
Cobia (Rachycentron
canadum)
Juvenile
6.27 g
10 weeks
0.85 - 1.36
Seleno-DL-
methionine
2.58 -
2.62
Sufficiency
Maximal and statistically
identical specific growth
rate and survival
Liu et al.
2010
E-67
-------
Spooios
l.ifoshiiio /
Si/o \\ o(
Ml
l'l\|)OMIIV
(lii rill i«ui
Injioslod
(lioliin dose
So m»/k»
(In m(.
So ohomioiil
l'o nil
\\ hole
hod\ So
niii/kii
(In mi
IkTiciono
or
Siifl'iciono
l)efioiene\ s\ mpionis
liiisis lor sulficiono
(lolormi ii;i 1 ion
Roforonoo
Rainbow trout
(Oncorhynchus mykiss)
Juvenile
26.3 g
11 weeks
2.4-4.1
Organic Se -
yeast
2.8-4.8
Sufficiency
Optimal growth, survival
and antioxidant status
Rider et al.
2009
Atlantic cod (Gadus
morhua)
Larvae 0.16
g
(estimated
from dry wt
of larvae
23 days
4.8
Selenite
Na2Se03-5H20
3.5
Sufficiency
Larval survival increased
32%, growth essentially
unchanged relative to
survival of larvae fed
basal diet
Hamre et al.
2008
Coho salmon
{Oncorhynchus kisutch)
Smolt
14.28 g
Wild
smolts
Se in natural
diet unknown
Unknown
3.63
Sufficiency
Survival of wild smolts
1.5 - 2.Ox higher than
hatchery reared smolts
Felton et al.
1990
Hybrid striped bass
(wiper, Morone
chrysops x Morone
saxatilis)
Juvenile
2.94 g
12 weeks
1.19
Selenite
Na2Se03-5H20
5.13
Sufficiency
Highest weight gain of
any selenite diet test,
significantly higher than
basal diet weight gain
Jaramillo
2006
Hybrid striped bass
(wiper, Morone
chrysops x Morone
saxatilis)
Juvenile
2.92 g
12 weeks
0.90
Seleno-DL-
methionine
7.2
Sufficiency
Highest survival and
weight gain of any
seleno-DL-methionine
diet tested
Jaramillo
2006
North African catfish
(Clarias gariepinus)
Fingerling
68.6 g
12 weeks
3.67
Organic Se
15.43
Sufficiency
Maximal weight gain,
specific growth rate and
survival
Abdel-
Tawwab et al.
2007
E-68
-------
APPENDIX F: Toxicity of Selenium to
Aquatic Plants
F-l
-------
1.0 Selenite
Data are available on the toxicity of selenite to 13 species of freshwater algae and plants (Table
F-l). Results ranged from an LC50 of 70,000 (ig/L for the green alga, Chlorella ellipsoidea (Shabana and
El-Attar 1995) to 522 |ig/L for incipient inhibition of the green alga, Scenedesmus quadricauda
(Bringmann and Kuhn 1977a, 1978a,b, 1979, 1980b). Foe and Knight (Manuscript) found that 75 (ig/L
decreased the dry weight of Selenastrum capricornutum (Table F-l). Wehr and Brown (1985) reported
that 320 |ig/L increased the growth of the alga Chrysochromulina breviturrita.
The 96-hr EC50 for the saltwater diatom, Skeletonema costatum, is 7,930 |ig/L. based on reduction
in chlorophyll a (Table F-l). Growth of Chlorella sp., Platymonas subcordiformis, and Fucus spiralis
increased at selenite concentrations from 2.6 to 10,000 |ig/L (Table F-l). Other marine algae exposed to
selenite from 14 to 60 days had no observed effect concentrations (NOAEC) that ranged from 1,076 to
107,606 |ig/L. These data suggest that saltwater plants will not be adversely affected by concentrations of
selenite that do not affect saltwater animals.
2.0 Selenate
Growth of several species of green algae was affected by concentrations ranging from 100 to
40,000 |ig/L (Table F-l). Blue-green algae appear to be more tolerant to selenate with 1,866 |ig/L being
the lowest concentration reported to affect growth (Kiffney and Knight 1990). Kumar (1964) found that a
blue-green alga developed and lost resistance to selenate. The difference in the sensitivities of green and
blue-green algae to selenate might be of ecological significance, particularly in bodies of water
susceptible to nuisance algal blooms. For example, Patrick et al. (1975) reported that a concentration of
1,000 |ig/L caused a natural assemblage of algae to shift to a community dominated by blue-green algae.
The saltwater coccolithophore, Cricosphaera elongata, had reduced growth when exposed to
41,800 (ig/L selenate for 14 days (Boisson et al. 1995). Seven other saltwater algal species investigated by
Wong and Oliveira (1991a) exhibited NOEC growth values that ranged from 1,043 to 104,328 |ig/L. At
10,000 |ig/L. selenate is lethal to four species of saltwater phytoplankton and lower concentrations
increase or decrease growth (Table F-l). Wheeler et al. (1982) reported that concentrations as low as 10
|ig/L reduced growth of Porphyridium cruentum (Table F-l).
Although selenite appears to be more acutely toxic than selenate to most aquatic animals, this
does not seem to be true for aquatic plants. Selenite and selenate are about equally toxic to the freshwater
algae Anabaena cylindrica, Anabaena flos-aquae, Anabaena variabilis, Anacystis nidulans, and
Scenedesmus dimorphus (Kiffney and Knight 1990; Kumar and Prakash 1971; Moede et al. 1980) and the
saltwater algae Agemenellum quadroplicatum, Chaetoceros vixvisibilis and Amphidinium carterae (Wong
and Oliveira 1991a). The two oxidation states equally stimulated growth of Chrysochromulina
F-2
-------
breviturrita (Wehr and Brown 1985). On the other hand, selenate is more toxic than selenite to the
freshwater Selenastrum capricornutum (Richter 1982; Ibrahim and Spacie 1990) and the saltwater
Chorella sp., Platymonas subcordiformis and Nannochloropsis oculata (Wheeler et al. 1982; Wong and
Oliveira 1991a). In addition, Fries (1982) found that growth of thalli of the brown macroalga, Fucus
spiralis, was stimulated more by exposure to selenite at 2.605 |ig/L than to the same concentration of
selenate.
A Final Plant Value, as defined in the Guidelines, cannot be obtained because no test in which the
concentrations of selenite or selenate were measured and the endpoint was biologically relevant has been
conducted with an important aquatic plant species.
F-3
-------
Table F-l. Toxicity of selenium to aquatic plants
Species
Chemical
1 lardness
(m»/l. as
CaCO,)
Duration
(days)
KITecl
Concent ration
(MB/'-)"
Reference
FRESHWATER SPECIES
Selenium (IV)
Green alga,
Chlorella vulgaris
Sodium
selenite
-
90-120
Reduced
growth
5,480
De Jong 1965
Green alga,
Chlorella ellipsoidea
Sodium
selenite
-
7
EC50
70,000
Shabana and El-
Attar 1995
Green alga,
Scenedesmus
dimorphus
Sodium
selenite
-
14
Reduced
growth
24,000
Moede et al.
1980
Green alga,
Scenedesmus
quadricauda
Sodium
selenite
-
8
Incipient
inhibition
522
Bringmann and
Kuhn 1977a;
1978a,b; 1979;
1980b
Green alga,
Scenedesmus
quadricauda
Sodium
selenite
-
8
Incipient
inhibition
2,500
Bringmann and
Kuhn 1959a
Green alga,
Selenastrum
capricornutum
Sodium
selenite
-
4
EC50
2,900
Richter 1982
Green alga,
Selenastrum
capricornutum
Sodium
selenite
-
6
EC50
65,000
Ibrahim and
Spacie 1990
Blue-green alga,
Anabaena constricta
Sodium
selenite
-
7
EC50
67,000
Shabana and El-
Attar 1995
Blue-green alga,
Anabaena cylindrica
Sodium
selenite
-
14
Reduced
growth
24,000
Moede et al.
1980
Blue-green alga,
Anabaena flos-aquae
Sodium
selenite
-
10
Reduced
chlorophyll
a
1,866
Kiffney and
Knight 1990
Blue-green alga,
Anabaena variabilis
Sodium
selenite
-
6-18
LC50
15,000b
Kumar and
Prakash 1971
Blue-green alga,
Anacystis nidulans
Sodium
selenite
-
10-18
LC50
30,000b
Kumar and
Prakash 1971
Blue-green alga,
Microcystis
aeruginisa
Sodium
selenite
-
8
Incipient
inhibition
9,400
(9,300)
Bringmann and
Kuhn 1976;
1978a,b
Alga,
Euglena gracilis
-
-
15
Reduced
growth
5,920
Bariaud and
Mestre 1984
Duckweed,
Lemna minor
-
-
4
EC50
2,400
Wang 1986
Duckweed,
Lemna minor
Sodium
selenite
-
14
EC50
(mult, rate)
3,500
Jenner and
Janssen-
Mommen 1993
F-4
-------
Species
Chemical
1 lardness
(111"/1. its
("a CO.,)
Duration
(days)
KITecl
Concent ration
(Jili/I-)'
Reference
Duckweed,
Lemna minor
Sodium
selenite
-
14
NOEC
(mult, rate)
800
Jenner and
Janssen-
Mommen 1993
Selenium (VI)
Green alga,
Anki strode smus
falcatus
Sodium
selenate
-
14
Did not
reduce
growth
10
Vocke et al. 1980
Green alga,
Scenedesmus
dimorphus
Sodium
selenate
-
14
Reduced
growth
22,100
Moede et al.
1980
Green alga,
Scenedesmus
obliquus
Sodium
selenate
-
14
Reduced
growth
100
Vocke et al. 1980
Green alga,
Selenastrum
capricornutum
Sodium
selenate
-
14
Reduced
growth
300
Vocke et al. 1980
Green alga,
Selenastrum
capricornutum
Sodium
selenate
-
4
EC50
199
Richter 1982
Green alga,
Selenastrum
capricornutum
Sodium
selenate
-
6
EC50
<40,000
Ibrahim and
Spacie 1990
Blue-green alga,
Anabaena cylindrica
Sodium
selenate
-
14
Reduced
growth
22,100
Moede et al.
1980
Blue-green alga,
Anabaena flos-aquae
Sodium
selenate
-
10
Reduced
chlorophyll
a
1,866
Kiffney and
Knight 1990
Blue-green alga,
Anacystis nidulans
Sodium
selenate
-
6-18
EC50
39,000b
Kumar and
Prakash 1971
Blue-green alga,
Anabaena viriabilis
Sodium
selenate
-
10-18
EC50
17,000b
Kumar and
Prakash 1971
Blue-green alga,
Microcoleus
vaginatus
Sodium
selenate
-
14
Reduced
growth
10,000
Vocke et al. 1980
Duckweed,
Lemna minor
Sodium
selenate
-
14
EC50
(mult, rate)
11,500
Jenner and
Janssen-
Mommen 1993
Duckweed,
Lemna minor
Sodium
selenate
-
14
NOEC
(mult, rate)
>2,400
Jenner and
Janssen-
Mommen 1993
F-5
-------
Species
Chcmic:il
Snlinilv
(li/lvli)
Duiitlion
(iliiys)
KITecl
Concent r;ilion
(Mii/I-)'
Reference
SALTWATER SPECIES
Selenium (IV)
Green alga,
Dunaliella tertiolecta
Sodium
selenite
-
60
NOEC
growth
1,076
Wong and
Oliveira 1991a
Cyanophyceae alga,
Agemenellum
quadruplicatum
Sodium
selenite
-
60
NOEC
growth
10,761
Wong and
Oliveira 1991a
Diatom,
Chaetoceros
vixvisibilis
Sodium
selenite
-
60
NOEC
growth
1,076
Wong and
Oliveira 1991a
Diatom,
Skeletonema
costatum
Selenious
acidc
-
4
EC50
(reduction
in
chlorophyll
a)
7,930
U.S. EPA 1978
Coccolithophore,
Cricosphaera
elongata
Sodium
selenite
-
14
Reduced
growth
4,570
Boisson et al.
1995
Dinoflagellate,
Amphidinium
carterae
Sodium
selenite
-
60
NOEC
growth
10,761
Wong and
Oliveira 1991a
Dinoflagellate,
Peridinopsis borgei
Selenium
oxide
-
70-75
Maximum
growth
0.01-0.05
Lindstrom 1985
Eustigmatophyceae
alga,
Nannochloropsis
oculata
Sodium
selenite
-
60
NOEC
growth
107,606
Wong and
Oliveira 1991a
Pyrmnesiophyceae
alga,
Isochrysis galbana
Sodium
selenite
-
60
NOEC
growth
1,076
Wong and
Oliveira 1991a
Pyrmnesiophyceae
alga,
Pavlova lutheri
Sodiun
selenite
-
60
NOEC
growth
1,076
Wong and
Oliveira 1991a
Selenium (VI)
Green alga,
Dunaliella tertiolecta
Sodium
selenate
-
60
NOEC
growth
104,328
Wong and
Oliveira 1991a
Cyanophyceae alga,
Agemenellum
quadruplicatum
Sodium
selenate
-
60
NOEC
growth
10,433
Wong and
Oliveira 1991a
Diatom,
Chaetoceros
vixvisibilis
Sodium
selenate
-
60
NOEC
growth
1,043
Wong and
Oliveira 1991a
Coccolithophore,
Cricosphaera
elongate
Sodium
selenate
-
14
Reduced
growth
41,800
Boisson et al.
1995
Dinoflagellate,
Sodium
-
60
NOEC
10,433
Wong and
F-6
-------
Species
(hemicnl
Snlinilv
(li/lvli)
Duiitlion
(iliiys)
KITecl
Concent r;ilion
(Mii/I-)'
Reference
Amphidinium
carterae
selenate
growth
Oliveira 1991a
Eustigmatophyceae
alga,
Nannochloropsis
oculata
Sodium
selenate
-
60
NOEC
growth
10,433
Wong and
Oliveira 1991a
Pyrmnesiophyceae
alga,
Isochrysis galbana
Sodium
selenate
-
60
NOEC
growth
10,433
Wong and
Oliveira 1991a
Pyrmnesiophyceae
alga,
Pavlova lutheri
Sodium
selenate
-
60
NOEC
growth
104,328
Wong and
Oliveira 1991a
a Concentration of selenium, not the chemical.
b Estimated from published graph.
c Reported by Barrows et al. (1980) in work performed under the same contract.
F-7
-------
APPENDIX G: Unused Data
G-l
-------
Based on the requirements set forth in the guidelines (Stephen et al. 1985) the following studies
are not acceptable for the following reasons and are classified as unused data. Note the acceptance of
chronic toxicity data included diet and field exposures where selenium was the dominant toxicant.
Studies Were Conducted
Ahsanullah and Brand (1985)
Ahsanullah and Palmer
(1980)
Baker and Davies (1997)
Barghigiani et al. (1993)
Chidambaram and Sastry
(1991a,b)
Congiu et al. (1989)
Cuvin and Furness (1988)
Fowler and Benayoun
(1976a,b)
Gaikwad (1989)
with Species That Are Not Resident in North America
Gotsis (1982)
Hiraika et al. (1985)
Juhnke and Ludemann (1978)
Kitamura (1990)
Manoharan and Prabakaran
(1994)
Minganti et al. (1994, 1995)
Niimi and LaHam (1975,
1976)
Regoli (1998)
Regoli and Principato (1995)
Rhodes et al. (1994)
Ringdal and Julshamn (1985)
Rouleau et al. (1992)
Sastry and Shukla (1994)
Savant and Nilkanth (1991)
Shultz and Ito (1979)
Srivastava and Tyagi (1985)
Takayanagi(2001)
Tomasik et al. (1995b)
Tian and Liu (1993)
Wrench (1978)
Deelstra et al. (1989), Forsythe and Klaine (1994), Okasako and Siegel (1980) and Petrucci et al.
(1995) conducted tests with brine shrimp species that are too atypical to be used in derving national
criteria.
These Studies or Reviews
Adams and Johnson (1981)
Biddinger and Gloss (1984)
Bowie et al. (1996)
Brandao et al. (1992)
Brooks(1984)
Burton and Stemmer (1988)
Chapman et al. (1986)
Davies (1978)
Debruyn and Chapman
(2007)
Devillers et al. (1988)
Contain Relevant Data That
Eisler (1985)
Hall and Burton (1982)
Hodson and Hilton (1983)
Hodson et al. (1984)
Jenkins (1980)
Kaiser et al. (1997)
Kay (1984)
LeBlanc (1984)
Lemly (1993c, 1996ab,
1997d)
Lemly and Smith (1987)
Have Been Published Elsewhere
McKee and Wolf (1963)
National Research Council
(1976) Neuhold (1987)
NCDNR&CD (1986)
Peterson and Nebeker (1992)
Phillips and Russo (1978)
Presser (1994)
Roux et al. (1996)
Swift (2002)
Thompson et al. (1972)
Versar (1975)
G-2
-------
Authors Did Not Specify the Oxidation State of Selenium Used in Study
Greenberg and Kopec (1986) Kapu and Schaeffer (1991)
Hutchinson and Stokes Kramer et al. (1989) Rauscher (1988)
(1975) Mahan et al. (1989) Snell et al. (1991b)
Not Useful Because of No Effects Observed at Exposure Concentrations or Insufficient Number of
Treatments
Muscatello and Janz (2009)
Pyle et al. (2005)
Schlenk et al (2003)
Chronic Study with no Dietary Exposure
Hopkins et al. (2002)
Oti (2005)
Rowe (2003)
Teh et al. (2002)
Selenium Was a Component of an Effluent, Fly Ash, Formulation, Mixture, Sediment or Sludge
Apte et al. (1987)
Cherry et al. (1987)
Eriksson and Forsberg (1992)
Baer et al. (1995)
Cieminski and Flake (1995)
Eriksson and Pedros-Alio
Baker et al. (1991)
Clark et al. (1989)
(1990)
Berg et al. (1995)
Cooke and Lee (1993)
Fairbrother et al. (1994)
Besser et al. (1989)
Cossu et al. (1997)
Fava et al. (1985a,b)
Biedlingmaier and Schmidt
Coyle et al. (1993)
Feroci et al. (1997)
(1989)
Crane et al. (1992)
Finger and Bulak (1988)
Bjoernberg (1989)
Crock et al. (1992)
Finley (1985)
Bjoernberg et al. (1988)
Cushman et al. (1977)
Fisher and Wente (1993)
Bleckmann et al. (1995)
Davies and Russell (1988)
Fjeld and Rognerud (1993)
Boisson et al. (1989)
de Peyster et al. (1993)
Fletcher et al. (1994)
Bondavalli et al. (1996)
Dickman and Rygiel (1996)
Follett (1991)
Bowmer et al. (1994)
Dierenfeld et al. (1993)
Gerhardt (1990)
Briegeretal. (1992)
Doebel et al. (2004)
Gerhardt et al. (1991)
Burton and Pinkney (1984)
Drndarski et al. (1990)
Gibbs and Miskiewicz (1995)
Burton etal. (1983, 1987a)
Graham et al. (1992)
G-3
-------
Gunderson et al. (1997)
Jin etal. (1997)
McLean et al. (1991)
Hall (1988)
Jorgensen and Heisinger
Mehrle et al. (1987)
Hall et al. (1984, 1987,
(1987)
Metcalf-Smith (1994)
1988,1992)
Karlson and Frankenberger
Micallef and Tyler (1989)
Hamilton et al. (1986, 2000)
(1990)
Mikac et al. (1985)
Harrison et al. (1990)
Kemble et al. (1994)
Miles and Tome (1997)
Hartwell etal. (1987ab, 1988,
Kennedy (1986)
Miller et al. (1996)
1997)
Kersten et al. (1991)
Misitano and Schiewe (1990)
Hatcher et al. (1992)
King and Cromartie (1986)
Moore (1988)
Haynes et al. (1997)
King etal. (1991, 1994)
Munawar and Legner (1993)
Hayward et al. (1996)
Klusek et al. (1993)
Muskett et al. (1985)
Hellou et al. (1996b)
Koh and Harper (1988)
Naddy et al. (1995)
Henebry and Ross (1989)
Koike et al. (1993)
Nielsen and Bjerregaard
Henny et al. (1989, 1990,
Krishnaja et al. (1987)
(1991)
1995)
Kruuk and Conroy (1991)
Norman et al. (1992)
Hildebrand et al. (1976)
Kuehl and Haebler (1995)
Nuutinen & Kukkonen
Hjeltnes and Julshman (1992)
Kuehl et al. (1994)
(1998)
Hockett and Mount (1996)
Kuss et al. (1995)
Oberbach and Hartfiel (1987,
Hodson (1990)
Landau et al. (1985)
1988)
Hoffman etal. (1988, 1991)
Livingston et al. (1991)
Oberbach et al. (1989)
Homziak et al. (1993)
Lobel et al. (1990)
Ohlendorf et al. (1989, 1990,
Hopkins et al. (2000)
Luoma and Phillips (1988)
1991)
Hopkins et al. (2004)
Lundquist et al. (1994)
Olson and Welsh (1993)
Hothem and Welsh (1994a)
Lyle (1986)
Peters et al.(1999)
Jackson (1988)
MacFarlane et al. (1986)
Phillips and Gregory (1980)
Jackson et al. (1990)
Mann and Fyfe (1988)
Pratt and Bowers (1990)
Jacquez et al. (1987)
Marcogliese et al. (1987)
Presser and Ohlendorf (1987)
Jay and Muncy (1979)
Marvin and Howell.
Prevot and Sayer-Gobillard
Jayasekera (1994)
(1997)Maureretal (1999)
(1986)
Jayasekera and Rossbach
McCloskey and Newman
Pritchard (1997)
(1996)
(1995)
Pyle et al. (2001)
Jenner and Bowmer (1990)
McCloskey et al. (1995)
Reash et al. (1988, in press)
(1992)
McCrea and Fischer (1986)
Rhodes and Burke (1996)
G-4
-------
Ribeyre et al. (1995)
Sorenson and Bauer (1983)
Weres et al. (1990)
Rice et al. (1995)
Specht et al. (1984)
White and Geitner (1996)
Riggs and Esch (1987)
Steele et al. (1992)
Wiemeyer et al. (1986)
Riggs et al. (1987)
Stemmer et al. (1990)
Wildhaber and Schmitt
Robertson et al. (1991)
Summers et al. (1995)
(1996)
Roper et al. (1997)
Thomas et al. (1980b)
Williams et al. (1989)
Rowe et al. (1996)
Timothy et al. (2001)
Wolfe et al. (1996)
Russell et al. (1994)
Trieff et al. (1995)
Wolfenberger (1987)
Ryther et al. (1979)
Turgeon and 0=Conner
Wong and Chau (1988)
Saiki and Jenings (1992)
(1991)
Wong et al. (1982)
Saiki and Ogle (1995)
Twerdok et al. (1997)
Wu et al. (1997)
Saleh et al. (1988)
Unsal (1987)
Yamaoka et al. (1994)
Seelye et al. (1982)
Van Metre and Gray (1992)
Zagatto et al. (1987)
Sevareid and Ichikawa
Wahl et al. (1994)
Zaidi et al. (1995)
(1983)
Wandan and Zabik (1996)
Zhang et al. (1996)
Skinner(1985)
Wang et al. (1992, 1995)
Somerville et al. (1987)
Welsh (1992)
Exposed enzymes, excised tissue or tissue extractor
Tripathi and Pandey (1985) and Heinz (1993b) used test organisms that had been previously
exposed to pollutants in food or water.
Albers et al. (1996)
Al-Sabti (1994, 1995)
Arvy et al. (1995)
Augier et al. (1993a, b)
Avery et al. (1996)
Baatrup (1989)
Baatrup and Dansher (1987)
Baatrup et al. (1986)
Babich et al. (1986, 1989)
Barrington et al. (1997)
Becker et al. (1995a,b)
Bell et al. (1984, 1985,
1986a,b, 1987ab)
Berges and Harrison (1995)
Blondin et al. (1988)
Boisson et al. (1996)
Bottino et al. (1984)
Braddon (1982)
Braddon-Galloway and
Balthrop (1985)
Bradford et al. (1994a,b)
Brandt et al. (1990)
Byletal. (1994)
Chandy and Patel (1985)
Chen et al. (1997)
Cheng et al. (1993)
Christensen and Tucker
(1976)
Dabbert and Powell (1993)
DeQuiroga et al. (1989)
Dierickx (1993)
Dietrich et al. (1987)
Dillio et al. (1986)
G-5
-------
Doyotte et al. (1997)
Drotar et al. (1987)
Dubois and Callard (1993)
Ebringer et al. (1996)
Engberg and Borsting (1994)
Engberg et al. (1993)
Eun et al. (1993)
Foltinova and Gajdosova
(1993)
Foltinova et al. (1994)
Freeman and Sanglang
(1977)
Grubor-Lajsic et al. (1995)
Hait and Sinha (1987)
Hanson (1997)
Heisinger and Scott (1985)
Heisinger and Wail (1989)
Henderson et al. (1987)
Henny and Bennett (1990)
Hoffman and Heinz (1988,
1998)
Hoffman etal. (1989, 1998)
Hoglund (1991)
Hontela et al. (1995)
Hsu et al. (1995)
Hsu and Goetz (1992)
Ishikawa et al. (1987)
James et al. (1993)
Jovanovic et al. (1995, 1997)
Kai et al. (1995)
Kedziroski et al. (1996)
Kelly etal. (1987)
Kralj and Stunja (1994)
Lalitha and Rani (1995)
Lan et al. (1995)
Lemaire et al. (1993)
Livingstone et al. (1992)
Low and Sin (1995, 1996)
Micallef and Tyler (1990)
Montagnese et al. (1993)
Murata et al. (1996)
Nakonieczny (1993)
Neuhierl and Boeck (1996)
Nigro (1994)
Nigro et al (1992)
Norheim and Borch-Iohnsen
(1990)
Norheim et al. (1991)
0=Brien et al. (1995)
Olson and Christensen (1980)
Overbaugh and Fall (1985)
Palmisano et al. (1995)
Patel et al. (1990)
Patel and Chandy (1987)
Perez Campo et al. (1990)
Perez-Trigo et al. (1995)
Phadnis et al. (1988)
Price and Harrison (1988)
Rady et al. (1992)
Rani and Lalitha (1996)
Regoli et al. (1997)
Schmidt et al. (1985)
Schmitt et al. (1993)
Segner et al. (1994)
Sen et al. (1995)
Shigeoka et al. (1990, 1991)
Siwicki et al. (1994)
Srivastava and Srivastava
(1995)
Sun et al. (1995)
Takedaetal. (1992a,b,(1993,
1997)
Treuthardt (1992)
Vazquez et al. (1994)
Veena et al. (1997)
Wise et al. (1993a,b)
Wong and Oliveira (1991b)
Yokota et al. (1988)
Test procedures test material or results were not adequately described by Botsford (1997),
Botsford et al. (1997, 1998), Bovee (1978), Gissel-Nielsen and Gissel-Nielsen (1973, 1978), Greenberg
and Kopec (1986), Mauk (2001), and Nassos et al. (1980) or when the test media contained an excessive
amount (>200 |ig/L) of EDTA (Riedel and Sanders (1996).
G-6
-------
Some data obtained from tests conducted with just one exposure concentration to evaluate acute
or chronic toxicity were not used (e.g., Bennett 1988; Heinz and Hoffman 1998; Munawar et al. 1987;
Pagano et al. 1986; Wolfenberger 1986).
Kaiser (1980) calculated the toxicities of selenium(IV) and selenium(VI) to Daphnia magna
based on physiochemical parameters. Kumar (1964) did not include a control treatment in the toxicity
tests. The daphnids were probably stressed by crowding in the tests reported be Schultz et al. (1980).
Siebers and Ehlers (1979) exposed too few test organisms as did Owsley (1984) in some tests.
Selenium Concentrations Reported in Wild Aquatic Organisms Were Insufficient to Calculate BAF
Abdel-Moati and Atta (1991)
Baldwin et al. (1996)
Brugmann and Lange (1988)
Adeloju and Young (1994)
Barghigiani (1993)
Brumbaugh and Walther
Aguirre et al. (1994)
Barghigiani et al. (1991)
(1991)
Akesson and Srikumar
Baron et al. (1997)
Burger(1992, 1994, 1995,
(1994)
Batley (1987)
1996, 1997a,b)
Aksnes et al. (1983)
Baumann and Gillespie
Burger and Gochfeld
Allen and Wilson (1990)
(1986)
(1992a,b, 1993, 1995 ab,
Ambulkar et al. (1995)
Baumann and May (1984)
1996,1997)
Amiard et al. (1991, 1993)
Beal (1974)
Burger et al. (1992a,b,c,1993,
Andersen and Depledge
Beck et al. (1997)
1994a,b)
(1997)
Beland et al. (1993)
Byrne and DeLeon (1986)
Andreev and Simeonov
Beliaeff et al. (1997)
Byrne et al. (1985)
(1992)
Bell and Cowey (1989)
Cantillo et al. (1997)
Angulo (1996)
Benemariya et al. (1991)
Capar and Yess (1996)
Arrula et al. (1996)
Berry et al. (1997)
Capelli et al. (1987, 1991)
Arway (1988)
Bertram et al. (1986)
Cappon (1984)
Ashton (1991)
Besseretal. (1994, 1993)
Cappon and Smith (1981)
Augieretal. (1991, 1993,
Birkner(1978)
(1982a,b)
1995a,b)
Boisson and Romeo (1996)
Cardellicchio (1995)
Augspurger et al. (1998)
Bowerman et al. (1994)
Carell et al. (1987)
Avery et al. (1996)
Braune et a. (1991)
Carter and Porter (1997)
Badsha and Goldspink (1988)
Brezina and Arnold (1977)
Caurant et al. (1994, 1996)
Baines and Fisher (2001)
Brugmann and Hennings
Chau and Riley (1965)
Baldwin and Maher (1997)
(1994)
Chiang et al. (1994)
G-7
-------
Chou and Uthe (1991)
Friberg (1988)
Hargrave et al. (1992)
Chvojka (1988)
Froslie etal. (1985, 1987)
Harrison and Klaverkamp
Chvojka et al. (1990)
Gabrashanske and Daskalova
(1990)
Clifford and Harrison (1988)
(1985)
Hasunuma et al. (1993)
Collins (1992)
Gabrashanska and Nedeva
Haynes et al. (1995)
Combs et al. (1996)
(1994)
Hein et al. (1994)
Cosson et al. (1988)
Galgan and Frank (1995)
Heiny and Tate (1997)
Courtney et al. (1994)
Garcia - Hermandez et al.
Heinz (1993a)
Cruwys et al. (1994)
(2000)
Heinz and Fitzgerald
Crutchfield (2000)
Giardina et al. (1997)
(1993a,b)
Cumbie and Van Horn (1978)
Gillespie and Baumann
Heit (1985)
Currey et al. (1992)
(1986)
Heit and Klusek (1985)
Custer and Hohman (1994)
Gochfeld (1997)
Heit etal. (1980, 1989)
Custer and Mitchell (1991,
Goede (1985, 1991, 1993a,b)
Hellou et al. (1992a,b)
1993)
Goede etal. (1989, 1993)
(1996a,b)
Custer et al. (1997)
Goede and DeBruin (1984,
Henny and Herron (1989)
Dabeka and McKenzie
1985)
Hodge et al. (1996)
(1991)
Goede and Wolterbeek
Hilton et al. (1982)
Davoren (1986)
(1993, 1994a,b)
Honda et al. (1986)
Deaker and Maher (1997)
Gras et al. (1992)
Hothem and Ohlendorf
Demon et al. (1988)
Greig and Jones (1976)
(1989)
Dietzetal. (1995, 1996)
Gutenmann et al. (1988)
Hothem and Welsh (1994b)
Doherty et al. (1993)
Gutierrez-Galindo et al.
Hothem and Zador (1995)
Elliott and Scheuhammer
(1994)
Hothem et al. (1995)
(1997)
Guven et al. (1992)
Houpt et al. (1988)
Eriksson et al. (1989)
Halbrook et al. (1996)
Hunter etal. (1995, 1997)
Evans et al. (1993)
Hall and Fisher (1985)
Ibrahim and Farrag (1992)
Felton rt al. (1990)
Hamilton and Waddell
Ibrahim and Mat (1995)
Felton et al. (1994)
(1994)
Ishikawa et al. (1993)
Fitzsimons et al. (1995)
Hamilton and Wiedmeyer
Itano et al. (1984, 1985a,b)
Focardi et al. (1985, 1988)
(1990)
Jarman et al. (1996)
Fowler (1986)
Hansen et al. (1990)
Johns et al. (1988)
Fowler etal. (1975, 1985)
Hardiman and Pearson
Johnson (1987)
France(1987)
(1995)
Jop et al. (1997)
G-8
-------
Jorhem et al. (1994)
Lobeletal. (1989, 1991,
Nadkarni and Primack (1993)
Julshamn et al. (1987)
1992a,b)
Nakamoto and Hassler
Kai et al. (1986a,b, 1988,
Lonzarich et al. (1992)
(1992)
1992a,b, 1996)
Lourdes et al. (1990)
Narasaki and Cao (1996)
Kaiser et al. (1979)
Lowe et al. (1985)
Navarrete et al. (1990)
Kalas et al. (1995)
Lucas et al. (1970)
Nettleton et al. (1990)
Kidwell et al. (1995)
Lytle and Lytle (1982)
Nicola et al. (1987)
Koeman et al. (1973)
Mackey et al. (1996)
Nielsen and Dietz (1990)
Kovacs et al. (1984)
Maher (1987)
Norheim (1987)
Krogh and Scanes(1997)
Maher et al. (1992, 1997)
Norheim et al. (1992)
Krushevska et al. (1996)
Mann et al. (1988)
Norrgren et al. (1993)
Lakshmanan and Stephen
Mason et al. (2000)
Norstrom et al. (1986)
(1994)
Masuzawa et al. (1988)
0=Conner (1996)
Lalitha et al. (1994)
Matsumoto (1991)
0=Shea et al. (1984)
LamLeung et al. (1991)
Maven et al. (1995)
Ober et al. (1987)
Lan et al. (1994a,b)
May and McKinney (1981)
Oehlenschlager (1997)
Langlois and Langis (1995)
Mcdowell et al. (1995)
Ohlendorf (1986)
Larsen and Stuerup (1994)
McKenzie-Parnell et al.
Ohlendorf and Harrison
Larsen et al. (1997)
(1988)
(1986)
Lauchli (1993)
Meador et al. (1993)
Ohlendorf and Marois (1990)
Law et al. (1996)
Mehrle et al. (1982)
Ohlendorf et al. (1986a,b,
Lee and Fisher (1992a,b,
Meltzer et al. (1993)
1987, 1988a,b)
1993)
Metcalfe-Smith et al. (1992,
Okazaki and Panietz (1981)
Leighton and Wobeser
1996)
Ostapczuk et al. (1997)
(1994)
Michot et al. (1994)
Pakkala et al. (1972)
Leland and Scudder (1990)
Mills etal. (1993)
Pal et al. (1997) Palawski et
Lemly (1985a, 1994)
Moharram et al. (1987)
al. (1991)
Leonzio et al. (1986, 1989,
Moller (1996)
Palmer-Locarnini and Presley
1992)
Mora and Anderson (1995)
(1995)
Leskinen et al. (1986)
Morera et al. (1997)
Paludan-Miller et al. (1993)
Lietal. (1996)
Muir et al. (1988)
Papadopoulou and Andreotis
Lie et al. (1994)
Mutanen et al. (1986)
(1985)
Liu et al. (1987)
Park and Presley (1997)
Lizama et al. (1989)
Park et al. (1994)
G-9
-------
Paveglio et al. (1994)
Shen et al. (1997)
TranVan and Teherani (1988)
Payer and Runkel (1978)
Shirasaki et al. (1996)
Trocine and Trefry (1996)
Payer et al. (1976)
Shultz and Ito (1979)
Uthe and Bigh (1971)
Pennington et al. (1982)
Simopoulos (1997)
Vanderstoep et al. (1990)
Presley et al. (1990)
Skaare etal. (1990, 1994)
Varanasi et al. (1993, 1994)
Quevauviller et al. (1993a,b)
Smith and Flegal (1989)
Vitaliano and Zdanowicz
Ramos et al. (1992)
Smith et al. (1992)
(1992)
Rao et al. (1996)
Sorensen (1988)
Vlieg (1990)
Reinfelder and Fisher (1991)
Sorensen and Bauer
Vlieg etal. (1993)
Reinfelder et al. (1993, 1998)
(1984a,b) Sorensen and
Vos etal. (1986)
Renzoni et al. (1986)
Bjerregaard (1991)
Waddell and May (1995)
Riget et al. (1996)
Sorensen et al. (1982, 1983,
Wagemann (1988)
Risenhoover(1989)
1984)
Wagemann and Stewart
Roditi (2000)
Southworth et al. (2000)
(1994)
Roux et al. (1994)
Sparling and Lowe (1996)
Wagemann et al. (1988)
Ruelle and Keenlyne (1993)
Speyer(1980)
(1996) Walsh etal. (1977)
Sager and Cofield (1984)
Steimle et al. (1994)
Wang (1996)
Saiki (1986 ab, 1987, 1990)
Stoeppler et al. (1988)
Ward and Flick (1990)
Saiki and Lowe (1987)
Stone et al. (1988)
Warren et al. (1990)
Saiki and May (1988)
Stripp et al. (1990)
Weber (1985)
Saiki and Palawski (1990)
Sundarrao et al. (1991)
Welsh and Maughan (1994)
Saiki et al. (1992, 1993)
(1992)
Wen etal. (1997)
Sanders and Gilmour (1994)
Svensson et al. (1992)
Wenzel and Gabrielsen
Scanes(1997)
Tabaka et al. (1996)
(1995)
Scheuhammer et al. (1988)
Talbot and Chang (1987)
Whyte and Boutillier (1991)
Schantz et al. (1997)
Tallandini et al. (1996)
Williams et al. (1994)
Schmitt and Brumbaugh
Tan and Marshall (1997)
Wilson etal. (1992, 1997)
(1990)
Tang et al. (1997)
Winger and Andreasen
Schramel and Xu (1991)
Tao et al. (1993)
(1985)
Schuler et al. (1990)
Teherani (1987)
Winger etal. (1984, 1990)
Scott and Latshaw (1993)
Teigen et al. (1993)
Woock and Summers (1984)
Secoretal. (1993)
Thomas et al. (1999)
Wren et al. (1987)
Seelye et al. (1982)
Tilbury et al. (1997)
Wu and Huang (1991)
Sharif et al. (1993)
Topcuoglu et al. (1990)
Yamaoka et al. (1996)
G-10
-------
Yamazaki et al. (1996)
Yoshida and Yasumoto
(1987)
Zatta et al. (1985)
Zeisleretal. (1988, 1993)
Zhou and Liu (1997)
G-ll
-------
APPENDIX H: CALCULATION OF EF VALUES
H-l
-------
EPA calculated EF values by searching its database of selenium measurements and identifying all the selenium measurements from algae,
detritus, or sediment. EPA then searched for corresponding water column measurements from samples collected at the same aquatic site within
one year of the particulate sample. If more than one water measurement was available for any given particulate measurement, the median was
used. For each of these matched pairs of particulate and water measurements, EPA calculated the ratio of particulate concentration to water
concentration. If more than one ratio for any given category of particulate material (algae, detritus, or sediment) was calculated at an aquatic site,
EPA used the median ratio. The geometric mean of the algae, detritus, and sediment ratios was used as the site EF. Because there were at most
only 3 possible values (one for algae, one for detritus, and one for sediment), EPA used the geometric mean in order to reduce the potential for one
of the values to have excessive influence on the final site value. Sites with insufficient data to fulfill these criteria are left blank.
EPA evaluated differences in bioaccumulation between different categories of aquatic systems by analyzing EF values for different
categories. EPA sequentially consolidated categories and examined differences in the distribution of EF values between categories. See text for a
complete description of this analysis.
Reference
Silo description
Silo II)
Spocil'ic
\\;i(crbo(l\
1J |)0 -
ori;iiii;il
SpocN'ic
\\;ilcrbo(l\
Ij |)0 -
1 .enlie or
l.olic
(m»/k»)
^ iIi-ii'iiiin
(niii/kji)
C«,
imii/kii)
( II'l U'lll.llr
(mji/kii)
c
* WJlliT
(Uii/I.)
siio 1:1
(L/E)
Birkner 1978
East Allen Reservoir,
Medicine Bow WY
20
Reservoir
Lentic
3.00
41.00
11.09
4.80
2.31
Birkner 1978
Galett Lake, Laramie WY
7
Lake
Lentic
0.18
2.80
0.70
0.80
0.88
Birkner 1978
Larimer Highway 9 Pond,
Fort Collins CO
30
Pond
Lentic
15.50
47.30
27.08
15.90
1.70
Birkner 1978
Meeboer Lake, Laramie
WY
3
Lake
Lentic
0.10
0.30
0.17
0.30
0.58
Birkner 1978
Miller's Lake, Wellington
CO
22
Lake
Lentic
4.60
44.00
14.23
6.00
2.37
Birkner 1978
Sweitzer Lake, Delta CO
27
Lake
Lentic
10.35
6.50
8.20
9.40
0.87
Birkner 1978
Twin Buttes Reservoir,
Laramie WY
23
Reservoir
Lentic
7.80
10.80
9.18
7.60
1.21
H-2
-------
Rol'oronoo
Silo riosoriplion
Silo II)
Spooil'io
1J |)0 -
oi'i^iiiiil
Spooil'io
(\ po -
1 .oiilio or
1 .olio
^ ilrlnlllN
(Iiiii/kii)
<¦
(nili/kii)
c
y IMI'I li'llhllr
(niii/kii)
t
x U.lIlT
(US'/I.)
siio 1:1
(L/k)
Bowie et al.
1996
Hyco Reservoir
Reservoir
Lentic
27.00
27.00
11.50
2.35
Butler et al.
1993
Navajo Reservoir, Piedra
River Arm, near La Boca
N2
Reservoir
Lentic
2.65
0.60
1.26
1.00
1.26
Butler et al.
1997
Large pond on Dove
Creek
DCP1
Pond
Lentic
1.00
2.10
1.45
2.00
0.72
Butler et al.
1997
Large pond south of G
Road, southern Mancos
Valley
MNP2
Pond
Lentic
5.40
6.70
6.01
3.00
2.00
Butler et al.
1997
Pond downstream from
site MNP2, southern
Mancos Valley
MNP3
Pond
Lentic
4.50
5.90
5.15
1.00
5.15
Butler et al.
1997
Pond on Cahone Canyon,
west of 1 5 Road
CHP
Pond
Lentic
4.00
2.10
2.90
5.00
0.58
Butler et al.
1997
Pond on Woods Canyon at
15 Road
WCP
Pond
Lentic
2.30
3.20
2.71
3.00
0.90
Butler et al.
1997
West pond at CC Road
PVP1
Pond
Lentic
1.50
1.40
1.45
2.00
0.72
Grasso et al.
1995
Arapahoe Wetlands Pond
17
Pond
Lentic
1.87
0.40
0.86
1.00
0.86
Lemly 1985
Badin Lake
Lake
Lentic
7.70
2.07
3.99
0.32
12.48
Lemly 1985
Belews Lake
Lake
Lentic
44.10
8.27
19.10
10.91
1.75
Lemly 1985
High Rock Lake
Lake
Lentic
6.20
1.80
3.34
0.67
4.99
Muscatello and
Janz 2009
Vulture Lake
Lake
Lentic
0.35
0.54
0.43
0.43
1.01
Orr et al. 2006
Barns Lake Wetland
BLW
Lake
Lentic
4.40
2.00
2.97
0.50
5.93
H-3
-------
Rol'oronoo
Silo riosoriplion
Silo II)
Spooil'io
1J |)0 -
oi'i^iiiiil
Spooil'io
(\ po -
1 .oiilio or
1 .olio
^ ilrlnlllN
(Iiiii/kii)
C
(nili/kii)
c
y IMI'I li'llhllr
(niii/kii)
t
x U.lIlT
(US'/I.)
siio i:i
(L/k)
Orr et al. 2006
Fording River Oxbow
FRO
Oxbow
Lentic
5.55
7.90
6.62
5.04
1.37
Orr et al. 2006
Fording Settling Pond
(Clode Pond)
FSP
Pond
Lentic
5.49
2.80
3.92
42.99
0.09
Orr et al. 2006
Goddard Marsh
GM
Marsh
Lentic
3.21
26.00
9.14
90.95
0.10
Orr et al. 2012
Clode Pond 11
CL11
Pond
Lentic
25.80
25.80
36.10
0.71
Orr et al. 2012
Elk Lakes 14
EL14
Lake
Lentic
0.66
0.66
0.40
1.64
Orr et al. 2012
Flathead Wetland 17
FL17
Marsh
Lentic
1.42
1.42
0.20
7.10
Orr et al. 2012
Fording River Oxbow 10
FO10
Oxbow
Lentic
67.31
67.31
50.10
1.34
Orr et al. 2012
Goddard Marsh 13
G013
Marsh
Lentic
18.15
18.15
16.30
1.11
Orr et al. 2012
Henretta Lake 27
HE27
Lake
Lentic
4.30
4.30
8.60
0.50
Saiki and Lowe
1987
Kesterson Pond 11
Pond
Lentic
18.15
47.95
8.56
19.53
38.60
0.51
Saiki and Lowe
1987
Kesterson Pond 2
Pond
Lentic
152.70
44.65
34.82
61.92
195.85
0.32
Saiki and Lowe
1987
Kesterson Pond 8
Pond
Lentic
136.50
92.00
6.05
42.34
70.35
0.60
Saiki and Lowe
1987
Volta Pond 26
Pond
Lentic
0.42
1.01
0.29
0.50
0.53
0.93
Saiki and Lowe
1987
Volta Pond 7
Pond
Lentic
1.39
0.39
0.74
0.63
1.17
Schuler et al.
1990
Kesterson National
Wildlife Refuge
Kesterson
Pond 7
Pond
Lentic
87.10
5.90
22.67
100.00
0.23
H-4
-------
Rol'oronoo
Silo riosoriplion
Silo II)
Spooil'io
1J |)0 -
oi'i^iiiiil
Spooil'io
(\ po -
1 .oiilio or
1 .olio
^ ilrlnlllN
(Iiiii/kii)
<¦
(nili/kii)
c
y IMI'I li'llhllr
(niii/kii)
t
x U.lIlT
(US'/I.)
siio 1:1
(L/k)
Schuler et al.
1990
Kesterson National
Wildlife Refuge
Kesterson
Pond 2
Pond
Lentic
52.50
9.30
22.10
90.00
0.25
Schuler et al.
1990
Kesterson National
Wildlife Refuge
Kesterson
Pond 11
Pond
Lentic
53.70
11.50
24.85
40.00
0.62
Stephens et al.
1988
Marsh 4720
*
Marsh
Lentic
2.10
4.20
2.97
31.00
0.10
Butler et al.
1991
Uncompahgre River at
Colona
4
River
Lotic
0.95
0.95
1.50
0.63
Butler et al.
1993
Spring Cr. at La Boca
SP2
Creek
Lotic
1.60
0.50
0.89
5.00
0.18
Butler et al.
1995
Cahone Canyon at
Highway 666
CH
Creek
Lotic
2.50
4.30
3.28
12.00
0.27
Butler et al.
1995
Hartman Draw near
mouth, at Cortez
HD2
Draw
Lotic
0.45
0.20
0.30
2.00
0.15
Butler et al.
1995
McElmo Cr. atHwy. 160,
near Cortez
ME1
Creek
Lotic
1.80
1.80
2.00
0.90
Butler et al.
1995
McElmo Cr. downstream
from Alkali Cyn.
ME2
Creek
Lotic
1.11
1.10
1.10
3.00
0.37
Butler et al.
1995
McElmo Cr. downstream
from Yellow Jacket Cyn.
ME4
Creek
Lotic
1.04
0.50
0.72
6.00
0.12
Butler et al.
1995
McElmo Cr .upstream
from Yellow Jacket Cyn.
ME3
Creek
Lotic
0.82
0.40
0.57
6.00
0.10
Butler et al.
1995
Navajo Wash near
Towaoc
NW
Wash
Lotic
3.45
1.60
2.35
12.00
0.20
Butler et al.
1995
San Juan River at Four
Comers
SJ1
River
Lotic
0.52
0.30
0.39
1.50
0.26
Butler et al.
1995
San Juan River at Mexican
Hat Utah
SJ3
River
Lotic
0.94
0.20
0.43
1.50
0.29
Butler et al.
1995
Woods Cyn. Near Yellow
Jacket
WC
Creek
Lotic
3.30
1.50
2.22
5.50
0.40
H-5
-------
Rol'oronoo
Silo riosoriplion
Silo II)
Spooil'io
1J |)0 -
oi'i^iiiiil
Spooil'io
(\ po -
1 .oiilio or
1 .olio
^ ilrlnlllN
(Iiiii/kii)
C
(nili/kii)
c
y IMI'I li'llhllr
(niii/kii)
t
x U.lIlT
(US'/I.)
siio i:i
(L/k)
Butler et al.
1997
Cahone Canyon at
Highway 666
CHI
Creek
Lotic
2.05
2.05
10.50
0.20
Butler et al.
1997
Mud Creek at Highway
32, near Cortez
MUD2
Creek
Lotic
1.30
1.30
18.50
0.07
Butler et al.
1997
Tributary of Cahone
Canyon at 13 Road
CH2
Creek
Lotic
1.75
1.75
5.50
0.32
Butler et al.
1997
Tributary of Yellow Jacket
Canyon at Highway 666
YJ1
Creek
Lotic
1.85
1.85
7.00
0.26
Butler et al.
1997
Unnamed tributary of Cow
Canyon at 8 Road
COW
Creek
Lotic
1.45
1.45
3.50
0.41
Butler et al.
1997
Unnamed tributary of
Cross Canyon upstream
from Alkali Canyon
CCTR
Creek
Lotic
1.75
1.75
4.50
0.39
Casey 2005
Deerlick Creek
Creek
Lotic
1.00
0.20
0.45
0.20
2.24
Casey 2005
Luscar Creek
Creek
Lotic
5.50
3.20
2.40
3.48
10.70
0.33
Formation
2012
Crow Creek - 1A
CC-1A
Creek
Lotic
3.64
1.20
2.09
2.45
0.80
Formation
2012
Crow Creek - 3A
CC-3A
Creek
Lotic
3.10
0.83
1.60
2.20
0.81
Formation
2012
Crow Creek - CC150
CC-150
Creek
Lotic
1.20
0.63
0.87
0.80
1.04
Formation
2012
Crow Creek - CC350
CC-350
Creek
Lotic
1.50
0.70
1.02
0.86
1.16
Formation
2012
Crow Creek - CC75
CC-75
Creek
Lotic
1.01
0.54
0.74
0.52
1.19
Formation
2012
Deer Creek
DC-600
Creek
Lotic
4.55
1.40
2.52
1.62
1.55
H-6
-------
Rol'oronoo
Silo riosoriplion
Silo II)
Spooil'io
1J |)0 -
oi'i^iiiiil
Spooil'io
Ij po -
1 .oiilio or
1 .olio
(nig/kg)
^ ilrlnlllN
(Iiiii/kii)
<¦
c
y |MI'I li'llhlll'
(mii/kii)
t
x U.lIlT
(US'/I.)
siio i:i-
(L/k)
Formation
2012
Hoopes Spring - HS
HS
Spring
Lotic
12.00
2.30
5.25
20.95
0.24
Formation
2012
Hoopes Spring - HS3
HS-3
Spring
Lotic
12.00
7.00
9.17
17.05
0.54
Formation
2012
Sage Creek - LSV2C
LSV-2C
Creek
Lotic
8.09
4.60
6.10
13.80
0.45
Formation
2012
Sage Creek - LSV4
LSV-4
Creek
Lotic
9.56
3.60
5.87
8.45
0.69
Formation
2012
South Fork Tincup Cr.
SFTC-1
Creek
Lotic
0.73
0.31
0.47
0.44
1.32
Golder 2011;
Teck Coal
2013
McLeod River below
Cheviot Creek
MR-2
River
Lotic
1.47
1.47
2.38
0.62
Golder 2011;
Teck Coal
2013
McLeod River below
Luscar Dreek
MR-6
River
Lotic
0.86
0.86
4.29
0.20
Golder 2011;
Teck Coal
2013
McLeod River below
Whitehorse Creek
MR-4
River
Lotic
0.68
0.68
1.07
0.64
Golder 2011;
Teck Coal
2013
McLeod River reference
MR-1
River
Lotic
0.75
0.75
0.30
2.50
Golder 2011;
Teck Coal
2013
Prospect Creek far field
PC-3
Creek
Lotic
0.37
0.37
0.63
0.59
Golder 2011;
Teck Coal
2013
Prospect Creek reference
PC-1
Creek
Lotic
0.86
0.86
0.40
2.15
Hamilton and
Buhl 2004
lower East Mill Creek
LEMC
Creek
Lotic
25.70
38.90
31.62
24.00
1.32
H-7
-------
Rol'oronoo
Silo riosoriplion
Silo II)
Spooil'io
1J |)0 -
oi'i^iiiiil
Spooil'io
(\ po -
1 .oiilio or
1 .olio
^ ilrlnlllN
(Iiiii/kii)
C
(nili/kii)
c
y IMI'I li'llhllr
(niii/kii)
t
x U.lIlT
(US'/I.)
siio 1:1
(L/k)
McDonald and
Strosher 1998
Elk R. above Cadorna Cr.
(745)
ER 745
River
Lotic
0.31
1.28
0.63
0.10
6.30
McDonald and
Strosher 1998
Elk R. above Fording R.
ER 750
River
Lotic
0.78
0.70
0.74
0.40
1.85
McDonald and
Strosher 1998
Fording R. above Swift
Cr. (746)
ER 746
River
Lotic
1.56
2.41
1.94
8.60
0.23
McDonald and
Strosher 1998
Michel Cr. at Highway 3
ER 751
Creek
Lotic
1.26
2.32
1.71
7.10
0.24
Orr et al. 2006
Alexander Creek
AC
Creek
Lotic
4.49
0.90
2.01
0.90
2.23
Orr et al. 2006
Fording River
FR
River
Lotic
3.27
2.10
2.62
20.10
0.13
Orr et al. 2006
Line Creek
LC
Creek
Lotic
2.19
2.10
2.14
20.90
0.10
Orr et al. 2012
Elk River 1
ELI
River
Lotic
2.30
2.30
4.20
0.55
Orr et al. 2012
Elk River 12
EL12
River
Lotic
2.00
2.00
0.75
2.67
Orr et al. 2012
Fording River 23
F023
River
Lotic
6.35
6.35
30.60
0.21
Orr et al. 2012
Michel Creek 2
MI2
Creek
Lotic
2.10
2.10
7.40
0.28
Presser and
Luoma 2009
Upper Peters canyon (dry)
UPCW
dry
Wash
Lotic
1.20
0.60
0.85
3.20
0.27
Saiki and Lowe
1987
San Luis Drain
Drain
Lotic
67.00
275.00
79.90
113.76
316.50
0.36
Saiki and Lowe
1987
Volta Wasteway
Wasteway
Lotic
0.87
2.03
0.24
0.76
0.74
1.03
Saiki et al.
1993
Mud Slough at Gun Club
Road
GT5
Slough
Lotic
4.50
14.95
8.20
6.00
1.37
H-8
-------
Rol'oronoo
Silo riosoriplion
Silo II)
Spooil'io
1J |)0 -
oi'i^iiiiil
Spooil'io
(\ po -
1 .oiilio or
1 .olio
(
^ ilrlnlllN
C
(nili/kii)
c
y |MI'I li'llhlll'
(niii/kii)
t
x w.ili-r
(HSi/l.)
siio i:i-
(L/k)
Saiki et al.
1993
Salt Slough at the San
Luis National Wildlife
Refuge
GT4
Slough
Lotic
1.39
8.40
3.42
8.00
0.43
Saiki et al.
1993
San Joaquin R. above
Hills Ferry Road
SJR2
River
Lotic
1.25
5.00
2.50
7.00
0.36
Saiki et al.
1993
San Joaquin R. at Durham
Ferry State Recereation
Area
SJR3
River
Lotic
0.45
1.25
0.75
1.00
0.75
Stephens et al.
1988
Drain J3
*
Drain
Lotic
24.00
48.00
33.94
110.00
0.31
H-9
-------
APPENDIX I: Observed Versus Predicted
Egg-Ovary Concentrations
1-1
-------
The following table includes data for 317 individual fish tissue selenium measurements from the 64 sites where EFs could be calculated.
Observed egg-ovary fish tissue measurements were compared to predicted egg-ovary fish tissue measurements calculated using equation 22 of the
main text, also shown here for convenience.
= C„„. x TTF«-™'* xEFxCF (Equation 22)
These data were used to generate the observed to predicted egg-ovary concentration Figure 6.3 of the main text. When the measured tissue
type was either muscle or whole body, it was converted to egg-ovary using taxa specific conversion factors. The predicted and measured
concentrations are highly correlated (r = 0.82, t(3i5) = 25.30, P < 0.001).
Study
Site
Species
Site
\Y siler
(MB/I)
i:i
CI
I'red.
i:/o
(Illii/lvii)
Obs.
i:/o
(ms/ks)
Ohs.
tissue
type
Birkner 1978
East Allen Reservoir, Medicine Bow WY
Iowa darter
4.80
2.31
2.87
1.45
46.14
52.68
WB
Birkner 1978
Galett Lake, Laramie WY
Iowa darter
0.80
0.88
2.87
1.45
2.91
3.05
WB
Birkner 1978
Larimer Highway 9 Pond, Fort Collins
CO
northern plains
killifish
15.90
1.70
2.44
1.20
79.04
68.71
WB
Birkner 1978
Meeboer Lake, Laramie WY
northern plains
killifish
0.30
0.58
2.44
1.20
0.51
9.22
WB
Birkner 1978
Miller's Lake, Wellington CO
fathead minnow
6.00
2.37
2.78
1.40
55.31
15.37
WB
Birkner 1978
Miller's Lake, Wellington CO
Iowa darter
6.00
2.37
2.87
1.45
59.18
33.38
WB
Birkner 1978
Sweitzer Lake, Delta CO
northern plains
killifish
9.40
0.87
2.44
1.20
23.94
38.18
WB
Birkner 1978
Sweitzer Lake, Delta CO
fathead minnow
9.40
0.87
2.78
1.40
31.89
110.38
WB
Birkner 1978
Twin Buttes Reservoir, Laramie WY
northern plains
killifish
7.60
1.21
2.44
1.20
26.79
27.65
WB
Birkner 1978
Twin Buttes Reservoir, Laramie WY
fathead minnow
7.60
1.21
2.78
1.40
35.69
48.20
WB
Birkner 1978
Twin Buttes Reservoir, Laramie WY
Iowa darter
7.60
1.21
2.87
1.45
38.18
60.81
WB
Bowie et al. 1996
Hyco Reservoir
bluegill
11.50
2.35
2.00
2.13
114.97
87.47
WB
Butler etal. 1991
Uncompahgre River at Colona
flannelmouth sucker
1.50
0.63
1.52
1.41
2.03
2.40
WB
Butler etal. 1991
Uncompahgre River at Colona
white sucker
1.50
0.63
1.58
1.38
2.07
7.32
WB
Butler etal. 1991
Uncompahgre River at Colona
bluehead sucker
1.50
0.63
1.24
1.82
2.13
3.27
WB
Butler etal. 1991
Uncompahgre River at Colona
mottled sculpin
1.50
0.63
2.72
1.45
3.72
3.77
WB
1-2
-------
SiiiiIy
Site
Species
Sile
Wilier
(us/l)
i:i
d/ii)
ii
CI
I'reil.
i:/o
Obs.
i:/o
Ohs.
tissue
type
Bullcr cL al. 1991
Incompah^rc Ri\ cr ul Colona
molllcd sc ill pin
1.5U
0.0 3
2.72
1.45
3.72
6.39
WB
Butler etal. 1991
Uncompahgre River at Colona
brown trout
1.50
0.63
2.78
1.45
3.80
4.77
WB
Butler etal. 1991
Uncompahgre River at Colona
brown trout
1.50
0.63
2.78
1.45
3.80
5.06
WB
Butler etal. 1991
Uncompahgre River at Colona
rainbow trout
1.50
0.63
2.33
2.44
5.39
6.88
WB
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
brown trout
1.00
1.26
2.78
1.45
5.08
6.20
E-0
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
channel catfish
1.00
1.26
1.35
1.45
2.47
2.32
WB
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
bullhead
1.00
1.26
1.62
1.45
2.96
2.03
WB
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
bullhead
1.00
1.26
1.62
1.45
2.96
3.05
WB
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
common carp
1.00
1.26
1.58
1.92
3.82
6.15
WB
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
common carp
1.00
1.26
1.58
1.92
3.82
5.19
WB
Butler etal. 1993
Navajo Reservoir, Piedra River Arm, near
La Boca
common carp
1.00
1.26
1.58
1.92
3.82
6.15
WB
Butler etal. 1993
Spring Cr. at La Boca
white sucker
5.00
0.18
1.58
1.38
1.96
4.83
WB
Butler etal. 1993
Spring Cr. at La Boca
bluehead sucker
5.50
0.18
1.24
1.82
2.22
12.91
WB
Butler etal. 1993
Spring Cr. at La Boca
speckled dace
5.00
0.18
1.36
1.95
2.37
23.45
WB
Butler etal. 1993
Spring Cr. at La Boca
fathead minnow
5.00
0.18
2.78
1.40
3.48
11.46
WB
Butler etal. 1993
Spring Cr. at La Boca
brown trout
5.00
0.18
2.78
1.45
3.60
1.74
WB
Butler etal. 1993
Spring Cr. at La Boca
fathead minnow
5.50
0.18
2.78
1.40
3.83
8.38
WB
Butler etal. 1993
Spring Cr. at La Boca
brown trout
5.50
0.18
2.78
1.45
3.96
4.92
WB
Butler etal. 1995
Hartman Draw near mouth, at Cortez
sucker
2.00
0.15
1.25
1.41
0.53
1.07
WB
Butler etal. 1995
Hartman Draw near mouth, at Cortez
sucker
2.00
0.15
1.25
1.41
0.53
0.96
WB
Butler etal. 1995
Hartman Draw near mouth, at Cortez
flannelmouth sucker
2.00
0.15
1.52
1.41
0.64
0.69
WB
Butler etal. 1995
Hartman Draw near mouth, at Cortez
flannelmouth sucker
2.00
0.15
1.52
1.41
0.64
0.76
WB
Butler etal. 1995
Hartman Draw near mouth, at Cortez
flannelmouth sucker
2.00
0.15
1.52
1.41
0.64
0.87
WB
Butler etal. 1995
Hartman Draw near mouth, at Cortez
flannelmouth sucker
2.00
0.15
1.52
1.41
0.64
1.35
WB
Butler etal. 1995
Hartman Draw near mouth, at Cortez
fathead minnow
2.00
0.15
2.78
1.40
1.16
2.10
WB
1-3
-------
iws
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
Site
Species
Sile
Wilier
(ua/l)
i:i
d/ii)
TIP
CI
I'reil.
i:/o
Ohs.
i:/o
I larlman Draw near mouth, at Corky
fathead minnow
"• oil
U.15
:.7s
1.4U
1.10
2.24
McElmo Cr. at Hwy. 160, near Cortez
speckled dace
2.00
0.90
1.36
1.95
4.77
12.51
McElmo Cr. at Hwy. 160, near Cortez
fathead minnow
2.00
0.90
2.78
1.40
7.00
7.82
McElmo Cr.
Cyn.
downstream from Alkali
flannelmouth sucker
3.00
0.37
1.52
1.41
2.37
2.25
McElmo Cr.
Cyn.
downstream from Alkali
flannelmouth sucker
3.00
0.37
1.52
1.41
2.37
1.97
McElmo Cr.
Cyn.
downstream from Alkali
flannelmouth sucker
3.00
0.37
1.52
1.41
2.37
2.82
McElmo Cr.
Cyn.
downstream from Alkali
flannelmouth sucker
3.00
0.37
1.52
1.41
2.37
3.10
McElmo Cr.
Cyn.
downstream from Alkali
bluehead sucker
3.00
0.37
1.24
1.82
2.49
1.51
McElmo Cr.
Cyn.
downstream from Alkali
bluehead sucker
3.00
0.37
1.24
1.82
2.49
2.36
McElmo Cr.
Cyn.
downstream from Alkali
speckled dace
3.00
0.37
1.36
1.95
2.92
11.92
McElmo Cr.
Cyn.
downstream from Alkali
fathead minnow
3.00
0.37
2.78
1.40
4.29
6.71
McElmo Cr.
Jacket Cyn.
downstream from Yellow
flannelmouth sucker
6.00
0.12
1.52
1.41
1.54
2.11
McElmo Cr.
Jacket Cyn.
downstream from Yellow
flannelmouth sucker
6.00
0.12
1.52
1.41
1.54
1.83
McElmo Cr.
Jacket Cyn.
downstream from Yellow
flannelmouth sucker
6.00
0.12
1.52
1.41
1.54
2.68
McElmo Cr.
Jacket Cyn.
downstream from Yellow
flannelmouth sucker
6.00
0.12
1.52
1.41
1.54
3.38
McElmo Cr.
Jacket Cyn.
downstream from Yellow
flannelmouth sucker
6.00
0.12
1.52
1.41
1.54
4.23
McElmo Cr.
Jacket Cyn.
downstream from Yellow
common carp
6.00
0.12
1.58
1.92
2.18
7.49
McElmo Cr.
Jacket Cyn.
downstream from Yellow
common carp
6.00
0.12
1.58
1.92
2.18
7.11
1-4
-------
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
Site
Species
Sile
Wilier
(ua/l)
i:i
d/ii)
TIP
CI
I'reil.
i:/o
(mg/k»)
Ohs.
i:/o
(m»/k»)
McElmo Cr. downstream from Yellow
Jacket Cyn.
common carp
6.00
0.12
1.58
1.92
2.18
7.30
McElmo Cr. downstream from Yellow
Jacket Cyn.
fathead minnow
6.00
0.12
2.78
1.40
2.80
1.96
McElmo Cr. downstream from Yellow
Jacket Cyn.
fathead minnow
6.00
0.12
2.78
1.40
2.80
8.24
McElmo Cr. downstream from Yellow
Jacket Cyn.
red shiner
6.00
0.12
2.27
1.95
3.20
9.97
McElmo Cr.upstream from Yellow Jacket
Cyn.
flannelmouth sucker
6.00
0.10
1.52
1.41
1.23
2.40
McElmo Cr.upstream from Yellow Jacket
Cyn.
flannelmouth sucker
6.00
0.10
1.52
1.41
1.23
2.40
McElmo Cr.upstream from Yellow Jacket
Cyn.
flannelmouth sucker
6.00
0.10
1.52
1.41
1.23
2.96
McElmo Cr.upstream from Yellow Jacket
Cyn.
flannelmouth sucker
6.00
0.10
1.52
1.41
1.23
3.38
McElmo Cr.upstream from Yellow Jacket
Cyn.
flannelmouth sucker
6.00
0.10
1.52
1.41
1.23
5.07
McElmo Cr.upstream from Yellow Jacket
Cyn.
bluehead sucker
6.00
0.10
1.24
1.82
1.29
3.27
McElmo Cr.upstream from Yellow Jacket
Cyn.
bluehead sucker
6.00
0.10
1.24
1.82
1.29
3.09
McElmo Cr.upstream from Yellow Jacket
Cyn.
bullhead
6.00
0.10
1.62
1.45
1.34
4.35
McElmo Cr.upstream from Yellow Jacket
Cyn.
speckled dace
6.00
0.10
1.36
1.95
1.52
5.47
McElmo Cr.upstream from Yellow Jacket
Cyn.
speckled dace
6.00
0.10
1.36
1.95
1.52
13.68
McElmo Cr.upstream from Yellow Jacket
Cyn.
speckled dace
6.00
0.10
1.36
1.95
1.52
10.75
McElmo Cr.upstream from Yellow Jacket
Cyn.
common carp
6.00
0.10
1.58
1.92
1.74
8.45
1-5
-------
SiiiiIy
Site
Species
Sile
Wilier
(us/l)
i:i
d/ii)
ii
CI
I'reil.
i:/o
Obs.
i:/o
Ohs.
tissue
type
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
common carp
6.00
0.10
1.58
1.92
1.74
9.99
WB
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
green sunfish
6.00
0.10
2.29
1.45
1.91
7.26
WB
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
fathead minnow
6.00
0.10
2.78
1.40
2.23
6.01
WB
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
fathead minnow
6.00
0.10
2.78
1.40
2.23
7.41
WB
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
fathead minnow
6.00
0.10
2.78
1.40
2.23
6.15
WB
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
red shiner
6.00
0.10
2.27
1.95
2.55
8.99
WB
Butler etal. 1995
McElmo Cr.upstream from Yellow Jacket
Cyn.
red shiner
6.00
0.10
2.27
1.95
2.55
8.21
WB
Butler etal. 1995
Navajo Wash near Towaoc
bluehead sucker
12.00
0.20
1.24
1.82
5.30
16.91
WB
Butler etal. 1995
Navajo Wash near Towaoc
bluehead sucker
12.00
0.20
1.24
1.82
5.30
13.09
WB
Butler etal. 1995
Navajo Wash near Towaoc
speckled dace
12.00
0.20
1.36
1.95
6.23
17.00
WB
Butler etal. 1995
San Juan River at Four Comers
channel catfish
1.50
0.26
1.35
1.45
0.77
2.98
M
Butler etal. 1995
San Juan River at Four Comers
flannelmouth sucker
1.50
0.26
1.52
1.41
0.84
2.70
M
Butler etal. 1995
San Juan River at Four Comers
channel catfish
1.50
0.26
1.35
1.45
0.77
5.95
WB
Butler etal. 1995
San Juan River at Four Comers
flannelmouth sucker
1.50
0.26
1.52
1.41
0.84
2.11
WB
Butler etal. 1995
San Juan River at Four Comers
flannelmouth sucker
1.50
0.26
1.52
1.41
0.84
3.10
WB
Butler etal. 1995
San Juan River at Four Comers
flannelmouth sucker
1.50
0.26
1.52
1.41
0.84
0.86
WB
Butler etal. 1995
San Juan River at Four Comers
flannelmouth sucker
1.50
0.26
1.52
1.41
0.84
1.55
WB
Butler etal. 1995
San Juan River at Four Comers
flannelmouth sucker
1.50
0.26
1.52
1.41
0.84
5.92
WB
Butler etal. 1995
San Juan River at Four Comers
bluehead sucker
1.50
0.26
1.24
1.82
0.89
2.18
WB
Butler etal. 1995
San Juan River at Four Comers
bluehead sucker
1.50
0.26
1.24
1.82
0.89
1.71
WB
Butler etal. 1995
San Juan River at Four Comers
bluehead sucker
1.50
0.26
1.24
1.82
0.89
2.18
WB
Butler etal. 1995
San Juan River at Four Comers
speckled dace
1.50
0.26
1.36
1.95
1.04
8.40
WB
Butler etal. 1995
San Juan River at Four Comers
speckled dace
1.50
0.26
1.36
1.95
1.04
9.97
WB
Butler etal. 1995
San Juan River at Four Comers
speckled dace
1.50
0.26
1.36
1.95
1.04
5.67
WB
Butler etal. 1995
San Juan River at Four Comers
common carp
1.50
0.26
1.58
1.92
1.19
10.18
WB
1-6
-------
lyyS
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1995
1997
1997
1997
1997
1997
1997
1997
1997
1997
1997
1997
1997
1997
Site
Species
Sile
Wilier
(ua/l)
i:i
d/ii)
TIP
CI
I'reil.
i:/o
Ohs.
i:/o
Sail Juuii Ri \ cr aL Four Comas
cummuii carp
1.5U
o.:o
1.5S
i.y:
1.19
0.53
San Juan River at Four Comers
red shiner
1.50
0.26
2.27
1.95
1.75
6.84
San Juan River at Mexican Hat Utah
channel catfish
1.50
0.29
1.35
1.45
0.85
lOi
San Juan River at Mexican Hat Utah
flannelmouth sucker
1.50
0.29
1.52
1.41
0.93
2.40
San Juan River at Mexican Hat Utah
flannelmouth sucker
1.50
0.29
1.52
1.41
0.93
2.68
San Juan River at Mexican Hat Utah
flannelmouth sucker
1.50
0.29
1.52
1.41
0.93
4.23
San Juan River at Mexican Hat Utah
flannelmouth sucker
1.50
0.29
1.52
1.41
0.93
1.97
San Juan River at Mexican Hat Utah
flannelmouth sucker
1.50
0.29
1.52
1.41
0.93
2.40
San Juan River at Mexican Hat Utah
flannelmouth sucker
1.50
0.29
1.52
1.41
0.93
4.23
San Juan River at Mexican Hat Utah
bluehead sucker
1.50
0.29
1.24
1.82
0.98
4.18
San Juan River at Mexican Hat Utah
bluehead sucker
1.50
0.29
1.24
1.82
0.98
4.36
San Juan River at Mexican Hat Utah
bluehead sucker
1.50
0.29
1.24
1.82
0.98
4.91
San Juan River at Mexican Hat Utah
common carp
1.50
0.29
1.58
1.92
1.31
7.49
Woods Cyn. Near Yellow Jacket
fathead minnow
5.50
0.40
2.78
1.40
8.65
25.71
Woods Cyn. Near Yellow Jacket
fathead minnow
5.50
0.40
2.78
1.40
8.65
32.00
Woods Cyn. Near Yellow Jacket
fathead minnow
5.50
0.40
2.78
1.40
8.65
36.89
Cahone Canyon at Highway 666
green sunflsh
10.50
0.20
2.29
1.45
6.83
13.79
Large pond south of G Road, southern
Mancos Valley
fathead minnow
3.00
2.00
2.78
1.40
23.39
15.37
Mud Creek at Highway 32, near Cortez
bluehead sucker
18.50
0.07
1.24
1.82
2.94
4.55
Mud Creek at Highway 32, near Cortez
bluehead sucker
18.50
0.07
1.24
1.82
2.94
9.45
Mud Creek at Highway 32, near Cortez
bluehead sucker
18.50
0.07
1.24
1.82
2.94
10.18
Mud Creek at Highway 32, near Cortez
green sunflsh
18.50
0.07
2.29
1.45
4.33
11.03
Mud Creek at Highway 32, near Cortez
green sunflsh
18.50
0.07
2.29
1.45
4.33
10.16
Mud Creek at Highway 32, near Cortez
fathead minnow
18.50
0.07
2.78
1.40
5.05
10.76
Mud Creek at Highway 32, near Cortez
fathead minnow
18.50
0.07
2.78
1.40
5.05
16.77
Mud Creek at Highway 32, near Cortez
fathead minnow
18.50
0.07
2.78
1.40
5.05
9.08
Pond downstream from site MNP2,
southern Mancos Valley
smallmouth bass
1.00
5.15
1.93
1.42
14.09
17.03
Pond on Woods Canyon at 15 Road
fathead minnow
3.00
0.90
2.78
1.40
10.55
13.97
Pond on Woods Canyon at 15 Road
fathead minnow
3.00
0.90
2.78
1.40
10.55
20.96
Deerlick Creek
rainbow trout
0.20
2.24
2.33
2.44
2.55
3.14
1-7
-------
Sile
I'reil.
Obs.
Ohs.
Wilier
i:i
i:/o
i:/o
tissue
Slink
Site
Species
(MU/I)
(l/a)
CI
(mji/lvji)
type
Casc\ 2005
Dccrlick Creek
rainbow iroul
0.20
2.24
2.44
-> ss
8.16
L-0
Casey 2005
Luscar Creek
rainbow trout
10.70
0.33
2.33
2.44
19.85
16.79
M
Casey 2005
Luscar Creek
rainbow trout
10.70
0.33
2.33
2.44
19.85
33.48
E-0
Formation 2012
Crow Creek - 1A
sculpin
2.20
0.80
2.78
1.45
7.08
14.43
WB
Formation 2012
Crow Creek - 1A
sculpin
2.20
0.80
2.78
1.45
7.08
12.10
WB
Formation 2012
Crow Creek - 1A
brown trout
2.20
0.80
2.96
1.45
7.52
15.20
WB
Formation 2012
Crow Creek - 1A
brown trout
2.20
0.80
2.96
1.45
7.52
13.49
WB
Formation 2012
Crow Creek - 1A
sculpin
2.45
0.80
2.78
1.45
7.89
11.29
WB
Formation 2012
Crow Creek - 1A
brown trout
2.45
0.80
2.96
1.45
8.37
14.39
WB
Formation 2012
Crow Creek - 1A
sculpin
2.90
0.80
2.78
1.45
9.34
25.35
WB
Formation 2012
Crow Creek - 1A
brown trout
2.90
0.80
2.96
1.45
9.91
24.36
WB
Formation 2012
Crow Creek - 1A
sculpin
4.80
0.80
2.78
1.45
15.45
18.33
WB
Formation 2012
Crow Creek - 1A
brown trout
4.80
0.80
2.96
1.45
16.40
20.29
WB
Formation 2012
Crow Creek - 3A
sculpin
1.80
0.81
2.78
1.45
5.86
20.97
WB
Formation 2012
Crow Creek - 3A
sculpin
1.80
0.81
2.78
1.45
5.86
16.91
WB
Formation 2012
Crow Creek - 3A
brown trout
1.80
0.81
2.97
1.45
6.22
15.09
WB
Formation 2012
Crow Creek - 3A
brown trout
1.80
0.81
2.97
1.45
6.22
13.30
WB
Formation 2012
Crow Creek - 3A
sculpin
2.20
0.81
2.78
1.45
7.17
16.65
WB
Formation 2012
Crow Creek - 3A
brown trout
2.20
0.81
2.97
1.45
7.60
16.27
WB
Formation 2012
Crow Creek - 3A
brown trout
2.60
0.81
2.97
1.45
8.99
22.24
WB
Formation 2012
Crow Creek - 3A
sculpin
4.20
0.81
2.78
1.45
13.68
29.32
WB
Formation 2012
Crow Creek - 3A
brown trout
4.20
0.81
2.97
1.45
14.52
28.45
WB
Formation 2012
Crow Creek - CC150
sculpin
0.68
1.04
2.74
1.45
2.81
8.72
WB
Formation 2012
Crow Creek - CC150
sculpin
0.68
1.04
2.74
1.45
2.81
7.31
WB
Formation 2012
Crow Creek - CC150
brown trout
0.68
1.04
2.91
1.45
2.98
8.43
WB
Formation 2012
Crow Creek - CC150
brown trout
0.68
1.04
2.91
1.45
2.98
12.54
WB
Formation 2012
Crow Creek - CC150
sculpin
0.80
1.04
2.74
1.45
3.31
7.46
WB
Formation 2012
Crow Creek - CC150
brown trout
0.80
1.04
2.91
1.45
3.51
7.52
WB
Formation 2012
Crow Creek - CC150
sculpin
1.40
1.04
2.74
1.45
5.79
15.57
WB
Formation 2012
Crow Creek - CC150
brown trout
1.40
1.04
2.91
1.45
6.14
14.66
WB
Formation 2012
Crow Creek - CC150
sculpin
1.50
1.04
2.74
1.45
6.20
10.67
WB
Formation 2012
Crow Creek - CC150
brown trout
1.50
1.04
2.91
1.45
6.58
11.32
WB
1-8
-------
Sile
I'reil.
Obs.
Ohs.
Wilier
i:i
i:/o
i:/o
tissue
Slink
Site
Species
(MU/I)
(l/a)
CI
(mji/lvji)
type
I'onnaLioii :ui:
Crow Civvk - CC 3 5 <>
sculpin
us:
1.16
2.79
1.45
3.80
9.39
WB
Formation 2012
Crow Creek - CC350
sculpin
0.82
1.16
2.79
1.45
3.86
10.33
WB
Formation 2012
Crow Creek - CC350
sculpin
0.86
1.16
2.79
1.45
4.02
7.66
WB
Formation 2012
Crow Creek - CC350
brown trout
0.82
1.16
2.97
1.45
4.09
9.08
WB
Formation 2012
Crow Creek - CC350
brown trout
0.82
1.16
2.97
1.45
4.09
12.33
WB
Formation 2012
Crow Creek - CC350
sculpin
0.89
1.16
2.79
1.45
4.19
14.56
WB
Formation 2012
Crow Creek - CC350
brown trout
0.86
1.16
2.97
1.45
4.27
8.36
WB
Formation 2012
Crow Creek - CC350
brown trout
0.89
1.16
2.97
1.45
4.44
16.63
WB
Formation 2012
Crow Creek - CC350
sculpin
1.10
1.16
2.79
1.45
5.15
13.83
WB
Formation 2012
Crow Creek - CC350
brown trout
1.10
1.16
2.97
1.45
5.47
11.49
WB
Formation 2012
Crow Creek - CC75
sculpin
0.46
1.19
2.69
1.45
2.13
8.10
WB
Formation 2012
Crow Creek - CC75
sculpin
0.46
1.19
2.69
1.45
2.13
7.30
WB
Formation 2012
Crow Creek - CC75
brown trout
0.46
1.19
2.87
1.45
2.26
5.86
WB
Formation 2012
Crow Creek - CC75
brown trout
0.46
1.19
2.87
1.45
2.26
7.74
WB
Formation 2012
Crow Creek - CC75
sculpin
0.52
1.19
2.69
1.45
2.39
5.47
WB
Formation 2012
Crow Creek - CC75
brown trout
0.52
1.19
2.87
1.45
2.54
4.60
WB
Formation 2012
Crow Creek - CC75
sculpin
0.85
1.19
2.69
1.45
3.94
10.43
WB
Formation 2012
Crow Creek - CC75
brown trout
0.85
1.19
2.87
1.45
4.18
14.92
WB
Formation 2012
Crow Creek - CC75
sculpin
1.00
1.19
2.69
1.45
4.64
10.28
WB
Formation 2012
Crow Creek - CC75
brown trout
1.00
1.19
2.87
1.45
4.92
9.54
WB
Formation 2012
Deer Creek
sculpin
1.45
1.55
2.81
1.45
9.17
11.07
WB
Formation 2012
Deer Creek
sculpin
1.50
1.55
2.81
1.45
9.49
12.34
WB
Formation 2012
Deer Creek
sculpin
1.50
1.55
2.81
1.45
9.49
11.42
WB
Formation 2012
Deer Creek
brown trout
1.45
1.55
3.00
1.45
9.73
8.46
WB
Formation 2012
Deer Creek
brown trout
1.50
1.55
3.00
1.45
10.07
12.35
WB
Formation 2012
Deer Creek
brown trout
1.50
1.55
3.00
1.45
10.07
8.96
WB
Formation 2012
Deer Creek
sculpin
2.00
1.55
2.81
1.45
12.65
11.55
WB
Formation 2012
Deer Creek
brown trout
2.00
1.55
3.00
1.45
13.43
18.55
WB
Formation 2012
Deer Creek
sculpin
2.40
1.55
2.81
1.45
15.18
12.51
WB
Formation 2012
Deer Creek
brown trout
2.40
1.55
3.00
1.45
16.11
15.24
WB
Formation 2012
Hoopes Spring - HS
sculpin
20.50
0.24
3.63
1.45
26.38
33.71
WB
Formation 2012
Hoopes Spring - HS
sculpin
20.50
0.24
3.63
1.45
26.38
33.74
WB
1-9
-------
Sile
I'reil.
Obs.
Ohs.
Wilier
i:i
i:/o
i:/o
tissue
Sluilv
Site
Species
(MU/I)
(l/a)
CI
(mji/lvji)
type
I'onnaLioii :ui:
1 loo pes Spring - IIS
SC 111 pill
20.95
0.24
3.63
1.45
26.96
15. sy
WB
Formation 2012
Hoopes Spring - HS
brown trout
20.50
0.24
3.86
1.45
27.99
23.89
WB
Formation 2012
Hoopes Spring - HS
brown trout
20.50
0.24
3.86
1.45
27.99
36.15
WB
Formation 2012
Hoopes Spring - HS
brown trout
20.95
0.24
3.86
1.45
28.61
36.00
WB
Formation 2012
Hoopes Spring - HS
sculpin
27.30
0.24
3.63
1.45
35.13
52.15
WB
Formation 2012
Hoopes Spring - HS
brown trout
27.30
0.24
3.86
1.45
37.28
47.18
WB
Formation 2012
Hoopes Spring - HS
sculpin
40.45
0.24
3.63
1.45
52.05
59.94
WB
Formation 2012
Hoopes Spring - HS
brown trout
40.45
0.24
3.86
1.45
55.23
32.97
WB
Formation 2012
Hoopes Spring - HS3
sculpin
16.10
0.54
2.47
1.45
30.96
31.71
WB
Formation 2012
Hoopes Spring - HS3
sculpin
16.10
0.54
2.47
1.45
30.96
26.95
WB
Formation 2012
Hoopes Spring - HS3
sculpin
17.05
0.54
2.47
1.45
32.79
38.65
WB
Formation 2012
Hoopes Spring - HS3
brown trout
16.10
0.54
2.63
1.45
32.85
29.78
WB
Formation 2012
Hoopes Spring - HS3
brown trout
16.10
0.54
2.63
1.45
32.85
27.23
WB
Formation 2012
Hoopes Spring - HS3
brown trout
17.05
0.54
2.63
1.45
34.79
25.87
WB
Formation 2012
Hoopes Spring - HS3
sculpin
26.00
0.54
2.47
1.45
49.99
34.73
WB
Formation 2012
Hoopes Spring - HS3
brown trout
26.00
0.54
2.63
1.45
53.05
34.24
WB
Formation 2012
Hoopes Spring - HS3
sculpin
31.75
0.54
2.47
1.45
61.05
34.37
WB
Formation 2012
Hoopes Spring - HS3
brown trout
31.75
0.54
2.63
1.45
64.78
41.89
WB
Formation 2012
Sage Creek - LSV2C
sculpin
13.50
0.45
2.83
1.45
24.76
25.35
WB
Formation 2012
Sage Creek - LSV2C
sculpin
13.50
0.45
2.83
1.45
24.76
16.52
WB
Formation 2012
Sage Creek - LSV2C
sculpin
13.80
0.45
2.83
1.45
25.31
27.36
WB
Formation 2012
Sage Creek - LSV2C
sculpin
14.30
0.45
2.83
1.45
26.23
37.66
WB
Formation 2012
Sage Creek - LSV2C
brown trout
13.50
0.45
3.01
1.45
26.27
28.12
WB
Formation 2012
Sage Creek - LSV2C
brown trout
13.50
0.45
3.01
1.45
26.27
18.48
WB
Formation 2012
Sage Creek - LSV2C
brown trout
13.80
0.45
3.01
1.45
26.86
32.78
WB
Formation 2012
Sage Creek - LSV2C
brown trout
14.30
0.45
3.01
1.45
27.83
28.24
WB
Formation 2012
Sage Creek - LSV2C
sculpin
18.75
0.45
2.83
1.45
34.39
29.49
WB
Formation 2012
Sage Creek - LSV2C
brown trout
18.75
0.45
3.01
1.45
36.49
30.30
WB
Formation 2012
Sage Creek - LSV4
sculpin
8.45
0.69
2.70
1.45
23.02
29.04
WB
Formation 2012
Sage Creek - LSV4
sculpin
8.45
0.69
2.70
1.45
23.02
26.53
WB
Formation 2012
Sage Creek - LSV4
brown trout
8.45
0.69
2.88
1.45
24.43
23.42
WB
Formation 2012
Sage Creek - LSV4
brown trout
8.45
0.69
2.88
1.45
24.43
21.95
WB
1-10
-------
Sile
I'reil.
Obs.
Ohs.
Wilier
i:i
i:/o
i:/o
tissue
SuiiIy
Site
Species
(us/l)
d/ii)
ii
CI
type
Formation 2012
Soulli Fork lineup Cr.
SC 111 pill
0.32
1.32
2.86
1.45
1.73
8.24
WB
Formation 2012
South Fork Tincup Cr.
brown trout
0.32
1.32
3.05
1.45
1.84
5.32
WB
Formation 2012
South Fork Tincup Cr.
sculpin
0.43
1.32
2.86
1.45
2.37
5.44
WB
Formation 2012
South Fork Tincup Cr.
sculpin
0.44
1.32
2.86
1.45
2.42
13.51
WB
Formation 2012
South Fork Tincup Cr.
brown trout
0.43
1.32
3.05
1.45
2.51
3.25
WB
Formation 2012
South Fork Tincup Cr.
brown trout
0.44
1.32
3.05
1.45
2.57
9.69
WB
Formation 2012
South Fork Tincup Cr.
sculpin
0.56
1.32
2.86
1.45
3.06
8.52
WB
Formation 2012
South Fork Tincup Cr.
brown trout
0.56
1.32
3.05
1.45
3.24
3.82
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
white sucker
1.00
0.86
1.58
1.38
1.89
3.92
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
white sucker
1.00
0.86
1.58
1.38
1.89
4.41
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
white sucker
1.00
0.86
1.58
1.38
1.89
4.75
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
white sucker
1.00
0.86
1.58
1.38
1.89
5.03
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
white sucker
1.00
0.86
1.58
1.38
1.89
5.52
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
white sucker
1.00
0.86
1.58
1.38
1.89
5.54
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
fathead minnow
1.00
0.86
2.78
1.40
3.36
9.21
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
fathead minnow
1.00
0.86
2.78
1.40
3.36
9.22
WB
Grassoetal. 1995
Arapahoe Wetlands Pond
fathead minnow
1.00
0.86
2.78
1.40
3.36
10.20
WB
Hamilton and Buhl
2004
lower East Mill Creek
cutthroat trout
24.00
1.32
2.29
1.96
142.01
102.73
WB
Lemly 1985
Badin Lake
black bullhead
0.32
12.48
1.72
1.45
9.99
4.44
M
Lemly 1985
Badin Lake
western mosquitofish
0.32
12.48
2.37
1.20
11.33
5.77
M
Lemly 1985
Badin Lake
common carp
0.32
12.48
1.58
1.92
12.10
5.81
M
Lemly 1985
Badin Lake
green sunfish
0.32
12.48
2.29
1.45
13.30
3.25
M
Lemly 1985
Badin Lake
fathead minnow
0.32
12.48
2.78
1.40
15.52
3.17
M
Lemly 1985
Badin Lake
red shiner
0.32
12.48
2.27
1.95
17.74
4.45
M
Lemly 1985
Belews Lake
black bullhead
10.91
1.75
1.72
1.45
47.79
29.84
M
Lemly 1985
Belews Lake
western mosquitofish
10.91
1.75
2.37
1.20
54.18
46.86
M
Lemly 1985
Belews Lake
common carp
10.91
1.75
1.58
1.92
57.86
38.97
M
Lemly 1985
Belews Lake
green sunfish
10.91
1.75
2.29
1.45
63.60
20.84
M
Lemly 1985
Belews Lake
fathead minnow
10.91
1.75
2.78
1.40
74.25
28.75
M
Lemly 1985
Belews Lake
red shiner
10.91
1.75
2.27
1.95
84.87
38.59
M
Lemly 1985
High Rock Lake
black bullhead
0.67
4.99
1.72
1.45
8.36
5.58
M
1-11
-------
Sile
I'reil.
Obs.
Ohs.
Wilier
i:i
i:/o
i:/o
tissue
SiiiiIy
Site
Species
(us/l)
d/ii)
ii
CI
type
Lcml> 1985
1 li»li Rock Lake
w cslcrii mosq lulolish
U.t>7
4 ww
2.37
IJU
9.48
o.lu
M
Lemly 1985
High Rock Lake
common carp
0.67
4.99
1.58
1.92
10.12
4.49
M
Lemly 1985
High Rock Lake
green sunfish
0.67
4.99
2.29
1.45
11.13
3.13
M
Lemly 1985
High Rock Lake
fathead minnow
0.67
4.99
2.78
1.40
12.99
4.00
M
Lemly 1985
High Rock Lake
red shiner
0.67
4.99
2.27
1.95
14.85
4.62
M
McDonald and Strosher
1998
Elk R. above Cadorna Cr. (745)
cutthroat trout
0.10
6.30
2.29
1.96
2.83
10.61
WB
McDonald and Strosher
1998
Elk R. above Cadorna Cr. (745)
mountain whitefish
0.10
6.30
2.97
7.39
13.83
7.11
WB
McDonald and Strosher
1998
Fording R. above Swift Cr. (746)
cutthroat trout
8.60
0.23
2.29
1.96
8.71
24.96
WB
Muscatello and Janz
2009
Vulture Lake
white sucker
0.43
1.01
1.58
1.38
0.95
4.65
WB
Muscatello and Janz
2009
Vulture Lake
burbot
0.43
1.01
2.45
1.45
1.54
15.91
WB
Muscatello and Janz
2009
Vulture Lake
ninespine stickleback
0.43
1.01
3.22
1.45
2.03
6.02
WB
Muscatello and Janz
2009
Vulture Lake
northern pike
0.43
1.01
4.02
2.39
4.17
1.83
WB
Orr et al. 2012
Clode Pond 11
cutthroat trout
36.10
0.71
2.29
1.96
115.88
81.06
E-0
Orr et al. 2012
Elk Lakes 14
cutthroat trout
0.40
1.64
2.29
1.96
2.95
14.02
E-0
Orr et al. 2012
Elk River 1
cutthroat trout
4.20
0.55
2.29
1.96
10.33
11.02
E-0
Orr et al. 2012
Elk River 1
cutthroat trout
4.20
0.55
2.29
1.96
10.33
15.60
E-0
Orr et al. 2012
Elk River 12
cutthroat trout
0.75
2.67
2.29
1.96
8.98
9.00
E-0
Orr et al. 2012
Fording River 23
cutthroat trout
30.60
0.21
2.29
1.96
28.52
15.56
E-0
Orr et al. 2012
Fording River Oxbow 10
cutthroat trout
50.10
1.34
2.29
1.96
302.30
47.81
E-0
Orr et al. 2012
Henretta Lake 27
cutthroat trout
8.60
0.50
2.29
1.96
19.33
13.56
E-0
Orr et al. 2012
Michel Creek 2
cutthroat trout
7.40
0.28
2.29
1.96
9.43
10.07
E-0
Saiki and Lowe 1987
Kesterson Pond 11
western mosquitofish
38.60
0.51
2.37
1.20
55.41
155.61
WB
Saiki and Lowe 1987
Kesterson Pond 11
western mosquitofish
38.60
0.51
2.37
1.20
55.41
124.49
WB
Saiki and Lowe 1987
Kesterson Pond 2
western mosquitofish
195.85
0.32
2.37
1.20
175.68
268.13
WB
Saiki and Lowe 1987
Kesterson Pond 2
western mosquitofish
195.85
0.32
2.37
1.20
175.68
295.66
WB
1-12
-------
SiiiiIy
Site
Species
Sile
Wilier
(us/l)
i:i
d/ii)
ii
CI
I'reil.
i:/o
Obs.
i:/o
Ohs.
tissue
type
Saiki and Lowc 1987
IwikTion Pond 8
w cslcrn mosq lulolish
70.35
DM)
2.37
1.2U
120.13
196.31
WB
Saiki and Lowe 1987
Kesterson Pond 8
western mosquitofish
70.35
0.60
2.37
1.20
120.13
266.93
WB
Saiki and Lowe 1987
San Luis Drain
western mosquitofish
316.50
0.36
2.37
1.20
322.76
178.36
WB
Saiki and Lowe 1987
San Luis Drain
western mosquitofish
316.50
0.36
2.37
1.20
322.76
397.41
WB
Saiki and Lowe 1987
Volta Pond 26
western mosquitofish
0.53
0.93
2.37
1.20
1.41
1.53
WB
Saiki and Lowe 1987
Volta Pond 26
western mosquitofish
0.53
0.93
2.37
1.20
1.41
1.48
WB
Saiki and Lowe 1987
Volta Wasteway
western mosquitofish
0.74
1.03
2.37
1.20
2.15
1.62
WB
Saiki and Lowe 1987
Volta Wasteway
western mosquitofish
0.74
1.03
2.37
1.20
2.15
1.63
WB
Saiki etal. 1993
Mud Slough at Gun Club Road
bluegill
6.00
1.37
1.47
2.13
25.69
10.67
WB
Saiki etal. 1993
Mud Slough at Gun Club Road
bluegill
6.00
1.37
1.47
2.13
25.69
13.65
WB
Saiki etal. 1993
Mud Slough at Gun Club Road
largemouth bass
6.00
1.37
2.04
1.42
23.73
9.65
WB
Saiki etal. 1993
Mud Slough at Gun Club Road
largemouth bass
6.00
1.37
2.04
1.42
23.73
9.79
WB
Saiki etal. 1993
Mud Slough at Gun Club Road
western mosquitofish
6.00
1.37
2.10
1.20
20.61
13.17
WB
Saiki etal. 1993
Mud Slough at Gun Club Road
western mosquitofish
6.00
1.37
2.10
1.20
20.61
19.15
WB
Saiki etal. 1993
Salt Slough at the San Luis National
Wildlife Refuge
bluegill
8.00
0.43
1.47
2.13
10.70
9.17
WB
Saiki etal. 1993
Salt Slough at the San Luis National
Wildlife Refuge
bluegill
8.00
0.43
1.47
2.13
10.70
9.60
WB
Saiki etal. 1993
Salt Slough at the San Luis National
Wildlife Refuge
largemouth bass
8.00
0.43
2.04
1.42
9.89
5.68
WB
Saiki etal. 1993
Salt Slough at the San Luis National
Wildlife Refuge
largemouth bass
8.00
0.43
2.04
1.42
9.89
6.67
WB
Saiki etal. 1993
Salt Slough at the San Luis National
Wildlife Refuge
western mosquitofish
8.00
0.43
2.10
1.20
8.59
5.39
WB
Saiki etal. 1993
Salt Slough at the San Luis National
Wildlife Refuge
western mosquitofish
8.00
0.43
2.10
1.20
8.59
5.87
WB
Saiki etal. 1993
San Joaquin R. above Hills Ferry Road
bluegill
7.00
0.36
1.47
2.13
7.83
5.76
WB
Saiki etal. 1993
San Joaquin R. above Hills Ferry Road
bluegill
7.00
0.36
1.47
2.13
7.83
7.04
WB
Saiki etal. 1993
San Joaquin R. above Hills Ferry Road
largemouth bass
7.00
0.36
2.04
1.42
7.23
3.12
WB
Saiki etal. 1993
San Joaquin R. above Hills Ferry Road
largemouth bass
7.00
0.36
2.04
1.42
7.23
3.41
WB
Saiki etal. 1993
San Joaquin R. above Hills Ferry Road
western mosquitofish
7.00
0.36
2.10
1.20
6.28
2.63
WB
Saiki etal. 1993
San Joaquin R. above Hills Ferry Road
western mosquitofish
7.00
0.36
2.10
1.20
6.28
5.39
WB
1-13
-------
SiiiiIy
Site
Species
Sile
Wilier
(us/l)
i:i
d/ii)
ii
CI
I'reil.
i:/o
Obs.
i:/o
Ohs.
tissue
type
Saikietal. 1993
San Joaquin R. at Durham Ferry State
Recereation Area
bluegill
1.00
0.75
1.47
2.13
2.34
4.05
WB
Saikietal. 1993
San Joaquin R. at Durham Ferry State
Recereation Area
bluegill
1.00
0.75
1.47
2.13
2.34
4.27
WB
Saikietal. 1993
San Joaquin R. at Durham Ferry State
Recereation Area
largemouth bass
1.00
0.75
2.04
1.42
2.16
2.41
WB
Saikietal. 1993
San Joaquin R. at Durham Ferry State
Recereation Area
largemouth bass
1.00
0.75
2.04
1.42
2.16
2.55
WB
Saikietal. 1993
San Joaquin R. at Durham Ferry State
Recereation Area
western mosquitofish
1.00
0.75
2.10
1.20
1.87
2.03
WB
Saikietal. 1993
San Joaquin R. at Durham Ferry State
Recereation Area
western mosquitofish
1.00
0.75
2.10
1.20
1.87
2.39
WB
Stephens et al. 1988
Marsh 4720
black bullhead
31.00
0.10
1.72
1.45
7.43
10.16
WB
Stephens et al. 1988
Marsh 4720
common carp
31.00
0.10
1.58
1.92
9.00
36.49
WB
Stephens et al. 1988
Marsh 4720
common carp
31.00
0.10
1.58
1.92
9.00
40.33
WB
1-14
-------
The ratio of predicted versus observed tissue concentrations in the above table can be compared
against the main text Table 3.13 water concentrations that would be predicted to occur if each site' s egg-
ovary tissue concentration were at the criterion level. Figure 1-1 shows the results. It can be seen that for
those sites (in the left portion of each graph) where tissue concentrations equal to the egg-ovary criterion
would be predicted to yield water concentrations not far on either side of the water criteria values, the
predicted-to-observed tissue concentration ratios are not particularly biased relative to a ratio of 1.0. This
indicates that the model is performing reasonably well for those sites strongly influencing the derived
values of the water criteria.
The derivation of the water criteria concentrations involves an assumption of linearity in
projecting the water concentration that would correspond to a tissue concentration equal to the tissue
criterion. Figure 1-2 suggests that high BAFs tend to be associated with low water concentrations, and low
BAFs with high water concentrations. At the low concentrations associated with the 20th percentile
model-predicted BAF, the linearity assumption would appear to be environmentally conservative. At high
concentrations, the opposite situation would occur, but overall, because the criterion is based on the 20th
percentile, the linearity assumption appears to be protective.
1-15
-------
OJ
CC
C
o
¦M
ro
i/)
¦a
ai
>
.q
O
T3
ai
T3
ai
8
4
2
1
0.5
0.25
0.125
0.0625
0.03125
~
Lentic
V
~
~ ~
-*• -*•
~f ¥
* a ~
i ~
~
~
~
1 1 1 1
0.25
16
64
Site's Water Cone. (|jg/l_) Predicted at Tissue Criterion
0.0625
Site's Water Cone. (ug/L) Predicted at Tissue Criterion
Figures 1-1. For lentic (left panel) and lotic (right panel) waters, predicted-to-observed fish-tissue
concentration ratio for each of the 65 sites, plotted versus each site's Table 3.13 water concentration
that would be predicted to occur if its tissue levels were at the egg-ovary tissue criterion level.
Corresponding to how the water criteria concentrations were derived, for sites with multiple fish
species, the plotted ratio is for the species having the highest predicted tissue-to-water ratio (i.e., highest
predicted BAF). For sites having multiple samples of that species, the plotted value is the average
predicted-to-observed ratio for that species.
1-16
-------
64
(/)
2
>
a>
U)
-Q
1
o
0.5
Lentic
A
• ~
~
~ ~
~~
~ ~
~ ~ .
~
~
~ ~ ~
~
~ ~ ~
~
i i i i i
0.25 1 4 16 64
Site Observed Water Cone. (|jg/l_)
256
a>
a.
to
<
ca
T3
a>
>
.q
O
128
64
32
16
8
4
2
1
0.5
Lotic
~ ~
> .~
0.0625 0.25 1 4 16 64 256
Site Observed Water Cone. (|jg/l_)
Figures 1-2. For lentic (left panel) and lotic (right panel) waters, observed BAFs (egg-ovary tissue-
to-water concentration ratios) versus observed water concentration (both from the above table), for
each site's fish species used in Table 3.13 (that is, for the species used in the water criteria
calculations).
For sites having multiple samples of such species, tissue concentrations were averaged. Because
nearly all samples were either whole body or muscle, the graphed BAFs include application of the CF, to
normalize all samples to egg-ovary tissue. Since the CFs have been are assumed to be independent of
concentration, the graphs do not reflect any potential CF nonlinearities, if they exist.
1-17
-------
APPENDIX J: Supplementary Information
on Selenium Bioaccumulation in
Aquatic Animals
J-l
-------
1.0 Effects of Growth Rate on the Accumulation of
Selenium in Fish
EPA analyzed the effect of the growth rate parameter g when estimating selenium
bioaccumulation using the mechanistic bioaccumulation modeling described in Equation 1 of the main
text. Because the addition of tissue associated with growth could have a dilution effect on the chemicals
present in tissue, a parameter representing growth rate is present in the denominator of Equation 1.
Indeed, growth can be an important factor in the bioaccumulation of very hydrophobic chemicals with
low excretion rates such as polychlorinated biphenyls, (Connolly and Pedersen 1988). However, the effect
of growth may not be as important for selenium because of its unique biogeochemical characteristics,
route of exposure, and role as a micronutrient.
EPA tested the effect of the growth rate parameter g on estimates of selenium bioaccumulation
using Equation 1 with different food web scenarios. Increasing growth rates from 0 (no growth) to 0.2/day
(a relatively high rate of growth) reduced selenium concentrations in trophic level 2 and 3 organisms by
as much as a factor of 10 to 20. Thus incorporating growth rate in Equation 1 could result in significant
dilution of selenium and lower estimates of selenium bioaccumulation.
Although increasing the value of the growth parameter g in Equation 1 reduces estimates of
selenium bioaccumulation, this simple analysis neglects an important physiological linkage between
growth and food consumption. Organisms must consume enough food to support growth and meet their
energy requirements for respiration, specific dynamic action, waste loss, and reproduction. These
physiological requirements suggest that higher growth rates are associated with greater rates of food
consumption. Because food consumption is the primary route of selenium exposure in aquatic organisms,
increased selenium exposure associated with higher food consumption could counterbalance the dilution
of selenium in tissue associated with higher growth rates.
EPA tested the effects of growth on estimates of selenium bioaccumulation using Equation 1
when increased food consumption was associated with higher growth rates. EPA modified Equation 1 to
incorporate a simple relationship for bioenergetics (Thomann et al. 1992) and applied the model to
reexamine the sensitivity of selenium bioaccumulation to growth rates in trophic level 2 and 3 organisms.
The results of this analysis showed that increasing growth rates over two orders of magnitude increased
selenium concentrations in trophic level 2 by a factor of 2, and decreased selenium concentrations in
trophic level 3 by 10%. When growth rates were increased simultaneously in trophic levels 2 and 3, the
selenium concentrations increased by less than a factor of 2. This analysis suggests that when
bioenergetics is considered, selenium bioaccumulation is generally insensitive to organism growth rates.
EPA believes that uncertainties in the toxicokinetic parameters of selenium far outweigh the effects on
growth rate on selenium bioaccumulation. Thus, the growth rate parameter g was removed from Equation
J-2
-------
1 for the purpose of deriving a translation equation that could be used to implement a tissue-based
selenium water quality criterion.
2.0 Analysis of the Relative Contribution of Aqueous and
Dietary Uptake on the Bio accumulation of Selenium
EPA analyzed the relative contributions of direct aqueous uptake versus ingestion of selenium in
consideration of removing the uptake rate constant ku from Equation 1 in Section 3.2 of the main text.
Because an important exposure route for some chemicals is direct contact with water, an uptake rate
constant ku is present in the numerator of Equation 1. However, fish and invertebrate organisms absorb
selenium primarily through the consumption of food rather than from direct aqueous uptake (Forester
2007; Lemly 1985; Luoma et al. 1992). Thus, removing the uptake rate constant ku could simplify
Equation 1 while maintaining the key determinants of selenium bioaccumulation.
EPA tested the relative contribution of aqueous versus dietary uptake of selenium using a version
of Equation 1 that incorporates both exposure pathways (Thomann et. al. 1992). For trophic level 2,
selenium bioaccumulation was estimated for a range of uptake rates that varied according to the
respiration rate and aqueous transfer efficiency of selenium relative to dissolved oxygen. For trophic level
3, uptake rates were varied within a range of values reported in Besser et al. (1993) and Bertram and
Brooks (1986).
EPA's analysis showed that diet accounted for 34% - 92% of selenium bioaccumulation at trophic
level 2, with a median of 74%. At trophic level 3, diet accounted for 62% - 100% of tissue selenium, with
a median of 95%. Thus, disregarding aqueous uptake of selenium only resulted in a small (-5%)
reduction in estimated selenium bioaccumulation in trophic level 3 organisms. These results are consistent
with previous studies indicating that diet is the primary exposure route of selenium, and suggests that the
uptake rate constant for selenium can be removed from Equation 1 with negligible effect for higher
trophic levels organisms.
3.0 Kinetics of Accumulation and Depuration: Averaging
Period
3.1 Background
For setting averaging periods for aquatic life criteria, U.S. EPA (1995b) used the concept that the
criterion averaging period should be less than or equal to the "characteristic time" describing the toxic
speed of action. In the context of the water-borne direct toxicity of metals, characteristic time = 1/k,
where k is the first-order kinetic coefficient in a toxico-kinetic model fitted to the relationship between
LC50 and exposure duration.
J-3
-------
In the context of selenium bioaccumulation in a single trophic level, k would the first-order
depuration coefficient, and 1/k would equal the time needed to depurate to a concentration of 1/e times
the initial concentration (where e=2.718). For depuration of multiple trophic levels sequentially, the
characteristic time is likewise the time needed for c/c0 to reach a value of 1/e, as shown in Figure J-la.
The accumulation curve is the inverted depuration curve, as shown in Figure J-lb.
TL3 on depurTL2
TL3 on clean diet
TL2 on depurTLl
TL1 in clean water
TL1 on fixed water cone
TL2 on accum TL1
TL3 on fixed contam diet
TL3 on accum TL2
Time, days
Time, days
Figures J-l a & b. Depuration and accumulation behavior for algae-detritus-sediment k=0.2/day,
invertebrate k=0.2/day and fish k=0.02/day, calculated with time step = 0.1 day.
Concentration is expressed as a dimensionless ratio: concentration at time t divided by either starting
concentration (Jla) or plateau concentration (Jib).
In the Figures J-l a & b examples, the characteristic time for algae-detritus-sediment is 5 days,
the characteristic time for invertebrates on an invariant diet is 5 days, the characteristic time for fish on an
invariant diet is 50 days, and the characteristic time for fish on an invertebrate diet that is itself depurating
or accumulating is the approximate sum of the individual characteristic times, or -60 days.
In contrast to the model depuration rate, k, the model uptake rate (AE, assimilation efficiency,
multiplied by IR, intake rate) does not affect the characteristic response time. Rather it affects the
magnitude of the accumulation plateau. Uptake rate thus affects the TTF value itself but is not relevant to
setting an averaging period.
Because short averaging periods are more environmentally conservative than long averaging
periods, selecting parameter values for fast kinetics is more environmentally conservative. Figure J1
reflects environmentally conservative choices for k values.
J-4
-------
3.2 Approach for Modeling Effects of Time-Variable Se Concentrations
Expression of concentrations. None of the concentrations in this analysis are expressed in ordinary units
of concentration. All concentrations are modeled as values normalized to their allowable benchmark
concentration - that is, concentration = 1 for a particular medium (water, algae-detritus-sediment,
invertebrates, or fish) means that the medium is at its criterion concentration or corresponding benchmark.
It is assumed that the benchmarks correctly align - water held at its benchmark concentration will
ultimately yield Trophic Levels 1, 2, and 3 at their respective benchmark concentrations. The Trophic
Level 3 benchmark is the reproductive EC10 for the 5th percentile taxon: i.e., the fish tissue criterion.
Formulation of the bioaccumulation model for kinetic analysis. For algae-detritus-sediment, for
invertebrates, and for fish, accumulation at time t equals accumulation at time t-1 plus intake minus
depuration, as follows:
Algae-detritus-sediment:
CTLi[t] = Cm [t-1] + kuptake C[t-l]water - kTL1 CTL1[t-l]
Invertebrates:
CtL2[t] = CTL2[t-l] + AETL2 1R-TL2 CTLi[t-l] - kTL2 CTL2[t-l]
Fish:
Ctls[t] = CTL3[t-l] + AETL3 IRtl3 CTL2[t-l] - kTL3 CTL3[t-l]
For algae-detritus-sediment, the depuration rate k is assigned a value of 0.2/day, similar to the
sum of depuration and growth-dilution rate coefficients used by Brix and DeForest (2008). Because a
lentic system would involve the slower kinetics of sediment exchange, the rapid rate used here implies a
lotic system.
For invertebrates, a value of 0.2/day was assigned, considerably higher than those for
Lumbriculus, Asian clam, zebra mussel, but close to those of mayfly and copepods, which are very small
in size. As previously mentioned, higher k (more rapid kinetics) is an environmentally conservative
assumption in this context.
For fish, the median depuration coefficient measured by Bertram and Brooks (1986) for 6-9
month-old (early adult) fathead minnows was used, providing a kTL3 value of 0.02/day. Because of the
small size of adults of this species, this represents faster kinetics than would likely be applicable the
salmonids and centrarchids of greatest concern for selenium toxicity. The striped bass k value of Baines et
al. (2002) is inapplicable here because it was measured in the early juvenile life stage, a size that is too
small to be relevant to reproductive impairment stemming from exposure of adult females. The
concentration in fish could be equivalently viewed as either whole body or egg-ovary, relative to their
J-5
-------
respective benchmarks. That is, partitioning within body of the fish is assumed not to involve a time
delay.
The value of a TTF is given by AE x IR/k (or kuptake/k for algae-detritus-sediment).
Concentrations in TL1, TL2, and TL3 are normalized to their benchmarks, meaning that all benchmark
concentrations have a value of 1.0. In this normalized context, the TTFs must also equal 1.0, since upon
reaching steady state, TL1 at its benchmark will yield TL2 at its benchmark, which in turn will yield TL3
at its benchmark. Again, the analysis is not intended to reflect actual concentrations, merely portray
temporal behavior. Since 1 = TTF = AE x IR/k, it follows that AE x IR = k within this normalized
framework. Although only the product AE x IR is relevant, they are retained as distinct parameters to
maintain parallelism with remainder of the criterion document. AE was assigned a value of 0.5 for fish
and invertebrates, and IR = k/AE in the normalized framework.
Time step durations of 0.1-1.0 day were considered. Short time steps increase accuracy by
decreasing the numerical dispersion inherent in expressing C[t] = f(C[t-l]). A time step of 0.5 day was
found to yield sufficient accuracy, as measured by predicted values at the characteristic time for
depuration or accumulation (per Figure J-l).
Prediction of Effects. The effect level associated with the tissue concentration at any time t is calculated
via the log probit concentration-response curve, one of the commonly used sigmoid curves. It assumes
that the sensitivities in the underlying population are log-normally distributed such that the concentration
yielding effects on k percentage of the population is given by:
ECk = EC50 exp(o z)
where o is the inverse of the concentration-response curve slope and z is the normal deviate
corresponding to k percent (e.g., for k=10%, z=NORMSINV(0.1)=—1.28155). Among the reproductive
impairment studies presented in Appendix C, an approximate median ratio for EC50/EC10 is 1.5. This
translates to o=0.3164.
J-6
-------
Since the fish tissue criterion concentration equals 1.0 in this normalized framework, at any time
t, the fractional level of effect corresponding to any value of Ctl3 is given by:
Fractional Effect[t] = NORMSDIST(z[tJ)
where z[t] is given by:
z[tj = LN(CTL3[t]/l. 5)/0.3164
Exposure Scenarios. Three exposure scenarios were evaluated under which the water criterion was just
barely attained. The first two are absolute worst case scenarios, in which the 30-day average water
concentration remains continuously at the criterion concentration at all times. The third is a realistic
scemario.
1. Steady concentrations at the criterion: this is worst-case continuous exposure. In the real world
this could not occur because water concentrations vary substantially over time. For the 30-day
average concentration not to exceed more than once in three years, the realistically varying daily
concentrations must remain well below the criterion concentration a large majority of the time.
2. Uniform 1-day spikes at 3 OX the water criterion concentration, occurring at uniform 30-day
intervals (i.e., separated by 29 days of zero concentration) such that the 30-day average always
equals the criterion. This is the worst-case intermittent scenario, attaining the criterion through a
time series that continually maximizes the 30-day average exposure at the water criterion
concentration while also imposing the highest variability possible from spikes of 1-day duration.
In the real world intermittent runoff sources do not occur at uniform intervals: merely averaging
30-days between discharges would yield an exceedance each time the discharge occurred with
less than 30-days spacing. Further, the once-per-month peak concentrations could never be
controlled at exactly 3 OX the chronic water criterion per the above discussion of the first scenario.
It is because they lack real-world random variability that the above two scenarios are not realistic.
They are used as absolute worst cases for purposes of comparison. The following third scenario
represents a realistic and indeed typical situation for continuous exposure:
3. Log-normally distributed, smoothly variable concentrations with the 30-day average exceeding
the criterion once in three years when counted using the procedure of EPA (1986). The log
J-7
-------
standard deviation of 0.5 applied here represents typical real-world time variability for
continuously flowing waters. The log serial correlation coefficient p = 0.8 represents that typical
of smaller streams.
With respect to maximizing toxic effects while attaining the criterion, Scenarios #1 and #2 are
absolute worst cases. In contrast, Scenario #3 represents typical time variability in ambient waters. This
third scenario requires randomly generated concentrations (having specified target statistical
characteristics). Multiple runs of long series are therefore needed to assure some reasonable degree of
accuracy. A minimum of 20 runs of random series of 3000 days were used. The concentrations at each
half-day time step were generated by the following formula:
C[t] water = C[t-1JwaterA(p') * GMA(l-p ) * EXP {a * SQRT(l-p ^2) *NORMSINV(RAND)}
where p' (rho prime) is the desired serial correlation coefficient between half-day time steps: p'=SQRT(p)
[approximation], where p (rho) is the desired serial correlation coefficient between daily values; GM is
the desired geometric mean or median, and o is the desired log standard deviation. The above formula
allows a time series with the desired statistical characteristics to be generated.
3.2.1 Model Results
3.2.1.1 Steady concentrations at the water criterion concentration.
No graphic is needed to explain this scenario. With water steady at its criterion, algae-detritus-
sediment and invertebrates are likewise steady at their benchmark concentrations, and fish tissue is at its
criterion concentration. For the 5th percentile taxon, the effect would thus be 10% since the concentration
is steady at the EC 10.
3.2.1.2 Uniformly spaced spikes at maximum concentrations
Figure J-2. Scenario 2, uniform 1-day spikes at 3 OX the water criterion concentration, occurring
at uniform 30-day intervals such that the 30-day average always equals the criterion. Read invertebrate
and fish tissue concentrations on left scale, water concentrations on right scale. Time=0 does not represent
the beginning of exposure; prior to Time=0 the same exposure pattern had been going on for a long time
(e.g., 10,000 days).
J-8
-------
TL3
35
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2.5
O
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2
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ro 1.5
o
QC
O
u
o
_fc
o
G
3
U>
U>
0.5
fish tissue
water daily
water 30-d avg
1 -
500
1000 1500 2000
Time, days
2500
3000
Figure J-3. A typical example of log-normally distributed, smoothly variable concentrations.
The standard deviation of natural logs is 0.5 and the serial correlation coefficient of logs is 0.8 for daily
values, both typical real-world situations. (The compression of 3000 days into the graph might make it
difficult to recognize that the time series is smoothly varying - it has serial correlation.) At time=0, TL1,
TL2, and TL3 begin at their average concentrations.
In the Figure J-3 example run, instantaneous water concentrations exceed the 30-day average
criterion 7% of the time. The 30-day average concentrations exceed the criterion 1.05 times per 3 year
period, counted per the EPA (1986) counting method. Tissue concentrations do not exceed their criterion
at anytime, and the aggregate effect is 0.12%.
hi contrast to the previous scenario, the elevated concentrations here are random in their
magnitude, duration, and spacing. This randomness reduces the average exposure (and aggregate effect)
compatible with attainment of the 30-day average water target.
3.2.2 Summary of Scenario Results
Because Scenario 3 involves generation of random concentrations, the above graphs show just
one run (3000 days) for each. Full results for the 20 runs of that scenario are shown below.
J-10
-------
Scenario
Water:
# 30-day avg.
exceedances /
3-yrl
Water:
% of time
exceeding
Tissue:
% of time
exceeding
Mean
effect
for 5th
%ile
Taxon
Comment
1. Steady
0.00
0.00
0.00
10.0
Steady at water and tissue
benchmarks
2. Uniform
spikes
0.00
3.33
56.7
10.0
30-d avg water conc. remains
steady at benchmark (Fig. J2)
3. Smooth
variable
1.01
7.8
0.00
0.18
Median=0.49 x benchmark, log
stdev=0.5, rho(daily)=0.8 (e.g.,
Fig. 5) 2
1. Counting procedure for 30-d avg. exceedances is that ol
2. Results for Scenario 3 are average of 20 runs of 3000 d,
Runs not yielding exceedances within these bounds were
CV=0.35.
fU.S. EPA (1986).
lys, each run with 0.6-1.4 exceedances / 3 yr.
lot used. Among the 20 runs used, the effect
It can be concluded that the kinetics of selenium accumulation and depuration are sufficiently
slow that applying a 30-day averaging period to the water criterion concentration affords protection even
under unrealistic worst case conditions.
3.2.3 Example Responses to Increases in Water Concentrations
The previous Figures J-2 and J-3 illustrate situations after achievement of a dynamic steady state,
where daily water concentrations change but longer-term mean water concentrations do not change.
Given the same kinetic parameters as used above (i.e., yielding a 60-day characteristic time), this section
addresses the rate at which tissue concentrations respond to increases in mean water concentrations, for
example as would result from a new source. This is similar to the rising curve previously shown in Figure
J-lb. The rapid kinetics used here for the water-TLl step imply a small lotic system having little
involvement of the bed sediments.
3.2.3.1 Step-function example
This example addresses the question: If water concentrations are increased to a level that is
slightly too high, ultimately (at Time=oo) yielding fish-tissue concentrations at the EC20 instead of the
EC 10, how long would it take for those tissue concentrations to rise to a level that exceeds the (EC 10-
based) criterion?
Prior to Time=0 in this example the concentrations in TL3 had been at a moderate background
concentration of 0.406 times the criterion, corresponding to the median West Virginia reference-site egg
concentrations tabulated by West Virginia Department of Environmental Protection (2010). The
concentrations in TL1 and TL2 are likewise assumed to have been at 0.406 normalized to their
corresponding benchmarks. At Time=0 the water concentrations increase such that ultimately they will
J-ll
-------
produce an effect 10% higher than the target, thus at the EC20 of the hypothetical 5th percentile sensitive
species. For typical selenium concentration-response slopes, this is 1.15-fold above the EC10. Figure J4
illustrates this scenario, which shows that 90 days are needed for TL3 concentrations to rise above the
criterion.
2.5
O
'i—
4)
u
o
¦M
0)
>
¦fish tissue
water daily
water 30-d avg
re 1.5
a;
0c
o
u
0)
¦M
re
0
a>
3
01
ui
0.5
50 100 150 200 250
Time, days
300
350
400
Figure J-4. TL3 concentration responding to a Time=0 step-function increase in water
concentration that remains time-invariant thereafter.
Given that the water concentration is too high, ultimately yielding tissue concentrations at the
hypothetical sensitive species EC20, 1.15-fold above the criterion, and given the previously presented
kinetic parameters, it is calculated to take 90 days for TL3 concentrations to rise above the criterion.
J-12
-------
3.2.3.2 Continuously time-variable example for flowing waters
To provide more realism, this example considers typical time variability, following up on Figure
J3. In this example, prior to Time=0, TL1, TL2, and TL3 concentrations were at a low background
concentration, 0.1 normalized to their criterion or respective benchmark. At Time=0 begin water
concentrations having median = geometric mean = 0.49 normalized as a dimensionless ratio,
concentration/criterion. Because the water concentrations are log-normally distributed, with log standard
deviation = 0.5, the arithmetic mean is higher than the median and has the normalized value 0.56. If the
simulation went on for a very long time, this time series (designed to have geometric mean 0.49 times the
criterion, log standard deviation 0.5, and log serial correlation coefficient 0.8) would average one
exceedance every three years, when exceedances are counted using the EPA (1986) approach. Figure J-5
shows atypical short series of 400 days.
2.5
O
'i—
O)
'i—
U
O
+¦>
0)
>
ro 1.5
o
oc
o
u
i—
41
¦M
o
o
3
(/>
V)
0.5
50
100
Time, days
— fish tissue
water daily
• water30-davg
-
1 1 1 1
150 200 250 300
1 1
350 400
Figure J-5. Flowing water example of TL3 concentration starting at a concentration of 0.1
normalized to the criterion, and responding to randomly varying log-normally distributed water
concentrations having median 0.49 (expressed as a dimensionless ratio: concentration/criterion), log
standard deviation 0.5, and log serial correlation coefficient 0.8.
Again, all concentrations are as dimensionless ratios relative to the criteria concentrations.
J-13
-------
Several points are worth noting. Because the water concentrations happen (by chance) to be
below average for the first 50 days, the TL3 concentrations rise somewhat slowly during that period.
Were they to be above average during that period, the TL3 concentrations would more rapidly approach
their dynamically varying plateau. In such a short time series it is not graphically apparent what the long-
term average TL3 concentration will be; however, because the long-term arithmetic mean water
concentration would be 0.56 (normalized the its criterion), the TL3 concentration would likewise end up
averaging 0.56 normalized to its criterion, if tracked for many years.
It is also worth noting that most 400-day series of the type shown in Figure J-5 would not have
occurrences of 30-day average concentrations above the criterion (as suggested by Figure J-3). This
particular random series does have a period of 30-day average exceedances, near Day 300, but it does not
persist long enough to cause the TL3 concentration to approach its criterion.
Lastly, it should be noted that when concentrations are randomly varying as in Figure J-5, the
water concentrations that one observes are highly dependent on when the samples are taken. The TL3
concentrations observed are far less dependent on when the samples are taken (after the plateau is
approached), but time variations, although muted, are still present.
The example scenarios depicted here show lotic time to steady state of approximately 3 months to
less than 1 year under different discharge scenarios including both continuous and intermittent discharges.
The scenarios also assume that the new selenium input is from one source; multiple new sources
particularly with varying discharge patterns, might have a different response time and pattern for various
trophic levels.
The example is likely not appropriate for lentic systems, because they would not be expected to
have the rapidly varying water concentrations of Figure J-5. In addition, the water-to-TLl kinetics would
likely be slower in lentic systems with new or time-varying sources because of the role of bottom
sediments acting as a reservoir in recycling selenium. Ultimately this should yield slower rising and
smoother TL3 concentrations compared to those in Figure J-5.
J-14
-------
APPENDIX K: Translation of a Selenium
Fish Tissue Criterion Element to a
Site-Specific Water Column Value
-------
1.0 Translating the Concentration of Selenium in Tissue to
a Concentration in Water Using Mechanistic
Bioaccumulation Modeling
Introduction:
EPA recommends fish tissue elements of the selenium criterion supersede water column elements
under steady state conditions because the selenium concentration in fish tissue is a more sensitive and
reliable indicator of the negative effects of selenium in aquatic life. However, implementation of a fish
tissue criterion element can be challenging because many state and tribal Clean Water Act (CWA)
programs prefer the expression of water quality criteria as an ambient concentration in the water-column.
Therefore, EPA also recommends two monthly average water-column criterion elements, one for lotic
(flowing) waters, and the other for lentic (still) waters. EPA derived all water column criterion elements
from the egg/ovary criterion element representing a protective selenium concentration for fish species
populations. Thus the water column criterion elements also represent protective selenium concentrations
for fish species populations. If threatened or endangered fish species are present, states and tribes may
need to derive alternative water column elements with a refined protection goal that account for site-
specific bioaccumulation characteristics.
EPA derived water-column criterion elements by modeling selenium bioaccumulation in aquatic
systems. The EPA worked with the United States Geological Survey to derive a translation equation
utilizing a mechanistic model of bioaccumulation previously published in peer-reviewed scientific
literature (Luoma et. al., 1992; Wang et. al., 1996; Luoma and Fisher, 1997; Wang, 2001; Schlekat et al.
2002b; Luoma and Rainbow 2005; Presser and Luoma 2006; Presser and Luoma 2010; Presser 2013).
EPA translated the selenium egg-ovary criterion element into two set(s) of site-specific water
concentration values (lentic and lotic), and used the distribution(s) of those water column values to derive
the respective water-column criterion elements. This appendix describes approaches that states and tribes
may choose to use regarding application of this same mechanistic modeling approach (or alternatively an
empirical bioaccumulation factor (BAF) approach) to translate a fish tissue criterion element (egg-ovary,
whole body, or muscle) into site-specific water-column concentrations to more precisely manage
selenium in specific aquatic systems.
The relationship between the concentration of selenium in the tissues of fish and the
concentration of selenium in the water column can vary substantially among aquatic systems. The species
of fish, the species and proportion of prey, and a variety of site-specific biogeochemical factors affect
selenium bioaccumulation and thus determine the allowable concentration of selenium in ambient water
protective of aquatic life. States and tribes may choose to adopt the results of site-specific water column
translations as site-specific criteria (SSC) or adopt a translation procedure into state or tribal water quality
K-2
-------
standards. Under both options, the water quality standards revisions must be approved by EPA under
Section 303(c) of the Clean Water Act. If a state or tribe adopts a translation procedure that will be
implemented by other CWA programs, it must be scientifically defensible, produce repeatable,
predictable outcomes, and result in criteria that protect the applicable designated use. Examples of such
approaches include the mechanistic modeling approach and the empirical BAF approach described within
this Appendix.
EPA considered both mechanistic and empirical modeling approaches to translate the selenium
egg-ovary criterion element into water column concentration elements. A mechanistic modeling approach
uses scientific knowledge of the physical and chemical processes underlying bioaccumulation to establish
a relationship between the concentrations of selenium in the water column and the concentration of
selenium in the tissue of aquatic organisms. The mechanistic modeling approach enables formulation of
site-specific models of trophic transfer of selenium through aquatic food webs and translation of the egg-
ovary criterion element into an equivalent site-specific water concentration. The empirical modeling
approach establishes a relationship between concentrations of selenium in fish tissue and ambient water
directly by measuring selenium concentrations in both media and calculating the ratio of the two
concentrations. The ratio (BAF) can then be used to estimate the target concentration of selenium in the
water column as related to the adopted fish tissue element.
Both the mechanistic and empirical modeling approaches have advantages and disadvantages that
should be considered before deciding which approach to use. On the one hand, the mechanistic modeling
approach has the advantage of not requiring extensive fish tissue sampling and analysis by using
knowledge of aquatic system food webs. However, uncertainty in the selection of model parameters
increases uncertainty in the outcome leading to a reduction in defensibility. Of particular concern with
respect to the mechanistic model EPA developed is the selection of the value for the enrichment factor
parameter EF (discussed in more detail below). On the other hand, the empirical BAF approach is
conceptually and computationally simpler because it relies only on field measurements and does not
require extensive knowledge of the physical, chemical, or biological characteristics of the aquatic system.
However, obtaining a sufficient number of measurements in fish tissue and water may be logistically
difficult and/or more expensive.
The appropriate modeling approach to use when translating the selenium egg-ovary criterion
element to a site-specific water-column concentration depends on individual circumstances and site-
specific characteristics. The mechanistic modeling approach may be a useful method in situations where
there is little or no data on the amount of selenium in an aquatic system, the empirical BAF approach may
be desirable in circumstances where in fish tissue and water data are available. Below is a description of
K-3
-------
methodology than can be used to translate the egg-ovary criterion element to a site-specific water-column
concentration for site-specific management of selenium.
1.1 Relating the Concentration of Selenium in Fish Tissue and Water using the Mechanistic Modeling
Approach
The relationship between the concentration of selenium in the eggs or ovaries of fish and the
concentration of selenium in the water column is given in Equation K-l (Equation 18 from the main text):
r
q egg-ovary
" TTFcomposUe xEFxCF (Equation K-l)
= the concentration of selenium in water (|ig/L),
= the concentration of selenium in the eggs or ovaries of fish (jug/g),
= the product of the trophic transfer factor (TTF) values of the fish species
that is the target of the egg-ovary criterion element and the TTF values
of all lower trophic levels in its food web (no units of measurement, see
explanation below).
= the steady state proportional bioconcentration of dissolved selenium at
the base of the aquatic food web (L/g),
= the species-specific proportion of selenium in eggs or ovaries relative to
the average concentration of selenium in all body tissues (no units of
measurement).
The basic principles expressed in Equation K-l are illustrated in the conceptual model shown in
Figure K-l.
Selenium dissolved in surface water enters aquatic food webs by becoming associated with
trophic level 1 primary producer organisms (e.g., algae) and other biotic (e.g., detritus) and abiotic (e.g.,
sediment) particulate material. An enrichment function (EF) quantifies the bioconcentration of selenium
in particulate material and thus its bioavailability in the aquatic system. The parameter EF is a single
value that represents the steady state proportional concentration of selenium in particulate material
relative to the concentration of selenium dissolved in water.
wnere:
Cwater
r
^egg-ovary
rj-'rjipc°mp°Site
EF
CF
K-4
-------
Organic particulate material is consumed by trophic level 2 organisms (usually aquatic
invertebrates, but also some fish species that are herbivores/detritivores) resulting in the accumulation of
selenium in the tissues of those organisms. Trophic level 2 invertebrates are consumed by trophic level 3
fishes resulting in further accumulation of selenium in the tissues of those fish. Bioaccumulation of
selenium from one trophic level to the next is quantified by a trophic transfer factor (TTF). A TTF is a
single value that represents the steady state proportional concentration of selenium in the tissue of an
organism relative to the concentration of selenium in the food it consumes. Different species of organisms
metabolize selenium in different ways. Thus each species is associated with a specific TTF value.
Because the trophic transfer of selenium through all trophic levels is mathematically equal to the product
of the individual TTF values, all consumer-resource interactions in a particular aquatic ecosystem are
simplified in Equation K-l by representing the product of all the individual TTF values as the single
parameter TTFvompostte.
Fish accumulate selenium in different tissues of the body in differing amounts. Species
physiology, age, diet, sex, and spawning status are some of the factors that affect selenium partitioning in
body tissues. Because the primary selenium criterion element is expressed as a concentration in the eggs
and/or ovaries, a conversion factor (CF) quantifies the relationship between the concentration of selenium
in the eggs and/or ovaries and the average concentration of selenium in the whole body or muscle tissues.
The parameter CF in Equation K-l is a single value that represents the steady state proportional
concentration of selenium in the eggs and/or ovaries relative to the average concentration of selenium in
all body tissues. Different species of fish accumulate selenium in their eggs and ovaries to different
degrees. Thus each species of fish is associated with a specific CF value.
K-5
-------
Egg-Ovary FCV
o Species Egg-Ovary to Whole-Body Conversion Factor (CF)
Fish Whole-Body
Concentration
Species Trophic Transfer Function (177' )
Invertebrate
Concentration
^J1Jipcomp°site'^
Species Trophic Transfer Function (TTF)
Concentration in
Particulate Material
o Enrichment Factor (EF)
Water-Column
Concentration
Figure K-l. Conceptual model for translating the egg-ovary FCV to a water-column concentration.
Note: States may want to use the whole body or muscle criterion elements as the starting point for site
specific translation to a water column concentration.
Once the parameters that quantify the transfer of selenium through each step in this pathway are
identified, they can be used with Equation K-l to translate the egg-ovary criterion element to a site-
specific concentration of selenium in the water column (i.e., target water column concentration).
Because each TTF value is species-specific, it is possible to differentiate bioaccumulation in
different aquatic systems by modeling the food web of the target fish species. For example, where the
food web contains more than 3 trophic levels, TTFcomposite can be represented as the product of all TTF
values for each trophic level given in Equation K-2, which is a generalization of Equation 10 from the
main text:
K-6
-------
TTF composite = jjj-712 x yyy.T/.J x x jjpTLn (Equation K-2)
Where:
I"/],-ompostw _ t|lc proc[Llct: 0f au TTF vaiues at all trophic levels.
777''"'" = the TTF value of the highest trophic level.
The consumption of more than one species of organism at the same trophic level can also be
modeled by expressing the TTF value at a particular trophic level as the average TTF values of all species
at that trophic level weighted by the proportion of species consumed given as Equation K-3 (Equation 11
in the main text):
TTF = ^ {TT1-]"X x wi) (Equation K-3)
i
Where:
TTI<]"-X = the trophic transfer factor of the i111 species at a particular trophic level
w; = the proportion of the ith species consumed.
These concepts can be used to formulate a mathematical expression of /'/ythat models
selenium bioaccumulation in a variety of aquatic ecosystems. Figure K-2 illustrates five hypothetical food
web scenarios and the formulation of TTFcomvosite for each of them. For each scenario, the value of
7,77-t;'""""'v"e. the CI'' value associated with the targeted fish species, and the site-specific value can be
used with Equation K-l to translate the egg-ovary criterion element to a site-specific water concentration
value. The hypothetical food web models in Figure K-2 are a few possible examples of food web models
for illustrative purposes. It is desirable to derive and use of a food web model that best represents the
aquatic system for which the water column translation will apply. The general steps for deriving a site-
specific translation of the egg-ovary criterion element to a water concentration value are described below.
K-7
-------
A) Three trophic levels (simple):
y 'y yy composite Y 'V X 1 'V
TT1''"J TTFtu
"w«
B) Four trophic levels (simple):
jijipcomposite rprpj^TIA ^ rprj^pTlT) ^ Y 'TFT12
JJfTL4 JJpTLi JJfTL2
~ 4^> ~
si»«
C) Three trophic levels (mix within trophic levels):
TTFcomposite = x ^12 x J+ x ^ )]
TTFtl2 j-ji.1*
77/'//? | w7 ^ 1
^—1 v>y^
TTF*12
D) Three trophic levels (mix across trophic levels):
jjpcomposite = {^JpTLi x WJ+ (tTFT" X TTFTL~ X W, )
—
&£££.'• ^ 1 ^ 'rf*
1 w2 << — '^T*
TTFtu
E)Four trophic levels (mix across trophic levels):
TTFcompoS,1e = ]^TpTLA ^ jjpTLi ^ w^+{^TpTU x W^TTF™
TTfTL4
TTpTL3
TTpTL2 t
JJpTL4
Figure K-2. Example mathematical expressions of 777^"mp"slte representing different food-web
scenarios.
jjpcomposite quantitatively represents the trophic transfer of selenium through all dietary pathways of a
targeted fish species. The mathematical expression of the food web model is used to calculate a value for
jjpcomposite usjng appr0priate species-specific TTF values and the proportions of each species consumed at
each trophic level. See text for further explanation.
K-8
-------
1.2 Steps for Deriving a Site-Specific Water Concentration Value from the Egg-Ovary Criterion
Element
Below are the steps for deriving a site-specific water concentration value from the selenium egg-
ovary criterion element using EPA's mechanistic model approach:
1) Identify the appropriate target fish species.
2) Model the food web of the targeted fish species.
3) Identify appropriate TTF values by either:
a. selecting the appropriate TTF values from a list of EPA-derived values, or
b. deriving TTF values from existing data, or
c. deriving TTF values by conducting additional studies, or
d. extrapolating TTF values from existing values.
4) Determine the appropriate value of EF by either
a. deriving a site-specific EF value from field measurements, or
b. deriving an appropriate EF value from existing data, or
c. extrapolating from EF values of similar waters.
5) Determine the appropriate CF value by either,
a. selecting the appropriate CF value from a list of EPA-derived values, or
b. deriving a ('!•' value from existing data, or
c. deriving a CF value by conducting additional studies, or
d. extrapolating a ('!•' value from existing values.
6) Translate the selenium egg-ovary criterion element into a site-specific water concentration value
using Equation K-l.
Below are detailed descriptions of each step followed by example calculations using a variety of
hypothetical scenarios. EPA is providing this information to support help states and tribes that choose to
develop selenium water column values from the egg-ovary criterion element or develop translation
procedures. Successful application of the mechanistic approach described here requires use of particular
food web models and parameter values that are appropriate for particular aquatic systems.
1.2.1 Identify the Appropriate Target Fish Species
1.2.1.1 When fish are present
In developing a site-specific translation of the egg-ovary criterion element, the user wshould
select whether to use a mechanistic model or empricial (BAF) approach. This decision will in large part
K-9
-------
determine the data and information requirements. A mechanistic model approach will likely require
information on the spatial and temporal distribution of aquatic organisms, and may require measurements
of selenium in ambient water and particulate material. An empirical model approach will use
measurements of selenium is fish tissue and ambient water.
Developing a site-specific translation of the egg-ovary criterion element will also entail selection
of which species of fish to target. The concentration of selenium in eggs and ovaries is the most sensitive
and consistent indicator of toxicity. However, toxicity and bioaccumulation potential can vary among
species. Species in the families Acipenseridae, Centrarchidae, and Salmonidae are particularly sensitive to
selenium (Table 3.3 in the main document), whereas species such as stoneroller species, creek chub,
blackside dace, and white sucker have documented tolerance to selenium and can be found in selenium
contaminated systems (NAMC 2008, Presser 2012). Green sunfish accumulate less selenium than other
species with comparable exposures in the same aquatic system (Hitt and Smith 2015). Selection of the
fish species in the aquatic system with the greatest selenium sensitivity and bioaccumulation potential is
recommended.
Several additional factors should also be considered in deciding which species to target when
developing a site-specific translation of the egg-ovary criterion element. Anadromous species (species
that migrate from salt water to spawn in fresh water) should generally avoided because selenium exposure
and bioaccumulation occurs over a relatively long period through the consumption of locally
contaminated aquatic organisms. Additionally considerations include whether the fish species selected
typically consume organisms known or suspected to readily bioaccumulate selenium (e.g., mollusks). For
example, high concentrations of selenium in San Francisco Bay white sturgeon are associated with their
consumption of Potamocorbula amurensis, a bivalve in close proximity to selenium-contaminated
sediments that rapidly and efficiently accumulates selenium (Stewart et al. 2004). In contrast, striped bass
from the same aquatic system have substantially lower concentration of selenium in their tissues because
their zooplankton-based food web has substantially lower selenium bioaccumulation characteristics
(Schlekat et al. 2004; Stewart et al. 2004). The 2016 selenium criterion was developed for freshwater, but
if considering other ecosystems, it may be worth noting that salinity may also affect bioaccumulation of
selenium. Freshwater mollusks tend to have relatively higher TTF values when compared to other
freshwater invertebrate taxa (e.g., aquatic insects), but they are lower than mollusks in marine or brackish
systems (and particularly P. amurensis, an invasive clam in the San Francisco Bay). In aquatic systems
with resident fish species of unknown selenium sensitivity and bioaccumulation potential, other factors
such as ecological significance could be considered when choosing a target species.
Data from fisheries or biological surveys or other biological assessments could be considered to
determine the fish species that reside in specific surface waters. State and tribal resource agency personnel
K-10
-------
familiar with fish sampling activities could also be a source of information on resident fish species.
General information on the fish species present in state and tribal surface waters may also be found at:
• State Fish and Game agencies
• U.S. Fish and Wildlife Service (http://www.fws.gov)
• U.S. Geological Survey (http://www.usgs.gov)
• NatureServe.org (http://www.natureserve.org)
• Fishbase (http://www.fishbase.org)
• State or local sources of biological information (e.g. Biota Information System of New Mexico at
http://www.bison-m.org)
Measurements of selenium in fish tissue would most reflect the ecosystem if adult (reproductively
mature) fish are sampled. Selenium measurements in fish tissue will likely be more stable in adult fish
because they are more likely to have a stable prey base. Reproductively mature (ripe or gravid) females
would be needed for measures selenium in eggs and/or ovary tissue for comparison to the the egg-ovary
tissue criterion element. It would be prudent to avoid sampling ovary tissue "post-spawn" due to a
potential decrease in selenium concentration presumably due to the loss of selenium through spawning
and release of eggs with relatively high concentrations of selenium. Consideration of closely related
taxonomic surrogates (same genus or family) for threatened or endangered species may be useful.
Figure K-3 shows an example decision tree that may help in selection of the appropriate fish
species for deriving a site-specific water concentration value from the selenium egg-ovary, whole-body,
or muscle FCV. The use of taxonomic hierarchies for anlysis utilizes evolutionary relationships to infer
biological similarities among organisms (Suter 1993). Additional information on fish tissue sampling
(e.g., species selection, temporal and spatial considerations) is under development and will be published
in the form of a technical support document (TSD) by the EPA in the near future.
K-ll
-------
Are nonanadromous species of the
Acipenseridae or Salmonidae families
present?
Yes
r
1
No
r
Target nonanadromous species in the
Acipenseridae or Salmonidae families
Are species in the genus Lepomis
present?
Yes
No
r
f
1
Target species in genus Lepomis (e.g.,
bluegill)
Is family Centrarchidae present?
Yes
No
r
r
1
Target species in family Centrarchidae
(e.g. bass)
Are resident species with confirmed or
suspected sensitivity or exposure risk to
selenium present?
Yes
r
1
No/do not know
r
Target resident species with confirmed or
suspected sensitivity or exposure risk to
selenium.
Target species with highest ecological
significance.
Figure K-3. Recommendeed decision process for selection of the fish species to use when deriving a
water concentration from the selenium egg-ovary FCV.
This decision tree is also generally applicable when using the whole body or muscle tissue as the starting
point for development of SSC, particularly when using the BAF approach.
1.2.1.2 When fish are absent from a site
Some aquatic systems do not contain resident fish. Fish may be absent from a waterbody because
of intermittent or persistent low flows, physical impediments such as waterfalls or impoundments, lack of
adequate habitat for feeding and/or spawning, or intolerable aquatic conditions related to pH, turbidity,
temperature, salinity, total dissolved solids, chemical contaminants, or pathogens. These conditions could
be due to natural or anthropogenic causes. Some streams may be naturally intermittent or ephemeral, or
K-12
-------
they might exhibit low or intermittent flows because of impoundments or water draw-down for
agricultural irrigation, industrial uses, drinking water supply, or other uses.
When fish are absent from a waterbody, consideration of sampling the most sensitive fish species
inhabiting nearby, most proximate downstream waters may be useful in order to understand selenium
bioaccumulation potential in such systems. Although the upper reaches of some aquatic systems may not
support fish communities, the invertebrate organisms that reside there may tolerate high concentrations of
selenium and pose a selenium risk to predator fish if transported downstream. Users may choose to
evaluate upstream waters without fish by measuring the selenium concentration in water, biotic and/or
abiotic particulate material, and/or the tissues of invertebrate aquatic organisms that reside there. Because
selenium associated with particulate material and invertebrate organisms can be transported downstream
during intermittent high flows, elevated concentrations of selenium in the tissues of downstream fish
could indicate upstream sources of selenium that require a more detailed evaluation of upstream
conditions.
1.2.2 Model the Food-Web of the Targeted Fish Species
After selecting the target fish species, model users should formulate a mathematical expression of
the target species food-web that will be used to calculate the value of As discussed
previously, /'/yis the product of the TTF values across trophic levels of the target fish species
food-web. The complexity of the food-web model will depend on the species of fish that is targeted, the
diversity of prey species in the aquatic system, and the amount of information that is available. Many of
the same information sources used to identify the targeted fish species in a waterbody could also be used
to obtain information about its food web. The types and proportions of food organisms the targeted fish
species consumes can be directly assessed through studies that examine stomach contents or from
information gathered through biological assessments. If site-specific information is not available, model
users could estimate the target fish species food-web using publicly available databases such as
NatureServe (http://www.natureserve.org). For example, the NatureServe database record for fathead
minnow in the HUC watershed #5040004 in Ohio indicates under the heading: "Ecology and Life History
- Food Comments," the fathead minnow "feeds opportunistically in soft bottom mud; eats algae and other
plants, insects, small crustaceans, and other invertebrates (Becker 1983, Sublette et al. 1990)."
Additional sources of information include:
• FishBase (http://www.fishbase.org). FishBase is a relational database developed at the World
Fish Center in collaboration with the Food and Agriculture Organization of the United Nations
(FAO) and many other partners.
K-13
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• Carlander, K.D. Handbook of Freshwater Fishery Biology, volumes 1, 2 and 3. Iowa state
University Press, Ames, Iowa. 1969-1997.
1.2.3 Identify Appropriate TTF Values
The food-web model uses appropriately selected species-specific TTF values (and, if appropriate,
proportions within the same trophic level). Model users identify the appropriate TTF values by using one
of the following four procedures, or by using other scientifically defensible methods.
1.2.3.1 Select the appropriate TTF values from the provided list of EPA-derived values
Species-specific TTF values represent the steady state proportional concentration of selenium in
the tissue of an organism relative to the concentration of selenium in the food it consumes. EPA-derived
TTF values for aquatic invertebrates and fish are provided in Tables K-1 and K-2 (Tables 3.10 and 3.11 in
main text; see also main text for a complete explanation of the procedure EPA used to derive these
values).
K-14
-------
Table K-l. EPA-derived Trophic Transfer Factor (TTF) values for freshwater aquatic
invertebrates.
AE = Assimilation efficiency (%), IR = Ingestion rate (g/g-d), ke = Elimination rate constant ( J)
Com 111011 name
Scienlilic name
ai:
Ik
K
Ill
Crustaceans
amphipod
Hyalella azteca
-
-
-
1.22
copepod
copepods
0.520
0.420
0.155
1.41
crayfish
Astacidae
-
-
-
1.46
water flea
Daphnia magna
0.406
0.210
0.116
0.74
Insects
dragonfly
Anisoptera
-
-
-
1.97
damselfly
Coenagrionidae
-
-
-
2.88
mayfly
Centroptilum triangulifer
-
-
-
2.38
midge
Chironimidae
-
-
-
1.90
water boatman
Corixidae
-
-
-
1.48
Mollusks
asian clam3
Corbicula fluminea
0.550
0.050
0.006
4.58
zebra mussel
Dreissena polymorpha
0.260
0.400
0.026
4.00
Annelids
blackworm
Lumbriculus variegatus
0.165
0.067
0.009
1.29
Other
zooplankton
zooplankton
-
-
-
1.89
a Not to be confused with Potamocorbula amurensis
Table K-2. EPA-derived Trophic Transfer Factor (TTF) values for freshwater fish.
AE = Assimilation efficiency (%), IR = Ingestion rate (g/g-d), ke = Elimination rate constant (/d).
Common name
Scienlilic name
ai:
ik
k.
Ill
Cypriniformes
blacknose dace
Rhinichthys atratulus
-
-
-
0.71
bluehead sucker
Catostomus discobolus
-
-
-
1.04
longnose sucker
Catostomus catostomus
-
-
-
0.90
white sucker
Catostomus commersonii
-
-
-
1.11
flannelmouth sucker
Catostomus latipinnis
-
-
-
0.98
common carp
Cyprinus carpio
-
-
-
1.20
creek chub
Semotilus atromaculatus
-
-
-
1.06
fathead minnow
Pimephales promelas
-
-
-
1.57
red shiner
Cyprinella lutrensis
-
-
-
1.31
redside shiner
Richardsonius balteatus
-
-
-
1.08
sand shiner
Notropis stramineus
-
-
-
1.56
Cyprinodontiformes
western mosquitofish
Gambusia affmis
-
-
-
1.21
northern plains killifish
Fundulus kansae
-
-
-
1.27
Esociformes
northern pike
Esox lucius
-
-
-
1.78
Gasterosteiformes
brook stickleback
Culaea inconstans
-
-
-
1.79
K-15
-------
Com moil 11:11110
Sciont il'ic 11:1111c
ai:
ik
k.
Ill
Perciformes
black crappie
Pomoxis nigromaculatus
-
-
-
2.67
bluegill
Lepomis macrochirus
-
-
-
1.03
green sunfish
Lepomis cyanellus
-
-
-
1.12
largemouth bass
Micropterus salmoides
-
-
-
1.39
smallmouth bass
Micropterus dolomieu
-
-
-
0.86
striped bass
Morone saxatilis
0.375
0.335
0.085
1.48
walleye
Sander vitreus
-
-
-
1.60
yellow perch
Percaflavescens
-
-
-
1.42
Salmoniformes
brook trout
Salvelinus fontinalis
-
-
-
0.88
brown trout
Salmo trutta
-
-
-
1.38
mountain whitefish
Prosopium williamsoni
-
-
-
1.38
cutthroat trout
Oncorhynchus clarkii
-
-
-
1.12
rainbow trout
Oncorhynchus mykiss
-
-
-
1.07
Scorpaeniformes
mottled sculpin
Cottus bairdi
-
-
-
1.38
sculpin
Cottus sp.
-
-
-
1.29
Siluriformes
black bullhead
Ameiurus melas
-
-
-
0.85
channel catfish
Ictalurus punctatus
-
-
-
0.68
The TTF values from these lists could be used exclusively, or in conjunction with TTF values
obtained from other sources (see below). Note that these tables do not represent an exhaustive list of all
TTF values that may be required to calculate a site-specific water concentration value. If this list does not
include a required TTF value, another approach could be considered to obtain an appropriate value.
1.2.3.2 Deriving TTF values from existing data
If model users cannot obtain one or more required TTF values from Tables K-l and/or K-2,
species-specific TTF values could be derived using existing data. One approach for deriving species-
specific TTF values is to use the physiological coefficients representing food ingestion rate (IR), selenium
efflux rate (kc), and selenium assimilation efficiency (A A) to calculate a TTF value using Equation K-4
(Equation 3 from the main text, Reinfelder et al. 1998) given as:
K-16
-------
TIF =
Where:
TTF = species-specific trophic transfer factor
AE = species-specific assimilation efficiency (%)
IR = species-specific ingestion rate (g/g-d)
ke = species-specific efflux rate constant (/d)
(Equation K-4)
The physiological coefficients IR, AE and are species-specific values. Values for AE and kc can
only be derived from laboratory studies. Values for IR may be derived from laboratory studies or obtained
from published literature. After the three physiological coefficients are obtained, a TTF value can be
calculated using Equation K-4.
Another way to derive species-specific TTF values is to empirically assess the relationship
between the selenium concentration in the tissue of organisms and the selenium concentration in the food
they consume using paired measurements from field studies. Species-specific TTF values can be derived
from such measurements by calculating ratios, using regression techniques, or other scientifically
defensible methods.
Model users could choose to use the same approach EPA used to calculate species-specific TTF
values. EPA derived TTF values using a combination median and regression approach. EPA defined the
TTF value for any trophic level as:
siTLn
TTFTLn = (Equation K-5)
Cfood
Where:
j jpTLn = trophic transfer factor of a given trophic level,
£tissue = The selenium concentration (mg/kg dw) in the tissues of the consumer
organism,
Cjggd = The selenium concentration (mg/kg dw) in the consumer organism's
food.
EPA used the median of the ratios given in Equation K-5 as the species-specific TTF value, but
only if an empirical relationship between the paired measurements could be confirmed by linear
K-17
-------
regression analysis. EPA considered the relationship acceptable if a linear regression of tissue selenium
concentration on food selenium concentration resulted in both a statistically significant fit (P < 0.05) and
a positive slope (i.e., selenium concentrations in the consumer increases with increasing selenium in
food).
1.2.3.3 Deriving TTF values by conducting additional studies
Additional studies could be conducted to obtain the data needed to derive TTF values for specific
needs, or to revise existing TTF values, if the existing TTF values do not appear to be appropriate for a
particular aquatic system.
1.2.3.4 Extrapolating TTF values from existing values
If one or more necessary TTF values are not available, and the information needed to derive a
species-specific TTF value is not available or impractical to obtain, model users could consider
extrapolating a new TTF value from other known TTF values. One possible method to extrapolate a TTF
value is to sequentially consider higher taxonomic classifications until one or more of the organisms with
a known TTF value matches the taxon being considered. If the lowest matching taxon is common to more
than one of the available TTF values, the average TTF from the matching table entries could be used. The
use of taxonomic hierarchies in this way utilizes evolutionary relationships to infer biological similarities
among organisms (Suter 1993).
EPA used such an extrapolation approach to derive some of the TTF values necessary to develop
the water column criterion elements. For example, the TTF value for Chrosomus eos (northern redbelly
dace) was not available. TTF values were also not available for other species in the genus Chrosomus, but
TTF values were available for species in the family Cyprinidae, including Rhinichthys atratulus
(blacknose dace), Cyprinus carpio (common carp), Semotilus atromaculatus (creek chub), Pimephales
promelas (fathead minnow), Cyprinella lutrensis (red shiner), Richardsonius balteatus (redside shiner),
and Notropis stramineus (sand shiner). Because Cyprinidae is the lowest taxonomic classification where
Chrosomus eos matches one or more species with an available TTF value, EPA used the median TTF
value of blacknose dace, common carp, creek chub, fathead minnow, red shiner, redside shiner, and sand
shiner as the TTF value for northern redbelly dace.
1.2.4 Determine the Appropriate EF Value
The selenium enrichment function (EF) value represents the bioavailability of selenium at the
base of the aquatic food web. The base of the aquatic food web includes phytoplankton, periphyton,
detritus, inorganic suspended material, biofilm, sediment and/or attached vascular plants (Presser and
Luoma, 2010). EPA refers to this mixture of living and non-living entities as particulate material. The
parameter varies more widely across aquatic systems than any other parameter, and is influenced by
K-18
-------
the source and form of selenium, water residence time, the biogeochemical characteristics of the
waterbody, and the type of particulate matter collected. Because EF can vary greatly across waterbodies,
this parameter has the greatest potential to introduce uncertainty in the translation from an egg-ovary
selenium concentration to a water column concentration. For this reason, use values derived from site-
specific data is recommended whenever possible in applying the model. One of the following four
procedures could be used to derive values, or other scientifically defensible methods could be used.
1.2.4.1 Deriving a site-specific EF value from field measurements
Equation 12 from the main text defines the parameter EF as the ratio of the concentration of
selenium in particulate material to the concentration of selenium dissolved in water given as:
r
j i t ' particulate /r~, . T7-
hr (Equation K-6)
^water
Where:
C
particulate = Concentration of selenium in particulate material (|ig/g)
Q
water = Concentration of selenium dissolved in water (|ig/L)
EF = Enrichment Function (L/g)
To calculate a site-specific lvalue, EPA first calculates the ratio of each individual particulate
measurement and its associated water measurement (if more than one water measurement is available for
any given particulate measurement, the median water measurement is used). If more than one ratio for
any given category of particulate material is available (e.g., more than one ratio of algae to water), EPA
takes the median of the ratios. EPA then calculates the geometric mean of the median ratios for each
category of particular material as the site value. EPA only uses sediment measurements if there are at
least one measurement from either algae or detritus.
Deriving a site-specific EF value in this manner is a relatively straightforward procedure.
However, consideration of data that appropriately accounts for the spatial and temporal variability of an
aquatic system would be useful in the development of any sampling plan. Aquatic system characteristics
such as dimension, volume, shape, residence time, velocity, and growing season are a few important
factors that should be considered in designing a sampling plan that will adequately account for variability.
State and Federal agencies (USGS, ACOE) as well as watershed groups may be useful sources of
information that can help characterize the temporal and spatial variability at a particular aquatic system.
When developing the selenium criterion, EPA observed a relatively lower correlation between the
selenium concentration in water and abiotic (benthic sediments) particulate samples compared to the same
analysis between water and biotic (algae and detritus) particulate samples, resulting in EPA's decision
K-19
-------
that calculation of any site-specific values include information from at least one type of biotic
particulate indeveloping its criteiron. Prioritization of sampling of biotic particulate material over abiotic
samples should be considered. Regaridng selenium measurements from abiotic particulate material,
consideration of utilizing at least one type of biotic particulate material when deriving the EF value of an
aquatic system is recommended.
Site-specific values using particulate and water samples that are as spatially and temporally
coincident as possible would be considered the most robust. Although EPA's analysis of particulate and
water samples from a sample population of aquatic systems found that samples taken within one year of
each other, based on data availability, were appropriate in deriving the national criterion (Figure 3.5 in the
main document), a site-specific EF value would ideally involve collecting particulate and water samples
at the same location and time to ensure their representativeness of sirte-specific conditions. One simple
and effective sampling and analysis scenario would be to collect water samples or a combination of
particulate and water samples, separate the particulate material from the water in each sample by filtering,
measure the concentration of selenium in the separated water and particulate material, compute the ratio
of the two measurements from each sample, and then calculate the mean or median of all the ratios.
Selenium bioaccumulation occurs more readily in aquatic systems with longer residence times
(such as lakes, reservoirs, oxbows, and wetlands) and with fine particulate sediments high in organic
carbon. A well-planned sampling protocol was developed in association with the development of a site-
specific water-column criterion for selenium in the San Francisco Bay Delta2. States and tribes may also
want to consult Doblin et al. (2006) for specific particulate sampling methods. EPA's National Rivers and
Streams Assessment3 also provides methods for quantitative periphyton sampling that commonly
represents the base of many aquatic food webs. Analytical methods to measure selenium in particulate
material and in water are discussed in Appendix L.
1.2.4.2 Deriving an appropriate EF value from existing data
If suitable and sufficient site-specific measurements of selenium in particulate material and water
are already available, the model user may be able to use that data to derive an appropriate value.
However, it would be important to ensure that the data represents current conditions, were collected and
analyzed using scientifically sound sampling and analytical techniques, and proper quality assurance and
quality control protocols were implemented.
1.2.4.3 Extrapolating from values of similar waters
2
https://www3.epa.gov/region9/water/ctr/selenium-modeling_admin-report.pdf
3 https://www.nemi.gov/methods/method_summary/12558/ (EPA-841-B-07-009) and
https://www.nemi.gov/methods/method_summary/12565/ (EPA-841-B-12-009)
K-20
-------
In circumstances where a site-specific, field-derived EF value is not available or practical to
develop, an EF value from one or more aquatic systems with similar hydrological, geochemical, and
biological characteristics could be used to estimate EF. However, there is a possibility of introducing
significant uncertainty when using values extrapolated from other aquatic systems. More information
on this topic is contained in Appendix H of this document.
1.2.5 Determine the Appropriate CF Value
1.2.5.1 Selecting the appropriate ('/¦' value from the list of values that were used to derive EPA's
recommended water criteria concentration values
The parameter CF represents the species-specific proportion of selenium in eggs or ovaries
relative to the average concentration of selenium in all body tissues. EPA derived species-specific CF
values for 20 species of fish from studies that measured selenium concentrations in both eggs and/or
ovaries and in whole body and/or muscle. These CF values can be found in Appendix B and are
reproduced below (Table K-3).
Table K-3. Selenium Whole Body to Egg-Ovary Conversion Factors (CF).
Common name
Median ratio
(Cegg-ovary/ Cwhole-
body)
Median ratio
(Cegg-ovary/
Cmuscle)
Muscle to
whole-body
correction
factor
Final CF
values
Species
Bluegill
2.13
2.13
Bluehead sucker
1.82
1.82
Brook trout
1.09
1.27
1.38
Brown trout
1.45
1.45
Creek chub
1.99
1.99
Common carp
1.92
1.92
Cutthroat trout
1.96
1.96
Desert pupfish
1.20
1.20
Dolly Varden
1.26
1.27
1.61
Fathead minnow
1.40
1.40
Flannelmouth sucker
1.41
1.41
Green sunfish
1.45
1.45
Mountain whitefish
5.80
1.27
7.39
Northern pike
1.88
1.27
2.39
Rainbow trout
1.92
1.27
2.44
K-21
-------
Com in on 11:11110
Median ratio
(Ce«»»-o\ arxl C w hole-
hod v)
Median ratio
(C 'e«»}»-o\ a vyl
(muscle)
Muscle to
whole-hody
correction
factor
linal (1
\ allies
Razorback sucker
2.31
1.34
3.11
Roundtail chub
2.07
2.07
Smallmouth bass
1.42
1.42
White sturgeon
1.33
1.27
1.69
White sucker
1.38
1.38
Genus
Catostomus
1.41
Gila
2.07
Lepomis
1.79
Micropterus
1.42
Oncorhynchus
1.96
Family
Catostomidae
1.41
Centrarchidae
1.45
Cyprinidae
1.95
Salmonidae
1.71
Order
Cyprinodontiformes
1.20
Perciformes
1.45
Class
Actinopterygii
1.45
The data and methods used to derive the CF in this table are described in Appendix B.
K-22
-------
1.2.5.2 Deriving a CFvalue from existing data
The parameter CF is mathematically expressed as Equation K-7 (Equation 16 in the main text):
G
CF =
' egg-ovary
r
whole-body (Equation K-7)
Where:
CF = Whole-body to egg-ovary conversion factor (dimensionless ratio).
Cegg-ovary = Selenium concentration in the eggs or ovaries of fish (jug/g)
Cwhole-body = Selenium concentration in the whole body of fish (mg/kg).
If suitable and sufficient data are available, a model user could derive a species-specific CF value
using the same numerical methods described above to calculate the parameter EF. The median of the
ratios given in Equation K-7 could be used as the species-specific CF value, but only if an empirical
relationship between the paired measurements could be confirmed by linear regression analysis. IN
deriving the national criterion, EPA considered it to be acceptable if a linear regression of egg-ovary
selenium concentration on whole body selenium concentration resulted in both a statistically significant
fit (P < 0.05) and a positive slope. Other scientifically defensible methods could be used. Regardless of
the method used, the user should ensure that the data used to derive CF values were collected using
adequate quality assurance and quality control protocols.
1.2.5.3 Deriving a CF value by conducting additional studies
Additional studies could be performed to obtain data needed to derive CI'' values for specific
needs or to revise existing CF values if there is reason to believe doing so may increase the accuracy of
the resulting water concentration value. Analytical methods to measure selenium in tissue are discussed in
Appendix L. Where appropriate, additional data could be obtained as part of a NPDES permit application
by invoking authority under CWA section 308 (or comparable state or tribal authority) to require NPDES-
regulated facilities to collect information necessary to develop permit limits.
1.2.5.4 Extrapolating the CF value from the list of values that were used to derive EPA's recommended
water criteria concentration values
If one or more necessary CF values are not available, and the information needed to derive a
species-specific CF value is not available or impractical to obtain, a model user could could consider
extrapolating a new CF value from other known CF values. One possible method to extrapolate a CF
value is to use the same taxonomic approach EPA uses for TTF values that are not available for specific
K-23
-------
species (Section 1.2.3.4). Sequentially consider higher taxonomic classifications could be considered until
one or more of the fish species with a known CF value matches the taxon being considered. If the lowest
matching taxon is common to more than one of the available CF values, the average CI'' value from the
matching table entries could be used.
1.2.6 Translate the Selenium Egg-Ovary Criterion Element into a Site-Specific Water
Concentration Value using Equation K-l
Model users could derive a site-specific water concentration value from the egg-ovary criterion
element value using Equation K-l with appropriate values of CF, 77(derived from the product of
the individual TTF values from each trophic level) and EF. Note that NPDES permitting regulations at 40
CFR § 122.45(c) requires that a Water Quality-Based Effluent Limit (WQBEL) for metals be expressed
as total recoverable metal, unless an exception is met under 40 CFR § 122.45(c)(l)-(3). Equation K-l
assumes selenium concentrations dissolved in water. While states and tribes may express ambient water
quality criteria in water quality standards as dissolved selenium, an additional step would be necessary to
convert the dissolved selenium concentration to a total recoverable selenium concentration for the
purpose of NPDES permitting. Guidance for converting expression of metal concentrations in water from
dissolved to total recoverable can be found in Technical Support Document for Water Quality-based
Toxics Control (U.S. EPA 1991) and The Metals Translator: Guidance for Calculating a Total
Recoverable Permit Limit from a Dissolved Criterion (U.S. EPA 1996).
1.3 Managing Uncertainty using the Mechanistic Modeling Approach
Uncertainty in the translation of the egg-ovary criterion element to a water column value using
the mechanistic bioaccumulation modeling approach (Equation K-l) can arise from several sources.
These include:
• Measurement error when deriving input parameters,
• Inaccurate food web models due to misidentification and/or incorrect proportions of prey
organisms,
• Inaccurate or inappropriate EF, TTF, and/or CF values,
• Biological variability,
• Unaccounted factors affecting bioaccumulation (e.g. selenium speciation), and
• Other unknown factors.
The most influential step in selenium bioaccumulation occurs at the base of aquatic food webs
(Chapman et al. 2010). The parameter Eb' characterizes this step by quantifying the partitioning of
K-24
-------
selenium between the dissolved and particulate state. EF can vary by at least two orders of magnitude
across aquatic systems (Presser and Luoma 2010). The greatest reduction in uncertainty could be
achieved when translating a fish tissue concentration of selenium to a water column concentration using
Equation K-l by using temporally and spatially coincident site-specific empirical observations of
dissolved and particulate selenium of sufficient quality and quantity to accurately characterize EF.
Presser (2013) provides several recommendation to reduce uncertainty in an ecosystem scale
approach to deriving a site-specific selenium water column criterion in a coal mining impacted area of
West Virginia. Suggested actions to reduce uncertainty include:
• Obtaining temporally matched pairs of selenium measurements in dissolved and particulate
material across a broad range of sites to ensure the samples accurately characterize the aquatic
system and to assess sample variability;
• Characterizing particulate material across seasons to better define the base of the food web;
• Evaluating aquatic systems variables such as residence time, watershed dilution, and physical
habitat attributes on as fine a scale as possible;
• Refining model assumptions to accurately characterize dietary preferences and composition of
fish, and develop additional TTF values if necessary;
• Identify and target fish species particularly sensitive to selenium;
• Consider temporal changes in the bioaccumulation potential of the aquatic system and changes in
selenium sensitivity over the life cycle of fish; and
• Consider variability in hydrology and selenium discharges.
The suitability of selected equation parameters could be determined by obtaining fish tissue and
water column measurements of selenium from small-scale field studies, use of equation K-l to estimate
one measurements using the other, and comparison of the estimated concentration with the actual
concentration (see Section 6.2.1 of the main document for a description of EPA's validation approach).
1.4 Example Calculations
Below are six hypothetical examples that demonstrate how to translate the egg-ovary FCV to a
site-specific water concentration criterion using Equation K-l. These examples encompass a variety of
hypothetical aquatic systems with various fish species and food webs. For these hypothetical examples,
species-specific TTF values were taken from Tables K-l and K-2, and CF values were taken from Table
K-3. To calculate EF in these examples, the EPA used a hypothetical water concentration of 5 (ig/L and
the hypothetical particulate concentrations of 4.25 jj.g/g and 8.75 jj.g/g in lotic and lentic aquatic systems,
respectively.
K-25
-------
1.4.1 Example 1
Bluegill (Lepomis macrochirus) in a river that consume mostly amphipods:
Current water concentration (|ig/L)
5.00
Current particulate concentration (mg/kg)
4.25
Trophic transfer factor for bluegill (TTFTL3)
1.03
Trophic transfer factor for amphipods (TTFTL2)
1.22
Egg-ovary to whole-body conversion factor for bluegill (CF)
2.13
Selenium egg-ovary FCV (mg/kg)
15.1
__ ^particulate
hh =
C
4
EF =
water
4.25
5.00
= 0.85 L/g
r
uegg-ovary
water ffpcomposite x pp x £p
TTpcomposite rj~"j~,j^TL3 ^ y ,j_^-TL2
= 1.03 x 1.22
= 1.26
15.1
r —
uwater
1.26 x 0.85 x 2.13
= 6.62 (ig/L
K-26
-------
1.4.2 Example 2
Fathead minnow (Pimephales promelas) in a river that consume mostly copepods:
Current water concentration (|ig/L)
5.00
Current particulate concentration (mg/kg)
4.25
Trophic transfer factor for fathead minnow (TTFTL3)
1.57
Trophic transfer factor for copepods (TTF1L2)
1.41
Egg-ovary to whole-body conversion factor for fathead minnow (CF)
1.40
Selenium egg-ovary FCV (mg/kg)
15.1
Cparticulate
EF - —
uwater
4.25
EF =
5.00
= 0.85 L/g
r
_ _ uegg-ovary
water ~ J"fpcomposite x pp x Qp
TTpCOmpOSite y Ty 'pTL3 ^ y Ty 'j^-TL2
= 1.57 x 1.41
= 2.21
15.1
Cwater ~ 2.21 x 0.85 x 1.40
= 5.74 jig/L
K-27
-------
1.4.3 Example 3
Bluegill (Lepomis macrochirus) in a lake that consume mostly aquatic insects:
Current water concentration (|ig/L)
5.0
Current particulate concentration (mg/kg)
8.75
Trophic transfer factor for bluegill (TTFTL3)
1.03
Trophic transfer factor for aquatic insects (median of Odonates, Water
boatman, Midges, and Mayflies) (TTFTL2)
2.14
Egg-ovary to whole-body conversion factor for bluegill (CF)
2.13
Selenium egg-ovary FCV (mg/kg)
15.1
Cparticulate
EF - —
uwater
8.75
EF =
5.00
= 1.75 L/g
r
uegg-ovary
-water
j'j'pcomposite x £F X CF
TTFComPosite ' J^TLS x
= 1.03x2.14
= 2.20
15.1
Cwater ~ 2.20 x 1.75 x 2.13
= 1.84 jig/L
K-28
-------
1.4.4 Example 4
Fathead minnow (Pimephales promelas) in a river that consume approximately % copepods and lA aquatic
insects:
Current water concentration (|ig/L)
5.0
Current particulate concentration (mg/kg)
4.25
Trophic transfer factor for fathead minnow (TTFTL3)
1.57
Trophic transfer factor for copepods and aquatic insects (TTF1L2)
Copepods =1.41
Average of all aquatic insects = 2.14
T1, xw/)
XTF = i=l
1.65
= (1.41 x %) + (2.14 x i/3)
= 1.65
Egg-ovary to whole-body conversion factor for fathead minnow (CF)
1.40
Selenium egg-ovary FCV (mg/kg)
15.1
Cparticulate
br —
r
°water
4.25
EF =
5.00
= 0.85 L/g
r
uegg-ovary
-water
j'j'pcomposite x £F X CF
TTFcomPosite XTF ^ 'J."I'F
= 1.57 x 1.65
= 2.59
15.1
Cwater ~ 2.59 x 0.85 x 1.40
= 4.90 jig/L
K-29
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1.5.5 Example 5
Flathead chub (Platygobio gracilis) in a river with a diet of approximately 80% aquatic insects and 20%
Current water concentration (|ig/L)
5.0
Current particulate concentration (mg/kg)
4.25
Trophic transfer factor of flathead chub:
Lowest matching taxon is the family Cyprinidae. Therefore, the TTF value of
Cyprinidae is used (TTFTL3)
1.20
Trophic transfer factor for insects (TTF1L2)
Average of all aquatic insects = 2.14
2.14
Egg-ovary to whole-body conversion factor for flathead chub (species-specific
value not available, so median CF for family Cyprinidae is used). (CF)
1.95
Selenium egg-ovary FCV (mg/kg)
15.1
Cparticulate
Cwater
= 0.85 L/g
TTFcomposite = [ffpTLS x TTpTL2 x WJ + [ffpTLS x
Where:
wi = Proportion of fathead chub diet from insects; and
w2 = Proportion of fathead chub diet from algae
TTFcomb = ^ 20 x 2.14 X 0.8] + [1.20 X 0.2]
= 2.29
r
°egg -ovary
-water J"fpcomposite x pp x Qp
15.1
C,
water 2^g x x
= 3.98 (Ig/L
K-30
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1.5.6 Example 6
Largemouth bass (Micropterus salmoides) in a large river that consume mostly Western mosquitofish
Current water concentration (|ig/L)
5.0
Current particulate concentration (mg/kg)
4.25
Trophic transfer factor of largemouth bass (TTFTL4)
1.39
TT 3
Trophic transfer factor of Western mosquitofish (TTF )
1.21
Trophic transfer factor for insects and crustaceans (TTF1L2)
Median all Insects - 2.14
Median all Crustaceans - 1.41
ttfil2= i=i
1.96
= (2.14 X 0.75) +(1.41 X 0.25)
= 1.96
Egg-ovary to whole-body conversion factor for largemouth bass (species-
specific value not available, so median CF for genus Micropterus is used) (CF)
1.42
Selenium egg-ovary FCV (mg/kg)
15.1
EF =
EF =
-particulate
Cwater
4.25
5.00
= 0.85 L/g
TTFComPosite XTFTL4 x nj~'nj~'J7TL2
= 1.39 x 1.21X 1.96
= 3.30
°egg -ovary
-water J"fpcomposite x pp x Qp
15.1
-water
3.30 x 0.85 x 1.42
= 3.79 jig/L
K-31
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2.0 Translating the Concentration of Selenium in Tissue to
a Concentration in Water using Bioaccumulation
Factors (BAF)
2.1 Summary of the BAF Approach
A bioaccumulation factor (BAF) is the ratio (in milligrams/kilogram per milligrams/liter, or liters
per kilogram) of the concentration of a chemical in the tissue of an aquatic organism to the concentration
of the chemical dissolved in ambient water at the site of sampling (U.S. EPA 2001c). BAFs are used to
relate chemical concentrations in aquatic organisms to concentrations in the ambient media of aquatic
ecosystems where both the organism and its food are exposed and the ratio does not change substantially
overtime. The BAF is expressed mathematically as:
C
BAF = ¦
Where:
r
water (Equation K-8)
BAF = bioaccumulation factor derived from site-specific field-collected
samples of tissue and water (L/kg)
Ctissue = concentration of chemical in fish tissue (mg/kg)
CWater = ambient concentration of chemical in water (mg/L)
The site-specific BAF can then be applied to the tissue criterion to solve for a target site-specific water
column criterion (Ctarget):
Cv, Ceqq—ovary criterion /T^ n\
target X ~—^ (Equation K-9)
Where:
Ctarget = site-specific water criterion concentration (mg/L)
Cegg-ovary criterion = national egg-ovary tissue criterion (15.1 mg Se/kg dw)
BAF = bioaccumulation factor derived from site-specific field-collected
samples of tissue and water (L/kg)
To translate a fish tissue criterion to a water concentration value, a site-specific, field-measured
BAF for the waterbody could be developed, and then a water concentration criterion could be calculated
using Equation K-9. Detailed information about how to derive a site-specific, field-measured BAF is
provided in Methodology for Deriving Ambient Water Quality Criteria for the Protection of Human
Health (2000) Technical Support Document Volume 3: Development of Site-specific Bioaccumulation
K-32
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Factors (U.S. EPA 2009). Although this guidance was developed for deriving human health criteria, the
methodological approach is also applicable to the derivation of aquatic life criteria. The following
example illustrates the calculation of a site specific water column criterion using the BAF approach.
2.1.1 Example: Derivation of a site specific water column criterion for a waterbody impacted by
selenium
Available data for a hypothetical site indicate that the average egg/ovary tissue concentration of
selenium for the bluegill (Lepomis macrochirus) is 22 mg/kg (dw). This concentration exceeds the
USEPA proposed egg/ovary criterion of 15.1 mg/kg (dw). The ambient selenium water column
concentration at that hypothetical site is 4.0 (ig/L. The following calculation shows how to derive a target
water column that would achieve a site-specific criterion using the bioaccumulation factor (BAF)
approach.
Site specific selenium egg/ovary concentration (bluegill; mg/kg dw)
22.0
Selenium egg/ovary criterion (mg/kg, dw)
15.1
Ambient selenium water column concentration (|ig/L)
4.0
Target water column concentration (|ig/L)
X
Set up proportional equation to solve for allowable water column concentration:
Site specific egg/ovary conc. Criterion egg ovary conc. (™g
Site specific water concentration Target water concentration
Solve for the target water concentration that will achieve a site-specific criterion:
22 0 (mgSe) 15 1 (m9 Se )
lb-l^kgdw)
4.0 (r^£—) Target water concentration
Target water concentration = 2.75 (ig/L.
2.2 Managing Uncertainty using the BAF Approach
Uncertainty can be introduced when using the BAF approach to derive a water concentration
value from a fish tissue criterion concentration. Inaccurate water concentration values can result when
BAFs are derived from water and fish tissue concentration measurements that are obtained from sources
that do not closely represent site characteristics, or from field data collected from large-scale sites that
encompass multiple water bodies or ecosystems. Most of this uncertainty results from differences in the
K-33
-------
bioavailability of selenium between the study sites where measurements are made to derive the BAF, and
the site(s) to which the BAF is used to derive needed water concentration values.
Because of uncertainties associated with the BAF approach, EPA does not recommend
developing BAFs from data extrapolated from different sites or across large spatial scales. EPA's
Framework for Metals Risk Assessment (U.S. EPA 2007) outlines key principles about metals and
describes how they should be considered in conducting human health and ecological risk assessments due
the the effects of water chemistry on bioavilability of such chemicals. The current science does not
support the use of a single, generic threshold BAF value as an indicator of metal bioaccumulation. The
use of BAFs are appropriate only for site-specific applications where sufficient measurements have been
taken from the site of interest and there is little or no extrapolation of BAF values across differing
exposure conditions and species.
The preferred approach for using a BAF to implement the selenium fish tissue criterion is to
calculate a site-specific, field-measured BAF from data gathered at the site of interest, and to apply that
BAF to that site. A site-specific, field-measured BAF is a direct measure of bioaccumulation in an aquatic
system because the data are collected from the aquatic ecosystem itself and thus reflects real-world
exposure through all relevant exposure routes. A site-specific, field-measured BAF also reflects biotic and
abiotic factors that influence the bioavailability, biomagnification, metabolism, and biogeochemical
cycling of selenium that might affect bioaccumulation in the aquatic organism or its food web.
Appropriately developed site-specific, field-measured BAFs are appropriate for all bioaccumulative
chemicals, regardless of the extent of chemical metabolism in biota from a site (U.S. EPA 2000).
Although a site-specific, field-measured BAF is a direct measure of bioaccumulation, its
predictive power depends on a number of important factors being properly addressed in the design of the
field sampling effort. For example, sampling in areas with relatively long water residence times should be
a priority because selenium bioaccumulation occurs more readily in aquatic systems with longer residence
times (such as wetlands, oxbows, and estuaries) and with fine particulate sediments high in organic
carbon. In addition, migratory species should generally not be used because their exposure to selenium
could reflect selenium concentrations in areas other than where the fish were caught. Fish may also need
to be sampled and BAF values recalculated if selenium levels significantly change over time because
BAFs are known to be affected by the ambient concentration of the metals in the aquatic environment
(McGeer et al. 2003; Borgman et al. 2004; DeForest et al. 2007). States and tribes should refer to
Methodology for Deriving Ambient Water Quality Criteria for the Protection of Human Health (2000)
Technical Support Document Volume (U.S. EPA 2009) for guidance on appropriate methods for
developing a site-specific, field-derive BAF.
K-34
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The advantage of using the BAF approach is its relative simplicity, especially when the data
necessary to derive the BAF is already available. Furthermore, the BAF approach is completely empirical
and does not require any specific knowledge about the physical, chemical, or biological characteristics of
the waterbody. The relationship between the concentration of selenium in fish tissue and water is directly
determined by direct measurements in these media. This may be advantageous when there are
uncertainties with how to collect a particulate sample that is representative of the base of the food web, or
dilution concerns (e.g., sandy streams with little surface area for algae sampling and high potential for
sand contamination of a benthic sediment sample).
Limitations of the BAF approach should be considered before deciding if this method is
appropriate for translating the selenium FCV to a water concentration value. One disadvantage of the
BAF approach is the considerable effort and resources necessary to collect sufficient data to establish the
relationship between tissue and water concentrations. Resource use increases as the spatial scale and
complexity of the aquatic system increases. Furthermore, the BAF approach does not allow extrapolation
across species, space, and large time scales because the site-specific factors that might influence
bioaccumulation are integrated within the tissue concentration measurements and thus cannot be
individually adjusted to extrapolate to other conditions. Thus, site-specific, field-measured BAFs only
provide an accounting of the uptake and accumulation of selenium for an organism at a specific site and
point in time. This is more important in lotic habitats, since the kinetics of selenium bioaccumulation may
be very different at a site upstream or downstream from the site of interest.
As noted previously, NPDES permitting regulations at 40 CFR § 122.45(c) require WQBELs for
metals be expressed as total recoverable metal unless an exception is met under 40 CFR § 122.45(c)(1)-
(3). Guidance for converting expression of metals in water from dissolved to total recoverable can be
found in Technical Support Document for Water Quality-based Toxics Control (U.S. EPA 1991) and The
Metals Translator: Guidance for Calculating a Total Recoverable Permit Limit from a Dissolved
Criterion (U.S. EPA 1996). Whether or not a water concentration value derived from a site-specific, field-
derived BAF requires conversion from dissolved to total recoverable selenium depends on how the BAF
is developed. Generally, conversion would not be necessary if the BAF is derived from water
concentration values that measure total selenium; however, conversion would be necessary if the BAF
was derived from water concentration values that measured dissolved selenium. Table K-4 compares
some of the principle characteristics of the mechanistic bioaccumulation modeling approach or the BAF
approach for translating the selenium FCV to a water concentration.
K-35
-------
3.0 Comparison of Mechanistic Bioaccumulation Modeling
and BAF Approaches
Data from Saiki et al. (1993) are used here to illustrate an example comparison of the two
translation approaches, the mechanistic bioaccumulation modeling approach and the bioaccumulation
factor (BAF) model approach. Definitive selenium measurements for all ecosystem compartments (e.g.,
water, algae, etc.) are available for two species, bluegill and largemouth bass, at four sites. Food web
pathways were calculated using results of gut content analysis. Although Saiki et al. (1993) satisfies the
minimum requirements for a site specific translation, it represents a sparse dataset, with only two
measurements per ecosystem compartment, one for the spring and fall of 1987, respectively. For purposes
of this exercise, samples from the same site collected at different time periods will be treated as replicate
data; however, EPA recommends using larger sample sizes collected during the same time period when
calculating a site specific criterion.
Selenium data used to calculate site specific water criteria are included in Table K-4. Median
concentrations and coefficients of variation for each ecosystem compartment at each site are included in
Table K-5. Because at most only two concentrations were available for each ecosystem, site median are
equal to site averages. Site specific translations for both approaches will be calculated using median
selenium concentrations.
K-36
-------
Table K-4. Selenium concentrations in ecosystem compartments for four sites described in Saiki et al. (1993).
Water concentrations expressed as [ag/L. all other concentrations expressed as mg/kg dw.
Largemouth
Site
Date
Water
Algae
Detritus
Amphipod
Chironomid
Crayfish
Zooplankton
Bluegill
Bass
Mud Slough at Gun
Fall
3
7.40
22
4.6
8.9
5.2
2.4
6.4
6.8
Club Road
1987
Mud Slough at Gun
Spring
9
1.60
7.9
3.3
7.2
4.4
5.4
5
6.9
Club Road
1987
Salt Slough at the San
Fall
Luis National Wildlife
3
0.38
8.9
3.4
5.4
3.1
4.5
4.5
4.7
Refuge
1987
Salt Slough at the San
Spring
Luis National Wildlife
13
2.40
7.9
3.7
6.9
3.2
4.4
4.3
4
Refuge
1987
San Joaquin R. above
Fall
3
1.20
6.6
3.8
6
1.7
2.6
3.3
2.2
Hills Ferry Road
1987
San Joaquin R. above
Spring
11
1.30
3.4
2.8
4.1
1.9
4.3
2.7
2.4
Hills Ferry Road
1987
San Joaquin R. at
Fall
1987
Durham Ferry State
1
0.39
1.2
1.5
1.5
0.77
1.6
2
1.8
Recreation Area
San Joaquin R. at
Spring
1987
Durham Ferry State
0.50
1.3
1.1
1.6
1.3
1.8
1.9
1.7
Recreation Area
K-37
-------
Table K-5. Median selenium concentrations in ecosystem compartments for four sites described in Saiki et al. (1993).
For purposes of this exercise, spring and fall samples measured at the same site are treated as replicates. Water concentrations expressed as (.ig/L.
all other concentrations expressed as mg/kg dw. Coefficients of determination included in parentheses.
Largemouth
Site Water Algae Detritus Amphipod Chironomid Crayfish Zooplankton Bluegill Bass
Mud Slough at Gun
Club Road
Salt Slough at the
San Luis National
Wildlife Refuge
6.0
(0.71)
8.0
(0.88)
4.50
(0.91)
1.39
(1.03)
14.95
(0.67)
8.40
(0.08)
3.95 (0.23)
3.55 (0.06)
8.05 (0.15)
6.15 (0.17)
4.80 (0.12)
3.15 (0.02)
3.90 (0.54)
4.45 (0.02)
5.70
(0.17)
4.40
(0.03)
6.85 (0.01)
4.35 (0.11)
San Joaquin R. above
Hills Ferry Road
7.0
(0.81)
1.25
(0.06)
5.00
(0.45)
3.30(0.21)
5.05 (0.27)
1.80 (0.08)
3.45 (0.35)
3.00
(0.14)
2.30 (0.06)
San Joaquin R. at
Durham Ferry State
Recreation Area
1.0 (na)
0.45
(0.17)
1.25
(0.06)
1.30 (0.22)
1.55 (0.05)
1.04 (0.36)
1.70 (0.08)
1.95
(0.04)
1.75 (0.04)
K-38
-------
3.1 Translation using the BAF Approach
Site specific BAFs were calculated for bluegill and largemouth bass at each of the four sites
(Table K-6). A site-specific water criterion was calculated for each species at the four sites using equation
K-8, which is equivalent to the BAF example shown in the previous section. The site specific criterion
calculation for bluegill at site "Salt Slough at the San Luis National Wildlife Refuge" is included below as
an example.
BAF =
'tissue
'water
4-4 \ig/g
8 \ig/L
= 0.55 L/g
-tissue criterion
'water criterion ~
BAF
8.5 mg/kg
0.55 L/g
= 15.5 [ig/L
The whole body tissue criterion of 8.5 mg/kg is used here because whole body fish tissue
selenium measurements were made. If site specific egg ovary fish tissue had been measured, then the egg
ovary tissue criterion of 15.1 mg/kg would have been used.
Table K-6. Site and species specific translated water concentrations using the BAF translation
liliicgill:
l.sir^ciiioiilh lisiss:
Water
Water
Water
WIJ Se
ISA I-"
SSC
W li Se
IJAI
SSC
Sile
(Mli/U
(!-/«•)
(MB/1-)
(I./Ji)
(MB/I-)
Mud Slough at Gun Club
Road
6.0
5.70
0.95
8.95
6.85
1.14
7.45
Salt Slough at the San Luis
National Wildlife Refuge
8.0
4.40
0.55
15.45
4.35
0.54
15.63
San Joaquin R. above Hills
Ferry Road
7.0
3.00
0.43
19.83
2.30
0.33
25.87
San Joaquin R. at Durham
Ferry State Recreation Area
1.0
1.95
1.95
4.36
1.75
1.75
4.86
a - Site specific criterion based on BAF
br respective species.
At each site, the lowest translated water criterion for all species is used as the site specific
criterion. At site "Mud Slough at Gun Club Road," the site specific criterion is based on the translated
concentration for largemouth bass, and at the other 3 sites, the site specific criterion is based on the
translated concentration for bluegill. Site specific water concentrations calculated using the BAF
approach range from 4.4 to 19.8 (ig/L Table K-6).
K-39
-------
3.2 Translation using the Mechanistic Bioaccumulation Modeling Approach
The first step in the bioaccumulation modeling approach is the calculation of site specific
enrichment factors (EFs). Because both algae and detritus selenium concentrations were available, the
first step was the calculation of separate EFs for algae and detritus at each site, following the procedures
described in section 1.2.4.1. Algal and detrital EFs, respectively, were calculated using the median of all
Se concentrations in algae (or detritus) at a site by the median of all Se concentrations in water at the
same site. After calculating separate algal and detrital EFs, the final EF at each site was calculated as the
geometric mean of the algal and detrital EF at a given site. Algal, detrital, and site EFs are shown in
Table K-7.
Table K-7. Se concentrations in water, algae, detritus, and site specific EFs.
She
Water
(HJi/l)
Algae
Detritus
i:i (i./«)
Mud Slough at Gun Club
Road
6.0
4.50
14.95
1.37
Salt Slough at the San Luis
National Wildlife Refuge
8.0
1.39
8.40
0.43
San Joaquin R. above Hills
Ferry Road
7.0
1.25
5.00
0.36
San Joaquin R. at Durham
Ferry State Recreation Area
1.0
0.45
1.25
0.75
As an example, the EF calculation for site "Salt Slough at the San Luis National Wildlife Refuge" is
shown below.
_ Calgae _ Cdetritus
al9ae ~ ; ttdetritus ~ water
EFsite I {EFalgae * ^detritus)
1.39 mg/kg ^ 8Amg/kg
ait"16 ~ 8.0 [ig/L ' btdetritus ~ 8.0 [ig/L
EFsite = 7(0.17 x 1.05)
EFsite = 0.43 L/g
The second step in the bioaccumulation modeling approach is the calculation of site specific
composite trophic transfer factors (XTFcomposite). Based on gut content analysis, bluegill diets consisted of
K-40
-------
47% amphipods, 23% chironomids, and 30% zooplankton, while largemouth bass diets consisted of 73%
bluegill and 27% crayfish.
The composite TTF for bluegill was calculated using the following equation:
TTFcomposite = [j-fpTLS x TTpTL2 x WJ + [ffpTLS x TTpTL2 x
+ [TTFTL3 X TTF712 X W3]
Where:
Wi =
w2 =
w3 =
proportion of diet from amphipods,
proportion of diet from chironomids, and
proportion of diet from zooplankton.
For each of the 3 species in the bluegill diet, site specific TTFTL3 and TTFTL2 were calculated
separately. Using median concentrations from Table K-5, xTFcomposite were calculated for each of the sites
and are included in Table K-8.
Table K-8. Trophic transfer factors (TTFs) for bluegill and bluegill prey.
1 1.2 Ills:
1 1.3 I I
liC-
Is:
liC-
liC-
Silo
Amphipod C'lii
ronomid
/ooplanklon
Ampli
( hiro
/oo
Blue-ill
Mud Slough at Gun Club
Road
0.41
0.83
0.40
1.44
0.71
1.46
0.59
Salt Slough at the San Luis
National Wildlife Refuge
0.73
1.26
0.91
1.24
0.72
0.99
0.90
San Joaquin R. above Hills
Ferry Road
1.06
1.62
1.10
0.91
0.59
0.87
0.96
San Joaquin R. at Durham
Ferry State Recreation Area
1.53
1.83
2.01
1.50
1.26
1.15
2.30
As an example, the bluegill xTFcomposite for site "Salt Slough at the San Luis National Wildlife Refuge" is
shown below.
TTFcomposite = ^ 24 x 0.73 X 0.47] + [0.72 X 1.26 X 0.23] + [0.99 X 0.91 X 0.30]
j"j
-------
The composite TTF for largemouth bass was calculated using the following equation:
TTFcomposite = yj-fpTU x jjpTLS x TTpTL2 x WJ + [TTpTL3 x TTpTL2 x ^
Where:
Wi = proportion of diet from bluegill, and
W2 = proportion of diet from crayfish
For the proportion of the largemouth bass diet consisting of bluegill, TTFTL3 x TTFTL2 was equal
to the xTFcomposite for bluegill. As was the case for bluegill, site specific TTFs were calculated for each
species, and are included in Table K-9.
Table K-9. Trophic transfer factors (TTFs) for largemouth bass and largemouth bass prey.
Cnivrish diclsirv
lilucgill diclsirv
IViK'lion:
I.MIi-
IViiclion:
Sile
Crayfish
Crav
Blue-ill'
LMIMUi
1MB
Mud Slough at Gun Club
Road
0.49
1.43
0.59
0.70
0.49
Salt Slough at the San Luis
National Wildlife Refuge
0.64
1.38
0.90
0.89
0.82
San Joaquin R. above Hills
Ferry Road
0.58
1.28
0.96
0.74
0.71
San Joaquin R. at Durham
Ferry State Recreation Area
1.22
1.69
2.30
2.06
4.03
a _ XTFcomposite for bluegill.
As an example, the largemouth bass XTFcombmed for site "Salt Slough at the San Luis National Wildlife
Refuge" is shown below.
TTpcomVosite = ^pppTLA x TTpComposite x + [TTpTL3 x TTpTL2 x
TTpcomposite = [0 gg x 0 90 x 0 73] + 38 x 0 54 x 0 27]
J"ppcomposite = 0 82
After calculating site and species specific EF and xTFcombmed, site specific water criterion concentrations
were calculated using a modified version of equation K-l, shown below.
K-42
-------
Cwater criterion ~
Ctissue criterion
EF x XTFcomPos^e
The site specific criterion calculation for bluegill at site "Salt Slough at the San Luis National Wildlife
Refuge" is included below as an example.
8.5 mg/kg
Cwater criterion = 0.43 L/gx0_90 = 22 A ^9,1
Because the selenium in fish tissue at these sites were measured as whole body concentrations,
the whole body criterion of 8.5 (ig/L is used, and an egg-ovary to whole body conversion factor is not
required. As with the BAF approach, the lowest translated water criterion for all species is used as the site
specific criterion. At site "San Joaquin R. at Durham Ferry State Recreation Area," the site specific
criterion is based on the translated concentration for largemouth bass, and at the other 3 sites, the site
specific criterion is based on the translated concentration for bluegill. Site specific water concentrations
calculated using the mechanistic bioaccumulation modeling approach are more variable than
concentrations calculated using the BAF approach, and range from 2.8 to 33.3 (ig/L Table K-10). At all
sites using both methods, the translated site specific water concentration criteria were higher than the
measured water concentrations.
Table K-10. Site and species specific translated water concentrations using the mechanistic
bioaccumulation modeling approach.
Kliiegill:
Lsirgemoiilh IJiiss:
Water
Water
i:i
WIJ So
ssc
WIJ So
SSC
Silo
(l-/g)
(mg/kg)
III
(MS/I )
(mg/kg)
III
(MS/I-)
Mud Slough at Gun Club
Road
1.37
5.70
0.59
10.61
6.85
0.49
12.65
Salt Slough at the San Luis
National Wildlife Refuge
0.43
4.40
0.90
22.14
4.35
0.82
24.18
San Joaquin R. above Hills
Ferry Road
0.36
3.00
0.96
24.79
2.30
0.71
33.31
San Joaquin R. at Durham
Ferry State Recreation Area
0.75
1.95
2.30
4.95
1.75
4.03
2.83
3.3 Summary Comparison of the Mechanistic Bioaccumulation and BAF Approaches
A comparison of the mechanistic bioaccumulation and BAF approaches is included in Table K-
11.
K-43
-------
Table K-ll. Comparison of mechanistic bioaccumulation and BAF approaches.
Mechanistic hioaccinmilalion modeling
liioacciimulalion I'aclor (IJAI )
Knowledge of the aquatic system needed
No information on aquatic system needed
Choice of input parameters at discretion of
state or tribe
No input parameters to choose
Species-specific
Species-specific
Can be applied at different sites if site EF can
be estimated.
Site-specific
Fish tissue sampling not required for
translation
Fish tissue and water sampling required
K-44
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APPENDIX L: Analytical Methods for
Measuring Selenium
L-l
-------
The Clean Water Act (CWA) establishes an EPA approval process for certain analytical methods
used in the National Pollutant Discharge Elimination System (NPDES) program and for section 401
certifications. EPA has several approved methods for measuring selenium in water under 40 CFR § 136.
EPA generally requires the use of EPA-approved methods for the NPDES program and for CWA section
401 certifications issued by states and tribes (40 CFR § 136.1). However, since there are no EPA
approved methods for the analysis of selenium in fish tissue, states and tribes may use analytical methods
not approved by EPA to evaluate the attainment of water quality standards or to develop or implement
Total Maximum Daily Loads provided that these methods are scientifically sound (40 CFR 122.21(g)(7)).
Implementation of a water quality standard for selenium may require the ability to detect and
measure the concentration of selenium in effluent, ambient water, tissue, and other media that is below
the detection limit or limit of quantitation that some analytical methods can provide. States and tribes
should choose an analytical method that is sufficiently sensitive to implement its water quality standard
for selenium. Below are descriptions of some of the methods available for measuring selenium
concentrations with sufficient sensitivity to implement EPA's recommended selenium criterion. Complete
descriptions of analytical methods appropriate for analyzing selenium in different media can be found in
the National Environmental Methods Index at http://www.nemi.gov.
1.0 General Considerations when Measuring
Concentrations of Selenium
The oxidation states of selenium dissolved in surface water are usually selenate (+6), selenite
(+4), and organo-selenium (-2). The presence of selenium in different oxidation states complicates some
analytical methods (Presser and Ohlendorf 1987). EPA recommends using standard reference samples to
check for the percentage recovery of each species of selenium (selenate, selenite and organo-selenium)
during initial testing of selenium methodologies for quality control and assurance.
If water samples are not filtered, particulate species such as elemental selenium and particulate
organo-selenium will also be measured. In addition, federal regulations at 40 CFR § 122.45(c) generally
requires considering total recoverable metals when establishing effluent limits and reporting
requirements.
2.0 Analytical Methods Recommended for Measuring
Selenium in Water
EPA has several approved analytical methods under 40 CFR § 136 specifically for measuring
total selenium in water. These regulations state that measurements for NPDES permit applications and
permittee reporting should be made using analytical methods approved by EPA. Because EPA has
L-2
-------
approved methods for analyzing selenium in water, these methods must be used for NPDES permits (40
CFR § 122.21(g)(7), 122.41(j), 136.1, 136.3, and 136.6).
A complete list of EPA-approved analytical methods for selenium can be found at:
http://www.epa.gov/waterscience/methods/method/. Three EPA-approved methods that may be
sufficiently sensitive4 for the purposes of implementing a selenium water quality criterion are listed below
(Table L-l).
Table L-l. Suggested EPA-Approved Methods for Selenium in Water
Method
Technique
Method
detection limit
American Public Health Standard
Method 3114 B (2009) or 3114 C
(2009)
Hydride generation atomic absorption
spectrometry (HG-AAS)
2 |_ig/L
EPA Method 200.8, Rev 5.4
(1998)
Inductively coupled plasma mass
spectrometry (ICP-MS)
7.9 (ig/L
EPA Method 200.9, Rev.2.2
(1994)
Stabilized temperature graphite
furnace atomic absorption (STGF-AA)
0.6 |_ig/L
2.1 American Public Health Standard Method 3114 B
For measuring selenium in water, American Public Health Standard Method 3114 B uses the HG-
AAS technique. Method 3114 B has a method detection limit (MDL) of 2 (ig/L. Samples for dissolved
analytes should be filtered on-site through 0.45-micron capsule filters certified free of trace-element
contamination or other appropriate filtering equipment (Wilde et al. 1999). Dissolved samples should be
preserved with high purity hydrochloric acid or nitric acid to a pH less than 2.
For measuring total selenium, samples should not be filtered. In addition, all selenium in the
sample should be in the form of selenite (+4). Thus, the following pre-treatment steps to convert all
selenium in the sample to selenite are critical when using the HG-AAS method:
1. Boiling with persulfate to oxidize and digest organic material.
2. Boiling with hydrochloric acid to reduce selenate species to selenite.
3. Reduction by sodium borohydride to hydrogen selenide in the quartz tube of the AAS.
4
For more information on choosing a sufficiently sensitive method, see the memorandum Analytical Methods for Mercury in
National Pollutant Discharge Elimination System (NPDES) Permits from James A. Hanlon, Director of the Office of Wastewater
Management, dated August 23, 2007, available at http://www.epa.gov/npdes/pubs/mercurymemo analvticalmethods.pdf.
L-3
-------
Optimal conversion conditions are essential for accurate results because too mild a reduction
could lead to incomplete reduction of selenate and too rigorous a reduction could lead to plating out of
elemental selenium (Cutter 1987, 1983; Presser and Barnes 1984, 1985).
Method 3114 B has the advantage that it is a fully validated method, is commonly used by many
laboratories, is relatively inexpensive, is less susceptible to background interference (Cutter 1987, 1983;
Presser and Barnes 1984, 1985), and has sufficient sensitivity to accurately measure what can be expected
in many lotic aquatic systems. However, this method may not be sufficiently sensitive for some lentic
aquatic systems where relatively lower selenium concentrations may need to be measured. If no selenium
is detected in a lentic system using this method, EPA recommends using a more sensitive analytical
method.
2.2 EPA Method200.8
EPA method 200.8 has a MDL of 7.9 (ig/L using the ICP-MS analytical technique. This method
has the advantage that no pre-treatment steps are necessary. However, this method may not be sufficiently
sensitive in many applications of the selenium criterion (Lamothe et al. 1999). If no selenium is detected
using this method, EPA recommends monitoring with a more sensitive method.
2.3 EPA Method200.9
Method 200.9 has a MDL of 0.6 |_ig/L using the STGF-AA analytical technique. This method has
the advantage that it can detect selenium at very low concentrations. However, graphite furnace
techniques require careful matrix matching.
Of these three EPA approved methods, Method 3114B using the HG-AAS technique is the most
cost-effective, with sufficient sensitivity and relatively low risk of interference in most cases. EPA
Method 200.8 may be used where appropriate, such as when selenium concentrations in effluent are
known to be higher than 7.9 (ig/L. EPA Method 200.9 may be used if a very low MDL is needed.
Some additional methods not approved by EPA that states and tribes might consider are:
• Collision/Reaction Cell Inductively Coupled Plasma Mass Spectroscopy (cICP-MS) (Garbarino
et al. 2005) - A relatively new technique that is a sensitive and selective detector for metal
analysis. However, isobaric interference can cause problems for quantitative determination as
well as identification based on the analyte pattern. Collision cells, reaction cells or other
interfaces reducing sample matrix effects that might otherwise interfere in the mass selective
determinative step are allowed in CWA analyses provided the method performance specifications
relevant to ICP-MS measurements are met
L-4
-------
• Fluorometric Analysis,- a wet chemistry technique using diaminonapthalene. This method also
achieves acceptable precision and accuracy on standard reference samples (Olson 1969; Olson et
al. 1975; American Public Health Association Standard Method 3500, on-line version).
Methods for measuring different species of selenium dissolved in water are also available. These
methods determine the species of dissolved selenium present in a sample through differential digestion
and hydride generation atomic adsorption spectrophotometry (Cutter 1978, 1983; Presser and Barnes,
1984; 1985; May et al. 2007). Selenite can be measured in samples with no pre-treatment. Selenate plus
selenite can be measured in samples subjected to boiling with hydrochloric acid. Subtraction of the
measured selenite fraction from the measured combined fraction would yield a measure of the selenate
fraction. If a sample is analyzed to measure total dissolved selenium as described above, then
measurements of the combined fraction can be subtracted to yield measurements of the dissolved organo-
selenium fraction.
3.0 Analytical Methods Available for Measuring Selenium
in Fish Tissue
EPA does not have approved methods under 40 CFR § 136 for measuring selenium in fish tissue.
However, states and tribes are not required to use EPA-approved methods for monitoring and assessment
of criteria attainment or other activities not related to permit applications or reports.
The techniques described above for analyzing selenium in water (HG-AAS, ICP-MS, and STGF-
AA) can be used to measure selenium in fish tissue if the samples are made soluble. Tissue samples are
homogenized and digested prior to analysis using strong acid or dry-ashing digestion as described below.
A review of sample digestion techniques has been published (Ihnat 1992). Standard reference materials,
analytical duplicates, and matrix spike samples are recommended to determine the applicability of a
selected digestion procedure.
3.1 Strong acid digestion
Solid samples can be subjected to strong acid digestion to break down mineral and organic
matrices. Samples are typically dried and homogenized before digestion. Determination of percent
moisture may be part of the drying procedure. Note that some strong acid digestion methods may not be
suitable for fish tissue. Strong acid digestion methods are categorized by the type of material or amount of
organic material present (e.g., solid waste; biological tissue, plants, soil, sediment, rock, coal) and degrees
of tissue solubilization needed (extraction, leachate, or complete destruction). Methods differ in acid
mixture and degree and type of heating (EPA Method 3050B, Revision 2, 1996; EPA Method 200.2,
L-5
-------
Revision 2.8, 1994; Briggs and Crock, 1986; Taggart, 2002, chapters I, J, and K). High boiling acids
(perchloric and sulfuric) may lead to a loss of selenium if solutions are heated to dryness.
3.2 Dry-ashing digestion
Dry-ashing digestion is applicable to biological samples (Brumbaugh and Walther, 1989; May et
al., 2007). Biological samples are normally lyophilized (freeze-dried) and homogenized before digestion.
Determination of percent moisture may be part of the drying procedure. Dried solid samples are:
1. Boiled in nitric acid for solubilization and oxidation
2. Ashed at 500° C with magnesium nitrate to complete oxidation and decompose remaining organic
material
3. Heated with hydrochloric acid to dissolve the ash and reduce selenium to the selenite (+4) state
required for detection by HG-AAS.
3.3 Analytical methods available for measuring selenium in particulate material
There are no 40 CFR § 136 methods for analyzing selenium in particulate material. However,
states and tribes are not required to use EPA-approved methods for monitoring and assessment of criteria
attainment or other activities not related to permit applications or reports.
The techniques described above for analyzing selenium in water (HG-AAS, ICP-MS, and STGF-
AA) can be used to measure selenium in particulate material after the sample has been separated from the
water and pre-treated using the same methods used for fish tissue. In order to obtain a particulate material
sample, a water column sample should be filtered to separate the particulate material and bed sediment.
Various techniques for collection of suspended particulate material using filtration are available from the
EPA (e.g. Method 1669) and the U.S. Geological Survey (Moulton et al. 2002; USGS, Britton and
Greeson 1987). These techniques include:
• EPA Method 1669 (1996) includes filtration through a 0.45 |_im capsule filter at the field site.
• USGS protocols for collection of phytoplankton and seston in rivers and streams as part of their
National Water Quality Assessment Program for watershed and habitat assessment
(http ://water .usgs .gov/nawqa/protocols .html).
• Textbooks such as Limnological Analyses address sampling of lakes using traditional techniques
including phytoplankton nets. (Wetzel and Likens 1991).
• Sampling of suspended material from estuaries where particulates are a substantial part of the
ecosystem is described in Doblin et al. (2005) as part of their work on the San Francisco Bay-
Delta Estuary.
• Separating suspended sediment using high-speed centrifugation and decantation when the
concentration of particulate material is relatively low (Horowitz et al. 1989).
L-6
-------
APPENDIX M: Abbreviations
M-l
-------
Reference and Site Abbreviations
Reference
Site
Species
Bi:
Birkner 1978
22
27
23
20
7
22
23
30
Miller's Lake, Wellington CO
Sweitzer Lake, Delta CO
Twin Buttes Reservoir, Laramie WY
East Allen Reservoir, Medicine Bow WY
Galett Lake, Laramie WY
Miller's Lake, Wellington CO
Twin Buttes Reservoir, Laramie WY
Larimer Highway 9 Pond, Fort Collins CO
FM
FM
FM
ID
ID
ID
ID
NPK
Fathead minnow
Fathead minnow
Fathead minnow
Iowa darter
Iowa darter
Iowa darter
Iowa darter
Northern plains
killfish
3
Meeboer Lake, Laramie WY
NPK
Northern plains
killfish
27
Sweitzer Lake, Delta CO
NPK
Northern plains
killfish
23
Twin Buttes Reservoir, Laramie WY
NPK
Northern plains
killfish
Bu91:
Butler etal. 1991
4
4
4
4
4
4
Uncompahgre River at Colona
Uncompahgre River at Colona
Uncompahgre River at Colona
Uncompahgre River at Colona
Uncompahgre River at Colona
Uncompahgre River at Colona
BhS
BnT
FS
MS
RT
WS
Bluehead sucker
Brown trout
Flannelmouth sucker
Mottled sculpin
Rainbow trout
White sucker
Bu93:
Butler etal. 1993
SP2
N2
SP2
N2
N2
N2
Spring Creek at La Boca
Navajo Reservoir, Piedra R. Arm, near La Boca
Spring Creek at La Boca
Navajo Reservoir, Piedra R. Arm, near La Boca
Navajo Reservoir, Piedra R. Arm, near La Boca
Navajo Reservoir, Piedra R. Arm, near La Boca
BhS
BT
BT
BB
ChC
cc
Bluehead sucker
Brown trout
Brown trout
Black bullhead
Channel catfish
Common carp
M-2
-------
Reference
Site
Species
SP2
Spring Creek at La Boca
FM
Fathead minnow
SP2
Spring Creek at La Boca
SD
Speckled dace
SP2
Spring Creek at La Boca
WS
White sucker
Bu95:
ME2
McElmo Cr., downstream from Alkali Canyon
BhS
Bluehead sucker
Butler etal. 1995
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
BhS
Bluehead sucker
NW
Navajo Wash near Towaoc
BhS
Bluehead sucker
SJ1
San Juan R. at Four Corners
BhS
Bluehead sucker
SJ3
San Juan R. at Mexican Hat Utah
BhS
Bluehead sucker
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
BB
Black bullhead
SJ1
San Juan R. at Four Corners
ChC
Channel catfish
SJ3
San Juan R. at Mexican Hat Utah
ChC
Channel catfish
ME4
McElmo Cr., downstream from Yellow Jacket Canyon
cc
Common carp
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
cc
Common carp
SJ1
San Juan R. at Four Corners
cc
Common carp
SJ3
San Juan R. at Mexican Hat Utah
cc
Common carp
HD2
Hartman Draw near mouth, at Cortez
FM
Fathead minnow
ME1
McElmo Cr. at Hwy. 160, near Cortez
FM
Fathead minnow
ME2
McElmo Cr., downstream from Alkali Canyon
FM
Fathead minnow
ME4
McElmo Cr., downstream from Yellow Jacket Canyon
FM
Fathead minnow
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
FM
Fathead minnow
WC
Woods Canyon near Yellow Jacket
FM
Fathead minnow
SJ1
San Juan R. at Four Corners
FS
Flannelmouth sucker
HD2
Hartman Draw near mouth, at Cortez
FS
Flannelmouth sucker
ME2
McElmo Cr., downstream from Alkali Canyon
FS
Flannelmouth sucker
ME4
McElmo Cr., downstream from Yellow Jacket Canyon
FS
Flannelmouth sucker
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
FS
Flannelmouth sucker
SJ3
San Juan R. at Mexican Hat Utah
FS
Flannelmouth sucker
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
GnS
Green sunfish
ME4
McElmo Cr., downstream from Yellow Jacket Canyon
RSh
Red shiner
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
RSh
Red shiner
M-3
-------
Reference
Site
Species
SJ1
San Juan R. at Four Corners
RSh
Red shiner
ME1
McElmo Cr. at Hwy. 160, near Cortez
SD
Speckled dace
ME2
McElmo Cr., downstream from Alkali Canyon
SD
Speckled dace
ME3
McElmo Cr., upstream from Yellow Jacket Canyon
SD
Speckled dace
NW
Navajo Wash near Towaoc
SD
Speckled dace
SJ1
San Juan R. at Four Corners
SD
Speckled dace
HD2
Hartman Draw near mouth, at Cortez
Su
Sucker
Bu97:
MUD2
Mud Cr. at Hwy. 32, near Cortez
BhS
Bluehead sucker
Butler etal. 1997
MNP2
Large pond south of G Road, southern Mancos Valley
FM
Fathead minnow
MUD2
Mud Cr. at Hwy. 32, near Cortez
FM
Fathead minnow
WCP
Pond on Woods Canyon at 15 Road
FM
Fathead minnow
CHI
Cahone Canyon at Hwy. 666
GnS
Green sunfish
MUD2
Mud Cr. at Hwy. 32, near Cortez
GnS
Green sunfish
MNP3
Pond downstream from site MNP2, southern Mancos Valley
SB
Smallmouth bass
Ca:
DC
Deerlick Creek
RT
Rainbow trout
Casey 2005
LC
Luscar Creek
RT
Rainbow trout
Fo:
CC-1A
Crow Creek - 1A
BnT
Brown trout
Formation 2012
CC-3A
Crow Creek - 3 A
BnT
Brown trout
CC-150
Crow Creek - 150
BnT
Brown trout
CC-350
Crow Creek - 350
BnT
Brown trout
CC-75
Crow Creek - 75
BnT
Brown trout
DC
Deer Creek
BnT
Brown trout
HS
Hoopes Spring
BnT
Brown trout
HS-3
Hoopes Spring - 3
BnT
Brown trout
LSV-2C
Sage Creek - 2C
BnT
Brown trout
LSV-4
Sage Creek - 4
BnT
Brown trout
SFTC
South Fork Tincup Creek
BnT
Brown trout
M-4
-------
Reference
Site
Species
CC-1A
Crow Creek - 1A
Sc
Sculpin
CC-3A
Crow Creek - 3 A
Sc
Sculpin
CC-150
Crow Creek - 150
Sc
Sculpin
CC-350
Crow Creek - 350
Sc
Sculpin
CC-75
Crow Creek - 75
Sc
Sculpin
DC
Deer Creek
Sc
Sculpin
HS
Hoopes Spring
Sc
Sculpin
HS-3
Hoopes Spring - 3
Sc
Sculpin
LSV-2C
Sage Creek - 2C
Sc
Sculpin
LSV-4
Sage Creek - 4
Sc
Sculpin
SFTC
South Fork Tincup Creek
Sc
Sculpin
Gr:
17
Arapahoe Wetlands Pond
FM
Fathead minnow
Grasso et al. 1995
17
Arapahoe Wetlands Pond
WS
White sucker
HB:
LEMC
Lower East Mill Creek
CT
Cutthroat trout
Hamilton and
Buhl 2004
Le:
BA
Badin Lake
BB
Black bullhead
Lemly 1985
BE
Belews Lake
BB
Black bullhead
HR
High Rock Lake
BB
Black bullhead
BA
Badin Lake
CC
Common carp
BE
Belews Lake
CC
Common carp
HR
High Rock Lake
CC
Common carp
BA
Badin Lake
FM
Fathead minnow
BE
Belews Lake
FM
Fathead minnow
HR
High Rock Lake
FM
Fathead minnow
BA
Badin Lake
GnS
Green sunfish
BE
Belews Lake
GnS
Green sunfish
HR
High Rock Lake
GnS
Green sunfish
M-5
-------
Reference
Sa87:
Saiki and
Lowe 1987
Sa93:
Saiki et al. 1993
St:
Stephens et al.
1988
Site
~BA
BE
HR
BA
BE
HR
KP11
KP2
KP8
SLD
VP26
VW
GT4
GT5
SJR2
SJR3
GT4
GT5
SJR2
SJR3
GT4
GT5
SJR2
SJR3
M4720
M4720
Badin Lake
Belews Lake
High Rock Lake
Badin Lake
Belews Lake
High Rock Lake
Kesterson Pond 11
Kesterson Pond 2
Kesterson Pond 8
San Luis Drain
Volta Pond 26
Volta Wasteway
Salt Slough at San Luis Wildlife Refuge
Mud Slough at San Luis Wildlife Refuge
San Joaquin R. above Hills Ferry Rd.
San Joaquin R. at Durham Ferry Recreation Area
Salt Slough at San Luis Wildlife Refuge
Mud Slough at San Luis Wildlife Refuge
San Joaquin R. above Hills Ferry Rd.
San Joaquin R. at Durham Ferry Recreation Area
Salt Slough at San Luis Wildlife Refuge
Mud Slough at San Luis Wildlife Refuge
San Joaquin R. above Hills Ferry Rd.
San Joaquin R. at Durham Ferry Recreation Area
Marsh 4720
Marsh 4720
Species
WM
Western mosquitofish
WM
Western mosquitofish
WM
Western mosquitofish
RSh
Red shiner
RSh
Red shiner
RSh
Red shiner
WM
Western mosquitofish
WM
Western mosquitofish
WM
Western mosquitofish
WM
Western mosquitofish
WM
Western mosquitofish
WM
Western mosquitofish
Bg
Bluegill
Bg
Bluegill
Bg
Bluegill
Bg
Bluegill
LMB
Largemouth bass
LMB
Largemouth bass
LMB
Largemouth bass
LMB
Largemouth bass
WM
Western mosquitofish
WM
Western mosquitofish
WM
Western mosquitofish
WM
Western mosquitofish
BB
Black bullhead
CC
Common carp
M-6
-------
APPENDIX N: COMPARISON OF APPROACHES
for Calculating Selenium Tissue
Conversion Factors
N-l
-------
1.0 Comparison of the Median Ratio and Regression
Approaches
Regression analysis and the application of median ratios are two approaches that can be used to
quantify the relationship between two variables, such as the concentration of selenium within two tissue
types. When concentrations in the two tissues are plotted, each point represents the ratio of one tissue type
to another. A regression analysis calculates the line that best fits those tissue concentrations, which is
characterized by both a slope and a y-intercept. In contrast, the median ratio is a single value representing
the 50th centile of all ratios. Conversion factors (CFs) are presently calculated as the median ratio of two
tissue types. The use of median ratios grew out of the goal of patterning the translation procedure after the
Luoma and Presser selenium bioaccumulation model, where field derived factors representing the transfer
of selenium from one ecosystem compartment to another were represented as single values calculated
using constrained (y-intercept passes through the origin) regression. Median ratios were implemented to
produce a single value that was operationally similar to a constrained regression slope, but that was free
from the issues associated with constrained regression, particularly cases where the y-intercept was
notably different from zero, which would result in slopes that were highly divergent from slopes derived
using conventional regression. Both median ratios and conventional regression (with or without log
transformation) are far superior to constrained (no y-intercept) regression. The following discussion will
compare median ratios and conventional linear regression.
A median is a measure of central tendency that is free from all parametric assumptions associated
with linear regression. As the 50th centile of all y/x ratios, it is independent of the effects of outliers or the
overall distribution of ratios. As implemented in the criterion document, median ratios were assumed to
be representative of the linear relationship between the concentration in tissue y to the concentration in
tissue x. This assumption was tested with a pre-screening procedure using conventional linear regression.
If the regression model had a positive slope and was statistically significant at P<0.05, then the
relationship was assumed to be positive and linear, and a median ratio was used as representative of that
linear relationship.
A log-log regression includes both a slope and a y-intercept. Because they apply to log space,
these parameters mean something different than similar parameters in arithmetic space. Linear
relationships in log space translate back to power functions in arithmetic space. That is, the log space
straight line function:
N-2
-------
log(EO) = m • log(WB) + b
(1)
translates to:
EO = a WB m (2)
where the coefficient a=10b. The log-log plot intercept b represents the value of log EO when
WB=1 mg/kg (that is when log(WB)=0).
The key point when comparing log-log regression to the median ratio approach is that when log-
log slope m=l, then Equation 2 reduces to a simple direct proportion EO = a WB in arithmetic space.
Figure N-l illustrates the behavior of CF (that is, the ratio EO/WB), depending on whether the log-log
slope m of the plot of log(EO) versus log(WB) has a value 1, >1, or <1.
N-3
-------
1
0
m=l
0 0.5 1 1.5
log WB
0.35 -i
0.3 ~ ~ ~ ~
0.25 -
S 0.2 -
O 0.15 -
0.1 -
0.05 -
0 J , ,—
0 0.5 1
log WB
1.5
0.35 i
0.3 -
0.25 -
U 0.2 -
J? 0.15 -
0.1 -
0.05 -
0 -
0
1
log EO
2 T
1.5
1
0.5
0
m>l
0.7
0.6
0.5 -
LL
U 0.4
Un:1
O 0.3
0.2
0.1 -
0
0.7
0.6
0.5
LL
U 0.4
O 0.3
0.2
0.1
0
0 0.5 1 1.5
log WB
0 0.5 1
log WB
1.5
1
log EO
bo
o
1.5 +
1
0.5
0
m
-------
When the log-log slope m~ 1. CF does not change with concentration. In that case, CF is the
simple proportionality constant as assumed in all previous versions of the criterion document. When m is
noticeably different from 1, CF changes with concentration, and we would solve for its value at the EO
criterion concentration. If the EO criterion concentration is not near the median EO value in the graphed
data, then the regression-calculated CF value may differ somewhat from the median CF.
While both a median ratio and a linear regression account for all of the plotted values within a
particular relationship, the regression model is derived from the specific locations of every data point,
whereas the median is derived independent of the specific distribution of the data points. In this way, a
regression contains more information about the entire data distribution, and as such, is more affected by
deviations from linearity. This second point can be an advantage or a disadvantage, depending on the data
distribution. For some CF relationships in the database, there is evidence of slight non-proportionality, in
which the y/x ratios at higher concentrations are different than the y/x ratios at lower concentrations. In
these instances, a log transformation of the tissue concentrations will serve to better linearize the overall
relationship, so that the resulting regression model will better capture the y/x relationship across the full
concentration range. The median ratio of these models will be the same regardless of whether or not the
data are transformed. However, because the use of median ratios is based on the assumption of
proportionality, CFs calculated using regression of log transformed values will provide slightly more
accurate representations of the relationship across the full concentration range than a median ratio, for
those datasets that show some evidence of non-proportionality. An exception would be a case where the
midpoint of the data distribution, where the median ratio is more likely to be located, is similar to the
criterion concentration. In these instances the median ratio would be expected to be similar the regression
based CF regardless of slope. Finally, for those datasets that do not show this effect, selection of either the
median ratio or the regression based CF approach are both equally valid approaches.
Another source of uncertainty can occur for species with a CF derived from a narrow
concentration range that does not encompass the criterion concentration. In these instances, the slope of
the regression model may not be representative of the slope had there been concentrations bracketing the
criterion. Similarly, the median of the concentration ratios within this small range may not be
representative of the median ratio if there had been concentrations bracketing the criterion. However, it
may be preferable, or "safer", to use a non-parametric median rather than the result of an extrapolated
regression equation, particularly when the regression is based on few data points (no matter how good r2
is).
To conclude, CFs calculated from median ratios have the advantages of simplicity, being easier to
explain and implement, and they are "safer" in the sense that they are not affected by outliers or the
distribution of variance across the data range. CFs calculated from log regression include more
N-5
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information about the entire data distribution, but can be sensitive to outliers. CFs calculated from the two
approaches can diverge in cases where the data range does not encompass the criterion concentration,
particularly in cases those where the log transformed slope is also much greater or less than one. Overall,
the median ratio and log regression approaches generate similar CFs for this dataset, and have little effect
on the translated water criterion elements.
In general, as indicated by the idealized data in Exhibit A, the median and the TLS regression-
predicted CF will be similar under either of the following conditions: (a) log-log EO/WB slope near 1.0,
or (b) criterion near the middle of the observed data range of tissue concentrations for the species. They
are likely to differ from each other when both of the following conditions simultaneously occur: (c) log-
log slope distant from 1.0, and (d) criterion distant from the center of the data range.
2.0 Comparison of the Ordinary Least Squares and Total
Least Squares Regression Approaches
The calculation of conversion factors using linear regression following log transformation
addresses the issues associated with non-proportional relationships between Se in different tissues, and is
the approach recommended by several public commenters. Conventional ordinary least squares (OLS)
regression results can vary depending on which tissue type is assigned to the x and y axis, respectively.
This is because OLS regression assumes that the variable on the y axis is dependent on the variable on the
x axis, and the resulting regression is the line that minimizes the sum of the squared distances between
observed y-values and predicted y-values. OLS regression assumes that the values on the x-axis have no
uncertainty. For datasets such as the paired tissue concentrations used to calculate CF, there is no
dependency between the selenium concentrations in one tissue type to another tissue type, and
concentrations in both tissue types are equally uncertain. Because of this, we could assign either tissue
type to either axis, and the resulting CF would be slightly different. By convention, we assign egg-ovary
to the y-axis when comparing it to whole-body or muscle, and we assign muscle to the y-axis when
comparing it to whole-body, because these are the ratios used in the translation equations. While CFs
using median ratios are not affected by axis assignment, CFs using OLS are, for reasons described above.
An alternative regression approach that corrects this issue is total least squares (TLS) regression.
TLS regression is preferable to OLS regression in cases where there is error associated with each of the
variables, and there is no dependency of one variable on the other. With TLS, the regression is the line
that minimizes the sum of the squared distances between observed predicted x- and y-values, and
produced the same result regardless of which variable is assigned to which axis. Curves drawn by eye
tend to mimic TLS, not OLS. Without thinking about it, the person drawing the line naturally attempts to
N-6
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minimize both vertical and horizontal errors. However, a significant disadvantage of TLS regression is
that Excel has no built-in function to perform it, and many readers will be unfamiliar with it.
Table N-l shows the effect of the different calculation procedures (median ratio, log OLS
regression - xyOLS, log OLS regression with reversed axes - yxOLS, and log TLS regression) on all
directly measured CFs. Median ratio CFs tend to diverge from regression based CFs for datasets where
log-log slopes are markedly different than 1 and the criterion is not near the center of the observed
concentrations. CFs calculated from TLS regression nearly always fall between CFs calculated from OLS
regression with and without the axes reversed, and are not affected by axis order.
N-7
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Direetlv calculated convt
.rsion factors tor each tissue ratio,
hv method
Species
IO/WB
Ratio xvOLS v\OI,S
TLS
M/WB
Ratio
xvOLS
YX()I,S
TLS
i:o/\i
Ratio xvOLS vxOLS TLS
bluegill
2.13
1.90
2.04
1.98
1.32
1.36
1.37
1.36
1.38
1.11
1.24
1.18
bluehead sucker
1.82
1.41
1.50
1.45
1.23
1.70
1.67
1.59
1.48
0.82
0.91
0.85
brook trout
1.09
0.96
0.99
brown trout
1.45
1.53
1.77
1.74
common carp
1.92
1.62
1.63
1.62
1.61
1.36
1.41
1.45
1.14
1.06
1.18
1.14
creek chub
1.99
2.05
2.01
2.03
cutthroat trout
1.96
1.37
1.67
1.48
1.81
1.97
1.83
1.89
desert pupfish
1.20
1.14
1.14
1.14
dolly varden
1.26
1.64
1.52
1.59
fathead minnow
1.40
1.71
1.56
1.64
flannelmouth sucker
1.41
1.14
1.84
1.49
1.46
1.94
1.89
1.85
1.08
0.51
1.06
0.69
green sunfish
1.45
1.35
1.45
1.40
1.23
1.28
1.32
1.24
1.21
1.08
1.17
1.12
mountain whitefch
5.80
10.47
4.98
7.35
northern pike
1.88
1.65
1.78
1.70
rainbow trout
1.92
1.82
1.88
1.82
razorback sucker
2.31
1.93
1.89
1.90
roundtail chub
2.07
2.22
2.26
2.24
1.05
1.08
1.10
1.05
2.04
1.99
2.10
2.06
smallmouth bass
1.42
1.31
1.68
1.52
1.23
1.88
1.97
1.68
1.19
0.67
0.88
0.72
white sturgeon
1.33
0.97
1.07
1.01
white sucker
1.38
1.02
1.25
1.12
1.34
1.43
1.54
1.45
1.00
0.59
0.84
0.67
Table N-l. Comparison of all directly calculated conversion factors by method.
Methods include median ratio (Ratio), log ordinary least squares (xyOLS), log ordinary least squares with axes reversed (yxOLS), and log total
least squares (logTLS). Regression based CFs were calculated at the egg ovary criterion concentration of 15.1 mg/kg. Muscle to whole body
(M/WB) CFs were calculated at the muscle concentration at the egg-ovary criterion.
N-8
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The following examples illustrate the differences between OLS and TLS regressions, and the effect of
axis assignment on CF.
2.1 Example 1 - Flannelmouth Sucker (Egg-ovary/Whole-body)
CF by approach: (1.41 -median ratio, 1.13 - log OLS, 1.86 - log OLS with reversed axes, 1.48 - log
TLS)
Model comparison la - Regression model results and calculation of CF (Egg-ovary v-axis; Whole-body
x-axis):
OLS: log (Egg-ovary) = (0.7966 x (log Whole-body)) + 0.2857
log (Whole-Body) = (log (16 mg/kg) - 0.2857)/0.7966 = 1.153
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) =1.13
TLS: log (Egg-ovary) = (0.9877 x (log Whole-body)) + 0.1843
log (Whole-Body) = (log (16 mg/kg) - 0.1843)/0.9877 = 1.033
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) = 1.48
In Figure N-2, the fitted regression lines do not appear particularly divergent; however, these
points cover a relatively narrow (and low), concentration range. At the criterion concentration (log E/O =
1.204), the predictions lines are more divergent, resulting in the differences between the CFs. Also, note
that the TLS slope is close to 1. The resulting TLS-derived CF is similar to the median ratio CF (1.48 vs
1.41). In contrast, the OLS slope is lower than 1, resulting in a CF for the OLS model that is notably
different than the median ratio CF (1.13 vs 1.41).
N-9
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1.0
£
cc
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0
1
O)
O) _ _
J. 0.5
D)
o
— ^--OLS
•US
0.0
0.0
0.5
|0Q (^whole-body)
1.0
Figure N-2. OLS vs. TLS regression model fits for flannelmouth sucker.
Egg-ovary concentrations are on the y-axis and whole-body concentrations are on the x-axis.
Model comparison lb - Regression model results and calculation of CF (Egg-ovary x-axis; Whole-body
v-axis):
OLS: log(Whole-body) = (0.8126 x (log Egg-ovary)) - 0.0450 = 0.9335
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) = 1.86
TLS: log( Whole-body) = (1.012 x (log Egg-ovary)) - 0.1866 =1.033
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) = 1.48
At first glance, Figure N-3 appears very similar to Figure N-2. However, note that the axes are
reversed, and because we are now solving for y (whole body concentration at egg-ovary criterion
concentration), the shallower slope of the reverse OLS figure results a whole body concentration at the
egg-ovary criterion lower than in the upper figures, which in turn results in a larger CF. Also, note that the
TLS model is a mirror image of the model in Figure N-3, and as such has the same calculated CF. As
above, the TLS slope is close to 1, with a TLS-derived CF that is similar to the median ratio CF (1.48 vs
1.41). In contrast, the OLS slope is lower than 1, resulting in an OLS-derived CF that is notably different
than the median ratio CF (1.86 vs 1.41).
N-10
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egg-ovary
Figure N-3. OLS vs. TLS regression model fits for flannelmouth sucker.
Egg-ovary concentrations are on the x-axis and whole-body concentrations are on the y-axis.
N-ll
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2.2 Example 2 -Bluegill (Egg-ovary/Whole-body)
CF by approach: (2.13 -median ratio, 1.90 - log OLS, 2.07 - log OLS with reversed axes, 2.01 - log
TLS)
Model comparison 2a - Regression model results and calculation of CF (Egg-ovary v-axis; Whole-body
x-axis):
OLS: log(Egg-ovary) = (1.061 x (log Whole-body)) + 0.2227
log (Whole-Body) = (log (16 mg/kg) - 0.2227)/1.061 = 0.9250
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) = 1.90
TLS: log(Egg-ovary) = (1.240 x (log Whole-body)) + 0.0.0861
log (Whole-Body) = (log (16 mg/kg) - 0.0861)/1.240 = 0.9018
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) = 2.01
Compared to the OLS regression line, the slope of the TLS regression line is slightly steeper,
resulting in a slightly larger calculated CF (Figure N-4). Even though the slopes are larger than 1, the data
range encompasses the criterion concentration, which is close to the middle of the data distribution. As a
result, the regression based CFs are similar overall to the median ratio CF.
Data
- OLS
TLS
1
-0.5
0.5
2.0
-0.5
log (Cwh0|e body)
Figure N-4. OLS vs. TLS regression model fits for bluegill. Egg-ovary concentrations are on the y-axis
and whole-body concentrations are on the x-axis.
N-12
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Model comparison 2b - Regression model results and calculation of CF (Egg-ovary x-axis; Whole-body
v-axis):
OLS: log(Whole-body) = (0.7269 x (log Egg-ovary)) + 0.0129 = 0.8883
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) = 2.07
TLS: log(Whole-body) = (0.8066 x (log Egg-ovary)) - 0.0695 =0.9018
CF at egg-ovary criterion = 10A((log Egg-ovary) - (log Whole-body)) = 2.01
Compared to the OLS regression line, the slope of the TLS regression line is slightly steeper,
resulting in a slightly smaller calculated CF (Figure N-5). Even though the slopes are less than 1, the data
range encompasses the criterion concentration, which is also close to the middle of the data distribution.
As a result, the regression based CFs are similar overall to the median ratio CF.
egg-ovary,
Figure N-5. OLS vs. TLS regression model fits for bluegill.
Egg-ovary concentrations are on the x-axis and whole-body concentrations are on the y-axis.
The effect of the CFs calculated by the different approaches has a minor effect on the final
translated water criterion elements. Compared to the median ratio method, translated water criterion
element concentrations are slightly higher using CFs calculated from the log OLS regression methods,
CFs calculated from the reverse axis log OLS are slightly lower. Lentic translated water criterion element
N-13
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concentrations are the same using CFs from median ratios and log TLS regression methods, while lotic
concentrations calculated from log TLS CFs are slightly lower compared to those calculated using median
ratio CFs (Table N-2).
Table N-2. Translated water concentration criterion element criterion concentrations by CF
calculation method.
Method
Lentic (ng/L)
Lotic (jig/L)
Median Ratio
1.5
3.1
log OLS regression
1.6
3.3
inverse log OLS regression
1.4
2.9
log TLS regression
1.5
2.9
3.0 Comparison of Median-and Regression-based Conversion
Factors to Calculate Chronic Values for Muscle and
Whole Body Tissues
Besides being used in the translation of the egg-ovary (EO) tissue criterion to water, conversion
factors (CF) were also used to convert egg-ovary (EO) chronic values (CV) to muscle or whole body
tissue concentrations. These conversions were done when the data from a reproductive toxicity study did
not have muscle or whole body selenium concentrations or if the latter tissue data was not usable to
determine a chronic value. Directly calculated CVs using either muscle or whole body selenium
measurements from a study was preferred over converted CVs in the determination of the final chronic
value (= criterion).
Table N-3 provides a comparison of median-based and regression-based CFs when they are used
to convert an EO selenium concentration to muscle or whole body. Regression-based CFs used total least
squares (TLS) regression for the reasons stated above. The table lists each taxon in the reproductive
toxicity data set and presents CVs that are either directly calculated or converted from the EO CV using
either the median or TLS CF. Generally, the median-based and TLS-based CFs were similar for both
tissue types and this similarity resulted in similar criteria (bottom row). The muscle criterion for the data
set that contained directly calculated CVs and converted CVs was similar whether median or TLS CFs
were used, 11.3 and 10.6, respectively. The whole body criterion was also similar using these two
approaches, 8.5 and 9.6, respectively. The median-based CFs were selected based on reasons stated in the
previous section.
N-14
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Table N-3. Comparison of muscle and whole body chronic values when calculated directly and converted from egg-ovary concentrations
using median- and TLS regression-based conversion factors.
Taxon
EO
cv
Muscle chronic values (CV) and conversion factors (CF)
Whole body chronic values (CV) and conversion factors (CF)
Direct +
Median
Direct
+ TLS
Median
CF
Median
CV
TLS
CF
TLS
CV
Direct +
Median
Direct +
TLS
Median
CF
Median
CV
TLS
CF
TLS
CV
Salvelinus
56.22
44.48
35.36
1.26
44.48
1.59
35.36
34.92
24.34
1.61
34.92
2.31
24.34
Esox
34
21.70d
21.70d
1.88
18.13
1.70
20.00
14.23
13.77
2.39
14.23
2.47
13.77
Cyprinodon
27
28.72
34.18
0.94
28.72
0.79
34.18
22.50
23.68
1.20
22.50
1.14
23.68
0. mykiss
24.5
12.79
13.46
1.92
12.79
1.82
13.46
10.04
9.28
2.44
10.04
2.64
9.28
0. clarkii,
Rudolph
24.7
16.6d
16.6d
1.81
13.65
1.89
13.07
12.60
16.69
1.96
12.60
1.48
16.69
0. clarkii,
Nautilus
27.7
15.30
14.66
1.81
15.30
1.89
14.66
14.13
18.72
1.96
14.13
1.48
18.72
Oncorhynchus
25.31
14.28
14.49
NA
13.59
NA
13.65
11.58
12.81
NA
11.58
NA
12.81
Micropterus
26.3
22.16
36.53
1.19
22.16
0.72
36.53
18.52
17.30
1.42
18.52
1.52
17.30
L. macrochirus,
Coyle
26.3
19.13
22.29
1.38
NA
1.18
NA
8.6d
8.6d
NA
NA
NA
NA
L. macrochirus,
Doroshov
22.6
15.7d
15.7d
NA
NA
NA
NA
10.61
11.41
2.13
NA
1.98
11.41
L. macrochirus,
Hermanutz
14.7
13.4d
13.4d
NA
NA
NA
NA
10.6d
10.6d
NA
NA
NA
NA
Lepomis
20.60
15.91
16.74
1.38
14.98
1.18
17.45
9.890
10.13
2.13
9.656
1.98
10.40
Salmo
21
18.50
17.50
1.14
18.50
1.20
17.50
13.2d
13.2d
1.45
14.48
1.74
12.07
Acipenser
15.6
11.9d
11.9d
1.33
11.73
1.01
15.45
9.209
10.68
1.69
9.209
1.46
10.68
Criterion
15.10
11.34
11.57
NA
10.99
NA
13.35
8.538
9.567
NA
8.189
NA
9.879
directly calculated from muscle or whole body selenium concentrations
N-15
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