WHITE PAPER 

AQUATIC LIFE CRITERIA FOR CONTAMINANTS OF 

EMERGING CONCERN 

PART I 

GENERAL CHALLENGES AND RECOMMENDATIONS 

Prepared by the 

OW/ORD Emerging Contaminants Workgroup 

June 03, 2008 

NOTICE 

THIS DOCUMENT IS AN INTERNAL PLANNING DOCUMENT 

It has been prepared for the purpose of Research & Development Planning. 

It has not been formally released by the U.S. Environmental Protection Agency and should 

not at this stage be construed to represent Agency guidance or policy. 

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EPA WORKGROUP 

U.S. EPA, NHEERL, Mid-Continent Ecology Division, Duluth, MN 

Gerald T. Ankley* 

Richard Bennett 

Russell J. Erickson* 

Dale J. Hoff, Workgroup Co-chair* 

David R. Mount* 

Joseph Tietge 

U.S. EPA, NHEERL, Gulf Ecology Division, Gulf Breeze, FL 

Geraldine Cripe 

U.S. EPA, NERL, Ecological Exposure Research Division, Cincinnati, OH 

Mitchell Kostich 

David Lattier 

James Lazorchak* 

U.S. EPA, Office of Water, Washington, DC 

Janita Aguirre 

Joseph Beaman, Workgroup Co-chair* 

Diana Eignor 

Lisa Huff 

U.S. EPA, Office of Pesticide Programs, Washington, DC 

Les Touart 

Jean Holmes 

Technical Support – Great Lakes Environmental Center, Columbus, OH 

Tyler K. Linton* 

Gregory J. Smith 

*Coauthor 

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TABLE OF CONTENTS 

1.0 INTRODUCTION ...............................................................................................................1 

1.1 What is a Contaminant of Emerging Concern? ................................................................1 

1.2 Why is EPA Concerned with CECs?................................................................................2 

1.3 Purpose and Organization of This White Paper................................................................3 

2.0 CURRENT ALC METHODOLOGY..................................................................................5 

2.1 Standard ALC Derivation Procedures ..............................................................................5 

2.2 Alternatives for ALC Derivation ......................................................................................6 

2.3 Precedent for Deviating from Basic ALC Derivation Procedures....................................9 

3.0 CHARACTERISTICS OF CECs AND THEIR INFLUENCE ON ALC 

DEVELOPMENT..............................................................................................................10 

3.1 Characteristics of HPG-Active EDCs.............................................................................10 

3.2 Implications for ALC Development ...............................................................................12 

3.2.1 The Need For and Relevance of Acute Toxicity Data and a CMC ................... 13 

3.2.2 Defining Minimum Data Requirements in Terms of Taxonomic Coverage ..... 14 

3.2.3 Defining Appropriate Chronic Toxicity Data.................................................... 16 

3.2.4 Selecting Effect Endpoints Upon Which to Base ALC ..................................... 18 

3.2.4.1 Specific Examples of Measurable Changes at Different Levels of Biological 

Organization....................................................................................................... 20 

3.3 Pathways and Receptors Beyond the HPG-Axis ............................................................25 

4.0 SUMMARY AND RECOMMENDATIONS....................................................................27 

4.1 Relevance of Acute Toxicity Effect Levels in Setting ALC for CECs...........................27 

4.2 Defining Minimum Data Requirements in Terms of Taxonomic Coverage ..................28 

4.3 Use of Non-Resident Species in ALC Development......................................................29 

4.4 Defining Appropriate Chronic Toxicity Data.................................................................29 

4.5 Selection of Effect(s) Endpoints Upon Which to Base ALC..........................................30 

4.6 Involvement of an Expert Panel......................................................................................31 

5.0 REFERENCES ..................................................................................................................32 

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List of Acronyms:

ACR Acute to Chronic Ratio 

ALC Aquatic Life Criteria 

Ah Aryl Hydrocarbon (receptor) 

AV Acute (toxicity) value 

AWQC Ambient Water Quality Criteria 

CCC Criterion Continuous Concentration 

CEC Contaminants of Emerging Concern 

CMC Criterion Maximum Concentration 

CV Chronic (toxicity) value 

CWA Clean Water Act 

CYP Cytochrome enzymes (P450) 

EDC Endocrine Disrupting Chemicals 

E2 Estradiol (natural estrogen) 

EE2 Ethynylestradiol (synthetic pharmaceutical estrogen) 

ELS Early Life-Stage (toxicity test) 

EPA Environmental Protection Agency 

FAV Final Acute Value 

FACR Final Acute to Chronic Ratio 

GMAV Genus Mean Acute Value 

GMCV Genus Mean Chronic Value 

HPG Hypothalamic-Pituitary-Gonadal (axis) 

HPT Hypothalamic-Pituitary-Thyroid (axis) 

LOEC Lowest Observed Effect Concentration 

MDR Minimum Data Requirement 

MOA Mode of Action 

NOEC No Observed Effect Concentration 

OECD Organization for Economic Development and Cooperation 

OWC Organic Wastewater Contaminant 

PBDE Polybrominated Diphenyl Ether 

PPCP Pharmaceutical and Personal Care Product 

POP Persistent Organic Pollutant 

SMAV Species Mean Acute Value 

TBT Tributyltin 

USGS United States Geological Survey 

VTG Vitellogenin protein 

vtg Vitellogenin gene transcript 

WWTP Wastewater Treatment Plant 

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1.0 INTRODUCTION 

Under the United States Clean Water Act (CWA) (33 U.S.C. Sections 1251-1387), EPA is 

required to take a number of actions to protect and restore the ecological integrity of the Nation’s 

water bodies. Under Section 304(a) of the CWA, EPA must develop and publish ambient water 

quality criteria. Ambient water quality criteria (AWQC) are levels of individual pollutants, water 

quality characteristics, or descriptions of conditions of a water body that, if met, should protect 

the designated use(s) of the water. Examples of designated uses of a water body include 

swimming, drinking water, fishing, fish spawning, and navigation. States and authorized tribes 

establish designated uses for their water bodies. AWQC are recommended guidance that states 

and tribes may use as part of their water quality standards to protect water bodies for their 

designated use from chemical pollutants. 

AWQC for aquatic life (aquatic life criteria, ALC) developed under Section 304(a) reflect the 

“latest scientific knowledge” concerning “all identifiable effects” of the pollutant in question. 

These criteria are based solely on data and scientific determinations on the relationship between 

environmental concentrations of the pollutant and its effects. Criteria do not consider social and 

economic impacts, or the technological feasibility of meeting the chemical concentration values 

in ambient water. Since the early 1980's, EPA has been developing ALC to protect aquatic 

organisms from chemical specific pollutants under Section 304(a) of the CWA. In 1985, EPA 

published 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 has provided uniformity and transparency in the derivation methodology 

of ALC for a large number of compounds among several classes of chemicals. The majority of 

EPA’s currently recommended ALC have been derived using the methods outlined in the 

Guidelines. 

While the Guidelines remain the primary instrument the Agency uses to meet its broad objectives 

for the development of ALC, there have been many advances in aquatic sciences, aquatic and 

wildlife toxicology, population modeling, and ecological risk assessment that are relevant to 

deriving ALC. Some of the advances have been addressed through supplemental guidance on the 

derivation or site-specific modification of criteria (Prothro 1993; U.S. EPA 1994a), while others 

have been incorporated directly into derivation of individual ALC for certain chemicals (e.g., 

saltwater chronic aquatic life criterion for tributyltin, U.S. EPA 2003). Recently, considerable 

attention has been generated by a widely ranging group of chemicals termed, in this document, 

contaminants of emerging concern (CECs). As is discussed in the body of this document, some 

of these CECs present challenges for the application of the Guidelines to ALC development. 

1.1 What is a Contaminant of Emerging Concern? 

The term “contaminant of emerging concern” is being used within the Office of Water to replace 

“emerging contaminant,” a term that has been used loosely since the mid-1990s by EPA and 

others to identify chemicals and other substances that have no regulatory standard, have been 

recently “discovered” in natural streams (often because of improved analytical chemistry 

detection levels), and potentially cause deleterious effects in aquatic life at environmentally 

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relevant concentrations. They are pollutants not currently included in routine monitoring 

programs and may be candidates for future regulation depending on their (eco)toxicity, potential 

health effects, public perception, and frequency of occurrence in environmental media. CECs are 

not necessarily new chemicals. They include pollutants that have often been present in the 

environment, but whose presence and significance are only now being evaluated. 

CECs include several types of chemicals: 

• Persistent organic pollutants (POPs) such as polybrominated diphenyl ethers (PBDEs; 

used in flame retardants, furniture foam, plastics, etc.) and other global organic 

contaminants such as perfluorinated organic acids; 

• Pharmaceuticals and personal care products (PPCPs), including a wide suite of human 

prescribed drugs (e.g., antidepressants, blood pressure), over-the-counter medications 

(e.g., ibuprofen), bactericides (e.g., triclosan), sunscreens, synthetic musks; 

• Veterinary medicines such as antimicrobials, antibiotics, anti-fungals, growth promoters 

and hormones; 

• Endocrine-disrupting chemicals (EDCs), including synthetic estrogens (e.g.,17αethynylestradiol, which also is a PCPP) and androgens (e.g., trenbolone, a veterinary 

drug), naturally occurring estrogens (e.g.,17ß-estradiol, testosterone), as well as many 

others (e.g., organochlorine pesticides, alkylphenols) capable of modulating normal 

hormonal functions and steroidal synthesis in aquatic organisms; 

• Nanomaterials such as carbon nanotubes or nano-scale particulate titanium dioxide, of 

which little is known about either their environmental fate or effects. 

1.2 Why is EPA Concerned with CECs? 

The variety of chemicals labeled as CECs leads to a variety of concerns for EPA. Widespread 

uses, some indication of chemical persistence, effects found in natural systems, and public 

concerns have made clear the need for EPA to develop criteria that can be used to help assess 

and manage potential risk of some CECs in the aquatic environment. A recent U.S. Geological 

Survey (USGS) reconnaissance study (Kolpin et al. 2002) provides a good example of the 

prevalence of a wide range of CECs in U.S. streams. Improved analytical chemistry techniques 

were used to document the occurrence of what the authors called organic wastewater 

contaminants (OWCs) being released into surface waters from wastewater treatment plants 

(WWTPs). The targeted OWCs included PPCPs, veterinary medicines and other EDCs. The 

investigators found at least one of 95 different target OWCs in 80 percent of the 139 streams 

sampled. A median of seven, and as many as 38, OWCs were found in single samples. 

The use and occurrence patterns associated with CECs are varied. Some CECs are similar to 

conventional toxic pollutants in that they are associated with industrial releases, whereas many 

others are used by the general public every day in homes, on farms, by businesses and industry 

(Daughton and Ternes 1999). PPCPs acting as EDCs can be released directly to the environment 

after passing through wastewater treatment processes, which are typically not designed to 

remove these pollutants from the effluent (Halling-Sorensen et al. 1998). Sludge from secondary 

treatment processes are land-applied as biosolids, supplying CECs which may leach or run off 

into nearby bodies of water. Pharmaceuticals used in animal feeding operations may be released 

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to the environment in animal wastes via direct discharge of aquaculture products (i.e., 

antibiotics), the excretion of substances in animal urine and feces of livestock animals, and the 

washoff of topical treatments from livestock animals (Boxall et al. 2003). 

EDCs discharged at WWTPs are one group of CECs with potentially widespread environmental 

effects (Folmar et al. 1996; Folmar et al. 2001; Jobling et al. 1998; Woodling et al. 2006). 

Although particular concern has been expressed about the anthropogenic EDCs, there are also 

natural estrogens (estradiol and its metabolites estriol and estrone) entering the aquatic 

environment through wastewater discharge and excretion from domestic animals. Furthermore, 

little is known about the environmental occurrence, fate and, transport for any of these 

compounds after they enter aquatic ecosystems. Many of the man-made compounds have been in 

use for a long time, and there is concern about pharmacologically active ingredients and personal 

care products that are designed to stimulate a physiological response in humans, plants, and 

animals (Daughton and Ternes 1999). 

Frequent detection of compounds by itself does not constitute a need for ALC. Rather, criteria 

development for CECs needs to focus efforts on chemicals that demonstrate a reasonable 

potential to adversely affect aquatic life. Of CECs now known to be found in some surface 

waters of the U.S., EDCs have received the most attention because field studies from around the 

world have demonstrated that very low concentrations of some of these compounds can 

significantly impact natural populations of aquatic vertebrates. For example, observational field 

studies (Jobling et al. 1998) have shown a high occurrence of intersex (the presence of both male 

and female characteristics) in wild populations of a fish known as roach (Rutilus rutilus) in rivers 

in the United Kingdom that are downstream from WWTPs. Similar results have recently been 

reported for white sucker (Catastomus commersoni) in northern Colorado, U.S.A (Woodling et 

al. 2006). In a multiyear study by Kidd et al. (2007), the authors showed that environmentally 

relevant concentrations of ethynylestradiol, EE2, caused reproductive failure and near collapse of 

a natural fathead minnow population in an experimental lake, and also had deleterious effects on 

the reproductive biology of the pearl dace. These direct effects resulting in loss of forage fish 

have led to cascading effects on the lake trout population due to lack of prey (Kidd, personal 

communication). Researchers from the U.S. Geological Survey (USGS) have observed intersex 

and testis-ova (the presence of eggs in the testis) in bass species collected from the Potomac 

River and its tributaries in West Virginia, Maryland, and Washington DC, and also quantified 

EDCs in their blood (Blazer et al. 2007; Chambers and Leiker 2006). The occurrence of intersex 

fish in the Potomac River, as well as documented occurrence of this and related effects in other 

waters of the US and internationally, prompted Congressional hearings that were held in October 

2006 to inquire about the “State of the Science on EDCs in the Environment,” as well as EPA 

activities associated with EDCs. 

1.3 Purpose and Organization of This White Paper 

The purpose of this white paper is to provide general guidance on how criteria development for 

CECs could be facilitated through a supplemental interpretation of the Guidelines, with 

particular attention to PPCPs with an EDC mode of action (MOA). Section 2 of this part (Part I) 

of the white paper describes the Guidelines procedures and identifies several areas in which these 

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procedures could be modified to address potential limitations for deriving criteria for CECs. 

Section 3 expands upon the areas of concern with respect to specific toxicological characteristics 

of some CECs. Section 4 summarizes these concerns and provides recommendations that could 

aid in the development of criteria for CECs in a resource efficient manner that takes best 

advantage of existing knowledge. Part II of this white paper further describes these concerns and 

recommendations using data for the synthetic pharmaceutical estrogen EE2. 

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2.0 CURRENT ALC METHODOLOGY 

The Guidelines specify various data and procedural recommendations for criteria derivation, and 

also define general risk management goals for criteria, which are to provide a high level of 

protection for aquatic communities and for important species in these communities. ALC are 

defined to consist of two concentrations – the Criterion Maximum Concentration (CMC), 

intended to protect against severe acute effects, and the Criterion Continuous Concentration 

(CCC), intended to protect against longer term effects on survival, growth, and reproduction. The 

CMC is used in criteria to limit peak exposures by requiring that 1-hour averages of exposure 

concentrations not exceed the CMC more often than once in three years on average. The CCC is 

used in criteria to limit more prolonged exposures by requiring that 4-day averages of exposure 

concentrations not exceed the CCC more often than once in three years on average. 

The CMC and CCC are usually derived from laboratory toxicity test results using specific 

standard procedures described in the Guidelines, but the Guidelines also have general provisions 

for deviating from these procedures as warranted by available information. The following text 

will first give an overview of the data requirements and calculations in the standard procedures, 

and then discuss how these procedures might vary under the umbrella of the Guidelines. 

2.1 Standard ALC Derivation Procedures 

The CMC is determined based on available Acute Values (AVs) – median lethal concentrations 

(LC50s) or median effect (for a severe acute effect such as immobilization) concentrations 

(EC50s) from aquatic animal acute toxicity tests (48- to 96-hours long) meeting certain data 

quality requirements. To compute a CMC, the Guidelines require that acceptable AVs be 

available for at least eight genera with a specified taxonomic diversity, in order to address a wide 

variety of the organisms constituting an aquatic animal community. These minimum data 

requirements include three vertebrates (a salmonid fish, a fish from a family other than 

salmonidae, and a species from a third chordate family) and five invertebrates (a planktonic 

crustacean, a benthic crustacean, an insect, a species from a phylum other than Chordata or 

Arthropoda, and a species from another order of insect or a fourth phylum). 

For each genus, a Genus Mean Acute Value (GMAV) is calculated by first taking the geometric 

mean of the available AVs within each species (Species Mean Acute Value, SMAV) and then the 

geometric mean of the SMAVs within the genus. The fifth percentile of the set of GMAVs so 

obtained is calculated based on a specified estimation method, and designated the Final Acute 

Value (FAV). The FAV is then lowered to the SMAV for an important, sensitive species if 

appropriate. The CMC is set equal to half of the FAV to represent a low level of effect for the 

fifth percentile genus, rather than 50% effect. 

The CCC is generally determined based on available Chronic Values (CVs), which are either (a) 

the geometric mean of the highest no-observed-effect concentration (NOEC) and lowest 

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observed effect concentration (LOEC) for effects on survival, growth, or reproduction in aquatic 

animal chronic tests or (b) in some recent criteria (e.g., ammonia), the EC20 in such tests based 

on concentration-effect regression analyses. Chronic tests for invertebrate species are required to 

include the entire life-cycle, but for fish partial life-cycle and early life-stage (ELS) testing 

protocols are accepted, the latter not including reproductive endpoints and not used if life-cycle 

or partial life-cycle tests are available and show more sensitive adverse effects. 

If CVs are available for at least eight genera with the required taxonomic diversity, the CCC is 

set to the fifth percentile of Genus Mean Chronic Values (GMCVs), by the same procedure used 

to derive an FAV from GMAVs. Otherwise, the CCC is set to the FAV divided by a Final Acute 

Chronic Ratio” (FACR) that is based on acute to chronic ratios (ACRs – the ratio of the AV to 

the CV from parallel acute and chronic tests) for at least three species with a specified taxonomic 

diversity. The CCC can also be based on plant toxicity data if aquatic plants are more sensitive 

than aquatic animals, or on other data as deemed scientifically justified. 

Further details on test requirements and calculation methods for the CMC and CCC are specified 

in the Guidelines, including deriving criteria that are a function of water quality characteristics. 

2.2 Alternatives for ALC Derivation 

The procedures described above enable broad application to toxic chemicals generally, and are 

only constrained by specific data requirements for quality and minimum taxonomic 

representation. Since they are not restricted with respect to specific types of chemicals, there is 

no reason to suppose that the standard data requirements and procedures specified by the 

Guidelines are any more or less applicable to CECs than to the chemicals for which criteria have 

already been developed. The Guidelines anticipated that rote application of the basic procedures 

may not yield the most appropriate criteria; consequently, the Guidelines provide flexibility 

when appropriate for deviation from the normal procedures regardless of the type of chemical, as 

indicated by the following provisions (hereafter referred to as the "Good Science" clauses: 

“These National Guidelines should be modified whenever sound scientific evidence 

indicates that a national criterion produced using these Guidelines would probably be 

substantially overprotective or underprotective of aquatic organisms and their uses on a 

national basis.” (p. 18).

"On the basis of all available pertinent laboratory and field information, determine if the 

criterion is consistent with sound scientific evidence. If it is not, another criterion, either 

higher or lower, should be derived using appropriate modifications of these Guidelines."

(p. 57).

In addition, although the standard procedures in the Guidelines for deriving a CMC and CCC use 

only toxicity tests meeting certain requirements, the Guidelines also mandate the collation and 

examination of other data that might show effects that should be considered in criteria derivation: 

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"Pertinent information that could not be used in earlier sections might be available 

concerning adverse effects on aquatic organisms and their uses. The most important of 

these are data on ... any other adverse effect that has been shown to be biologically 

important. Especially important are data for species for which no other data are 

available. ... Such data might affect a criterion if the data were obtained with an 

important species, the test concentrations were measured, and the endpoint was 

biologically important.” (p. 54).

While alternatives are allowed when a specific situation dictates, the Guidelines still require that 

any changes in the procedures are consistent with the level of protection represented by the 

standard procedures: 

"Derivation of numerical national water quality criteria for aquatic organisms and their 

uses is a complex process and requires knowledge in many areas of aquatic toxicology; 

any deviation from these Guidelines should be carefully considered to ensure that it is 

consistent with other parts of these Guidelines." (p. iv).

Therefore, for the development of criteria for any chemical, the general strategy should be to 

start with the standard Guidelines procedures and then to adapt those procedures as warranted by 

available information on the effects of the chemical. This strategy applies to CECs as well, 

although certain considerations might more consistently be important for CECs. Specific 

attributes of CECs that might affect criteria derivations are considered in Section 3 of this paper, 

but several issues are introduced here that are of general concern. 

Are data on acute toxicity needed for risk assessments? 

Some chemicals are not acutely toxic even at concentrations so high that they could not possibly 

occur in the environment (e.g., at the chemical solubility, or exceeding exposures possible based 

on known chemical production and discharges). The acute lethality of some classes of chemicals 

might be measurable, but would occur at environmental concentrations so much higher than 

those affecting reproduction, growth, or chronic survival that, in practice, environmental 

exposures will always be far below acutely lethal levels if those exposures are managed to limit 

chronic effects. Therefore, derivation of the CMC might be unnecessary or impossible. Thus, if 

the existing data indicate that it is reasonably certain that acute toxicity would not occur at 

environmentally relevant concentrations, conducting additional acute tests is likely to be 

unwarranted. 

Even if a CMC is not needed, another use of acute toxicity data is for developing “acute to 

chronic ratios” (ACRs) that are used with the FAV to calculate the CCC (see pages 40-42 in the 

Guidelines) , so that dropping acute testing requirements must consider this consequence as well. 

However, if acute effect concentrations are extremely high compared to chronic effect 

concentrations (large ACRs), whether the ACR approach should be even used warrants some 

consideration. Large ACRs are not, per se, less accurate than low ACRs, provided acute and 

chronic effect concentrations are well defined and the issue is simply extrapolating from acute to 

chronic toxicity within a species. However, for criteria calculations, the FACR needs to be a ratio 

that extrapolates from the fifth percentile of the acute effect concentration distribution to the fifth 

percentile of the chronic effect distribution. This requires appropriately combining ACR 

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information across species, the accuracy of which might be affected by large ACRs even if the 

accuracy of the individual ACRs is not. Therefore, in addition to not needing a CMC, extreme 

acute tolerance might also warrant direct calculation of the CCC rather than using the ACR 

approach, and thus eliminate the need for fulfilling all of the minimum acute toxicity test 

requirements as specified by the Guidelines. 

How should data requirements for tolerant taxa be addressed? 

The fifth percentile calculation methods for the CMC (as well as the CCC if the eight minimum 

data requirements noted above are met) require actual GMAV (or GMCV) values only for the 

four most sensitive genera. For more tolerant genera, it is only necessary to know that these 

toxicity values are greater than those of the four sensitive species. Therefore, toxicity test results 

that report "greater than" effect concentrations are acceptable for the tolerant taxa, and in fact are 

used in various criteria already. 

If chronic tests have not already been done on some taxa needed for the minimum data 

requirements, but which are known to be tolerant, testing resources might be wasted by 

generating numbers that will not affect results. If methods such as inter-chemical or inter-species 

extrapolation methods, or assays (e.g., in vitro tests, biomarkers) that have been related to apical 

effects such as reductions in growth, survival, or reproduction can demonstrate these taxa to be 

insensitive compared to other taxa, actual chronic tests on these taxa may not be needed. In other 

words, can minimum data requirements for tolerant taxa be satisfied by some type of estimation 

rather than by an actual test result? 

However, adding estimated data can become a rather open-ended process. Therefore, 

consideration must be given to how many estimated values should be allowed, relative to 

measured values, to produce an appropriate distribution of taxa in the data set used for criteria 

derivation. 

Should fish chronic tests be required to address reproduction? 

For chemicals (e.g., environmental estrogens) for which reproductive toxicity is of most concern, 

the allowance in the Guidelines for using ELS tests might need reconsideration. The Guidelines

already give priority to life-cycle and partial life-cycle tests when they are available and show 

greater sensitivity than ELS tests. However, other information (from other species, similar 

chemicals, knowledge of the MOA) regarding latent or multigenerational reproductive effects 

may demonstrate the importance of sexual development and reproduction, so as to establish a 

basis for not considering ELS test results (or even partial life-cycle tests), but rather requiring 

life-cycle tests for fish. 

What endpoints can serve as surrogates for traditional chronic endpoints? 

Although chronic criteria are and will continue to be based on effects on reproduction, growth, 

and survival, another issue is whether only toxicity data directly addressing these endpoints is 

acceptable. Is there additional information (e.g., sub-organismal biomarkers, behavioral data) 

that can be used in criteria derivation because they are adequately correlated to reproduction, 

growth, and survival? Use of such data would be consistent with the Guidelines requirements to 

examine all pertinent data and make modifications to the criteria derivation procedures that are 

consistent with sound scientific evidence 

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2.3 Precedent for Deviating from Basic ALC Derivation Procedures 

The recent ALC document for tributyltin (TBT) provides a good example of some of the types of 

procedural criteria modifications discussed above. TBT is a highly toxic biocide that has been 

used extensively in anti-fouling paint to protect the hulls of large ocean-going ships. It is deemed 

a problem in the aquatic environment because it is extremely toxic to non-target organisms, and 

has been linked to imposex (the superimposition of male anatomical characteristics on females) 

and to immuno-supression in snails and bivalves (U.S. EPA 2003). The concentrations reported 

to cause imposex in the laboratory are lower (range: 0.0093 to 0.0334 μg/L) than the FCV 

(0.0658 μg/L) calculated using the standard ALC derivation procedures (U.S. EPA 2003). The 

low effect concentrations established for female gastropods in the laboratory were subsequently 

corroborated in field studies. The CCC was lowered (to 0.0074 μg/L) based on the judgment that 

these effects were relevant for the risks of TBT to gastropod reproduction. 

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3.0 CHARACTERISTICS OF CECS AND THEIR INFLUENCE ON ALC 

DEVELOPMENT 

As described in Section 1.0, chemicals become labeled as CECs for a variety of reasons, many of 

which have relatively little to do with their toxicological characteristics. Consequently, the 

Guidelines cannot be interpreted or modified in one particular way that would be universally 

appropriate for all CECs. However, some characteristics may be shared by various CECs, such 

that discussing the implications of these characteristics in the context of deriving water quality 

criteria is worthwhile. The expected outcome is additional guidance addressing key issues that 

may arise and how best to accommodate these issues in deriving criteria. 

Much of the technical discussion that follows is centered on EDCs and, even more specifically, 

around chemicals that interact with the hypothalamic/pituitary/gonadal (HPG) axis. Endocrine 

function controlled via the HPG axis involves hormones broadly known as estrogens (“female” 

hormones such as estradiol) and androgens (“male” hormones such as testosterone), along with 

the body tissues and biochemical machinery with which they interact. Effects on this part of the 

endocrine system of various aquatic species have been documented in the literature, and 

publicized in the media, making toxicological disruption of this mechanism a good choice for 

discussing CECs in the context of the Guidelines. However, these types of substances are only a 

subset of EDCs, and an even smaller subset of CECs as a whole. While much of the discussion 

that follows uses HPG-active chemicals as a point of reference, the concepts presented may be 

useful in the derivation of ALC for many other chemicals as well. It is the principles more than 

the specifics that are important in considering the content of this report. 

3.1 Characteristics of HPG-Active EDCs 

While estrogenic and androgenic hormones are a core component of the HPG axis, this system 

also includes a much larger group of tissues and biochemical machinery within the body which, 

in vertebrates, govern sexual development, maturation, and reproduction. Commensurate with 

this complexity, there are many places within the system that environmental chemicals may act 

to modify the normal function of the HPG-axis. Thinking simply of “estrogenicity” or 

“androgenicity” as toxicological modes of action is still too broad – these categorical classes are 

more the outward “symptoms” of disruption in the HPG axis than they are unique modes of 

toxicological action. For example, the synthetic steroids EE2 and trenbolone bind to (and act as 

agonists of) vertebrate estrogen and androgen receptors, respectively, with similar or greater 

affinity than the natural endogenous hormones, estradiol and testosterone. In contrast, a variety 

of other medicinal pharmaceuticals are specifically designed to do the opposite, to be antagonists 

of these same receptors. As examples, tamoxifen (breast cancer treatment) and flutamide 

(prostate cancer treatment) bind quite specifically to vertebrate estrogen and androgen receptors, 

respectively, thereby blocking the activity of endogenous steroid hormones. But disruptors of the 

HPG axis are not limited to chemicals that bind directly to estrogen or androgen receptors; they 

also include chemicals that interact elsewhere in the overall biochemical pathway. As an 

example, there are chemicals that exert their activity through interactions with CYP (cytochrome 

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P450) enzymes involved in steroid production. The pharmaceutical chemical fadrozole acts to 

inhibit CYP19 aromatase, the enzyme that converts estradiol to testosterone. A number of 

conazole fungicides act as competitive inhibitors of several CYPs further up the steroid synthesis 

pathway (Ankley et al. 2005). 

Unlike many other chemicals that have either non-specific (e.g., narcotics) or more generalized 

reactive modes of action (e.g., electrophilic chemicals interacting with nucleic acids and 

proteins), HPG-active compounds tend to have very specific interactions with particular 

molecular targets within the biochemical pathway. There are a number of consequences arising 

from this specificity. One important consequence of target specificity is potency. Many 

pharmaceuticals are designed to be highly specific, and thus are extremely potent. For example, 

EE2 and trenbolone affect reproduction and development in fish at water concentrations in the 

very low ng/L (part-per-trillion) range (e.g., Ankley et al. 2003; Länge et al. 2001), well below 

effect concentrations for most chemicals for which current ALC have been derived. These very 

low biologically-active concentrations present substantial challenges for analytical 

determinations associated either with lab-based effects testing or field monitoring of in situ

exposures. In the case of EE2 and/or trenbolone, effects observed in fish are at concentration 

levels below the methodological limit of detection for most laboratories even in laboratory test 

water, and even more so ambient water and effluents. 

Such high potency can influence how one would approach criteria derivation when the chemicals 

exert minimal acute toxicity, but cause mostly long-term, sub-lethal effects. Trenbolone and EE2 

illustrate this situation quite well. Like most pharmaceuticals (some exceptions being 

chemotherapy and anti-parasitical agents), these chemicals are designed to “adjust” the 

biochemistry of the body without causing acute toxicity or other significantly adverse side 

effects. As a consequence, these types of pharmaceuticals tend to have low toxicity in short-term 

lethality assays (Webb 2001). In the context of criteria development, this has implications for the 

use of ACRs. Most conventional toxic pollutants with EPA ALC have ACRs of 10 or less 

(Cunningham et al. 2006; Host et al. 1995). In contrast, ACRs for EE2 and 17β-trenbolone in 

fish have been shown to range from 1,000 to greater than 300,000 (Ankley et al. 2005). Again, 

this is a result of relatively low acute toxicity and high chronic potency. Importantly, limited data 

for other MOA classes of pharmaceuticals suggest that this phenomenon is not restricted to 

endocrine-active substances. For example, Huggett et al. (2002) reported an ACR in fish of about 

50,000 for propanolol, a β-blocker. As discussed in Section 2, this large difference in acute and 

chronic potency may both make CMC values moot in the environmental management of these 

chemicals, and introduce uncertainty in the extrapolation between acute and chronic effects in 

the derivation of a CCC. 

The specificity of the molecular target also can greatly affect those taxa likely to be sensitive to 

the chemical MOA of concern. While some biological pathways (e.g., energy metabolism) tend 

to be highly conserved across all organisms, others can be quite specific to certain phylogenetic 

groups. Although the control of reproductive function through the HPG axis is highly conserved 

across vertebrate classes, lower taxonomic groups such as invertebrates have different endocrine 

system structure that function differently. For example, Segner et al. (2003) tested several 

estrogenic chemicals, including EE2, in a variety of partial and full life-cycle tests with a model 

fish (zebrafish) and several aquatic invertebrate species. They found that the fish was by far most 

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sensitive to the effects of the estrogenic chemicals, and was the only species that responded to 

EE2 at environmentally-relevant concentrations. As a result, it is likely that chronic toxicity data 

for fish would be the most influential in setting the criterion for EE2, and correspondingly 

unlikely that toxicological data for invertebrate species would have much impact. Plants do not 

have comparable endocrine system structure or function, and would not be expected to be 

sensitive to these types of compounds, but there is research that indicates that algal species may 

be a uniquely sensitive taxa for the assessment of other types of CECs such as antibacterial 

products like triclosan (Orvos et al. 2002; Wilson et al. 2003). 

Specificity in MOA can also affect how or if effects are expressed within a toxicity test, even in 

potentially sensitive species. In the case of chemicals that affect endocrine function, there are 

distinct “windows” when animals are likely to be sensitive and/or exhibit adverse outcomes. For 

example, a popular amphibian early developmental assay-FETAX (Frog Embryo Teratogenesis 

Assay-Xenopus) would be inadequate for detecting thyroid-active toxicants because the period of 

exposure and observation occurs early in development before the thyroid axis is functional in 

Xenopus. In the case of HPG-active toxicants, there are two windows of sensitivity during an 

animal’s life: during sexual differentiation in developing organisms (when “organizational” 

alterations occur), and during active reproduction in adults (when “activational” responses can be 

manifested; Ankley and Johnson 2004). As a result, it is critical that testing for HPG-active 

EDCs occur during periods when the system is vulnerable to disruption. It is equally critical that 

toxicity tests include observations during the periods when effects are expressed. Some of the 

changes caused during sensitive early developmental windows may not be expressed until later 

in life. For example, the ELS toxicity test protocol commonly used in criteria development to 

estimate the chronic sensitivity of fish contains the early life stages that could be sensitive to 

disruption of sexual development, but it does not extend through to maturation, and would 

therefore be insensitive for detecting disruption of sexual development. 

3.2 Implications for ALC Development 

As is clear from the text above, some characteristics of HPG-active chemicals (and many other 

CECs) create the need to carefully interpret the intent of the Guidelines, not just the routine 

derivation process. As indicated in Section 2.0 there is nothing about CECs that invalidates the 

principles embodied in the Guidelines; however, the Guidelines were written before many of the 

issues discussed in Section 3.1 were known, so they do not necessarily contain prescriptive 

guidance for some of the nuances created by some CECs. The following paragraphs discuss the 

implications of these issues for criteria development, following the four general topic areas 

outlined in Section 2.0: 

• The need for and relevance of acute toxicity data and a CMC; 

• Defining minimum data requirements in terms of taxonomic coverage; 

• Defining appropriate chronic toxicity data; and 

• Selecting effect endpoints upon which to base criteria 

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3.2.1 The Need For and Relevance of Acute Toxicity Data and a CMC

As described in Section 2.2, there are two primary uses for acute toxicity data under the 

Guidelines: 1) the derivation of the CMC; and 2) establishment of the CCC when the 

FAV/FACR method is used. As a practical matter, if the CMC is more than 96-fold higher than 

the CCC, then it will always be the CCC that is more limiting. This is because in the standard 

formulation of criteria, the CMC has a one-hour averaging period and the CCC a 96-hour 

averaging period; thus, if the difference between them is more than 96-fold, it is mathematically 

impossible to exceed the CMC without also exceeding the CCC. A minor exception to this issue 

occurs when ALC are implemented in an NPDES permit such that the CMC is applied to whole 

effluent while the CCC is applied after mixing, and the available in-stream dilution is large. 

However, these exceptions are rare, and even the 96-fold difference discussed here pales in 

comparison to the factors of 1,000 to 300,000-fold discussed previously in regard to EE2 and 

trenbolone. In cases where such extreme differences between acute and chronic toxicity 

thresholds exist, establishing ALC as having only a CCC seems a reasonable approach. 

While it is easy to see why a CMC would not be necessary when you have sufficient acute test 

data to show that the CMC would be dramatically higher than the CCC, this begs the question of 

how much data are needed to decide that this is the case. This decision should occur during the 

“problem formulation” step in the risk assessment for a specific chemical/class, and should be 

guided by the following types of information: 

• the amount and phylogenetic spread of acute toxicity data that are available; 

• toxicity data from short-term exposures that do not meet the strict definitions in the 

Guidelines of acute toxicity data acceptable for criteria derivation, but from which 

information on responses to acute exposures can be inferred; 

• short-term effect data garnered from longer-term exposures; 

• information from closely related chemicals that are thought to have the same MOA, and 

have more robust acute data sets; and 

• knowledge of the degree of phylogenetic distribution of the toxicity pathway of concern. 

A complicating issue resulting from a “moot” CMC is that data availability for acute effects will 

likely be limited. As such, having less than the required acute MDRs may preclude the ability to 

derive a CCC using the FAV/FACR approach typically used in the Guidelines. For chemicals 

with highly specific modes of action and large ACRs (such as many EDCs), it is very likely that 

the mechanisms for acute and chronic toxicity differ, since biological activity resulting in chronic 

effects is designed into the product and not a secondary consequence - such as many of the 

historical contaminants for which EPA has developed criteria. Also, sensitivity of different taxa 

classes to acute and/or chronic toxicity varies widely due to presence (or absence) and structure 

and function of phylogenetically-conserved systems. Both of these issues would introduce 

considerable uncertainty into the availability and interpretation of ACRs, and probably make it 

inadvisable to use the FAV/FACR approach anyway. The Guidelines discuss the inadvisability 

of using the ACR approach when ACRs vary by more than a factor of 10 without a clear 

relationship to taxonomy or acute sensitivity (page 41 of the Guidelines). A more advisable 

approach would generally be to develop a CCC directly from a sufficiently robust set of chronic 

data, using the procedures outlined in the Guidelines or an appropriate modification thereof. 

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3.2.2 Defining Minimum Data Requirements in Terms of Taxonomic Coverage

To develop a CCC directly from chronic toxicity data (rather than via FAV/FACR), the 

Guidelines require that acceptable chronic toxicity data be available from at least eight families 

with a taxonomic distribution fulfilling the requirements specified in the Guidelines (referred to 

as the “minimum data requirements” or “MDRs”). Having a blanket requirement for meeting the 

eight MDRs was included to insure a minimum level of “certainty” that the Guidelines will be 

protective of the broad phylogenetic distribution of organisms found in aquatic systems. 

Including this phylogenetic spread also enables criteria to be developed for chemicals for which 

the toxicological MOA is not known. Instead of “knowing” what organisms are most likely to be 

sensitive to a particular chemical, requiring a broad spread of empirical toxicity data makes it 

likely that whatever taxa may be sensitive to a chemical, they will be represented to some degree 

in the toxicity data set. 

In the case of EDCs, PPCPs, and certain other chemical classes, we may have a reasonable 

understanding of the toxicological MOA for the chemical, and from that knowledge we may be 

able to infer what taxa are most likely to be sensitive to a particular chemical (Ankley et al. 

2007; Williams 2005). As discussed in Section 2.2, the procedure used in the Guidelines for 

estimating the 5th percentile of a toxicity distribution is dependent on only the four lowest values; 

for this reason exact values for insensitive genera are not necessary, as long as there are 

sufficient data to infer that their sensitivity is lower than the four most sensitive genera. 

So how does one determine that a particular taxon is insensitive? The general structure of the 

Guidelines presumes that sensitivity is determined by conducting an acceptable toxicity test with 

that taxon. However, one can infer that the actual need is only to have sufficient information to 

conclude that the taxon is insensitive; if that determination can be confidently made based on 

other information, the information need may be met even if an actual toxicity test with that 

particular organism and chemical has not been conducted. This does not change the intent of the 

Guidelines. It only acknowledges the possibility that there is more than one way to meet the 

information requirement. 

Using the example of EE2, there is both physiological understanding and some empirical toxicity 

data to support the belief that vertebrates will be far more sensitive to EE2 toxicity than will 

invertebrates (see Part II of this white paper and Segner et al. 2003). As such, it would seem 

inappropriate to invest resources in testing a wide range of invertebrate taxa classes for 

sensitivity when all existing data indicate that the data would not affect the final criterion, which 

would be driven by sensitivity of vertebrates. In this case, it makes sense to argue that certain of 

the eight MDRs might be declared met not through direct testing, but through toxicological 

understanding of the chemical’s MOA and the physiology of those other taxa or existing toxicity 

data that establishes sensitivity differences among taxa. 

While this logic is clear, one must be careful in presuming that the primary MOA demonstrated 

by organisms with the target physiology is the only toxic MOA for the chemical. Particularly 

given the phylogenetic diversity of organisms, it is always possible that a chemical that behaves 

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with one MOA in one class of organisms may exert toxicity through a different mechanism in a 

different phylogenetic group. There are precedents for this scenario (Ankley et al. 2007). For 

example, exposure to the non-steroidal anti-inflammatory drug diclofenac via consumption of 

dead livestock has greatly diminished some populations of vultures in several East Asian 

countries. Diclofenac kills the birds through renal failure, which is only a relatively minor sideeffect of the drug in mammals. While the mechanism of renal toxicity in vultures is likely 

molecularly related to the mechanism of therapeutic action in man, i.e., both seem to occur due 

to inhibition of prostaglandin synthesis (Meteyer et al. 2005), the inhibition of similar molecular 

components appears to be manifested as dramatically different whole organism endpoints. The 

key is in achieving a reasonable balance between expending resources on collecting data most 

likely to influence the criterion, while maintaining some kind of backstop against initially 

unexpected toxicity in other organisms. 

One possibility for enhancing confidence regarding phylogenetic sensitivity is in considering 

data for other, closely-related chemicals with the same MOA. While the Guidelines focus 

analysis on toxicity data for the specific chemical in question, an understanding of toxicological 

MOA can also lead to an understanding of how other chemicals might act to exploit the same 

biological system in the same way. For example, one might reasonably infer that the relative

species sensitivity to EE2 is likely similar to 17-ß estradiol (E2), the natural hormone which EE2 

mimics. If, for example, there were a taxon which had been tested and found insensitive to E2, 

but had not been tested with EE2, it seems a reasonable assumption that that taxon would also be 

insensitive to EE2. 

The possibility of fulfilling certain information requirements using data other than from direct 

toxicity testing does raise some other interpretation challenges, in particular the definition of the 

sample size for determining the 5th percentile of the genera sensitivity distribution. For example, 

if one has reason to believe that all crustaceans would be insensitive to a chemical, how many 

genera does that assertion represent in the calculation of the genera sensitivity distribution? 

While this is a real issue that will have to be addressed, we believe the problem is tractable and 

the details of the resolution are left to later work. 

Because of the risk that our mechanistic understanding of a chemical may be incomplete, it 

seems unlikely that one could justify completely bypassing several MDRs solely on theoretical 

arguments (e.g., developing a criterion for a testosterone mimic based only on chronic toxicity 

data for vertebrates, with no invertebrate data at all). At the same time, prudent application of 

other data types to fulfill certain information requirements for criteria derivation does seem 

appropriate. Given the tremendous variation in understanding and availability of data likely to 

exist for different CECs, it is presumed that at least initial application of this approach will have 

to be justified on a chemical-by-chemical basis using appropriate scientific judgment. However, 

lines of evidence that might be applicable to this determination include: 

• an in-depth understanding of the toxicological (or, in the case of drugs, therapeutic) 

MOA; 

• information on the basic physiology of other taxa in relation to the MOA; 

• toxicity data from chronic exposures or other relevant experiments that do not meet the 

strict definitions of acceptable chronic data given in the Guidelines, but from which 

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information on relative taxon sensitivity can be inferred; and 

• information from closely related chemicals that are thought to have the same MOA and 

have more robust acute or chronic data sets. 

A separate, but related issue arises in respect to data from species not resident to North America. 

The Guidelines specify the use of toxicity data only from species resident to North America. 

However, particularly in regard to the study of EDCs, some fish species not resident to the U.S. 

have been advanced as experimental models for the evaluation of the chronic effects of EDCs to 

fish. Two clear examples at the time of this report are the zebrafish (Brachydanio rerio) and the 

Japanese medaka (Oryzias latipes), for which equivalency of EDC test data (with the fathead 

minnow) has been proposed through international groups such as the Organization for Economic 

Cooperation and Development (OECD; Ankley and Johnson 2004). These species have a rich 

toxicological database, and we know of no reason to believe that their sensitivities would be 

expected to be substantively different from sensitivities of at least some fish resident to the U.S. 

In keeping with international harmonization, we suggest that toxicity data from species with 

recognized international equivalency be included in criteria derivation with the full weight given 

to data from resident species. 

3.2.3 Defining Appropriate Chronic Toxicity Data

The Guidelines state that acceptable chronic tests for criteria derivation are full life-cycle 

exposures (F0 egg to F1 offspring) for both vertebrates and invertebrates, as well as partial lifecycle (adult to juvenile) and early life-stage (ELS; egg to juvenile) tests for fish. The acceptance 

of ELS tests in particular as acceptable chronic tests is predicated on the work of McKim et al. 

(1978) and other evidence that the toxicity thresholds obtained from ELS tests are generally 

within a factor of two of the thresholds from life-cycle chronic tests. 

While this general approach has been applied with apparent success for many chemicals, the 

Guidelines intimate concerns with the approach, noting that for some chemicals, ELS tests might 

not be good predictors of chronic toxicity, which would violate the principle underlying the use 

of ELS tests as chronic data (page 39 in the Guidelines). As noted previously, toxicological data 

for chemicals like EE2 show that certain chemicals may have potent effects on life processes that 

lie outside the exposure period represented by ELS tests (e.g., pronounced effects on 

reproduction), or on life processes for which the expression of effects does not occur until after 

the ELS period (e.g., embryo or larval exposure resulting in effects on sexual development and 

maturation in adult fish; see Section 3.1). It is clear from these examples that there are chemicals 

for which ELS tests should not be used as surrogates for full life-cycle exposures. In fact, 

chemicals that affect sexual differentiation may not be adequately assessed even with partial lifecycle exposures, since these protocols do not generally include observation of sexual 

development/maturation in fish exposed during early development. 

While the “Good Science” clause and other text in the Guidelines would not support reliance on 

ELS tests as chronic data for chemicals known to have specific effects on other life processes, 

such as sexual development or reproduction, the Guidelines would allow the development of a 

criterion using only ELS data for fish if there were not any specific data to indicate that this 

approach would be inappropriate. This is akin to an “innocent until proven guilty” approach. 

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However, we believe experiences with chemicals like EDCs make clear the need to move from 

the previous approach to one of “guilty until proven innocent.” In other words, it is probably 

wiser to require that the chronic toxicity data for fish include exposure and observation over a 

full life-cycle unless there is an affirmative reason to believe that it is not necessary (note: this 

issue is equally relevant to invertebrates species, but the ELS tests discussed in the Guidelines

are focused explicitly on fish; invertebrate tests would already be required to be life-cycle). In 

keeping with this shift in emphasis, we believe the requirements for chronic toxicity data in the 

Guidelines should be tightened by adding the further requirements that either: 

1) Full life-cycle data be available for at least one fish species; or 

2) There is a body of experimental information indicating that life processes outside 

the ELS or partial life-cycle exposure/observation windows would not be 

important to capturing the important toxicological effects of the chemical. 

At first glance, #2 may seem like requiring the proof of a negative, in that one would have to 

actually conduct the life-cycle test required by #1 in order to show that #2 is true. However, we 

believe there may be circumstances in which there may be data that speak to the sensitivity of 

different life stages that come from studies that, while scientifically valid, for some reason do not 

meet all the requirements of a valid life-cycle test as defined in the Guidelines. For example, 

there may be data for a life-cycle test with a non-resident species that includes the relevant life 

processes but does not qualify as an acceptable chronic test for the derivation of criteria because 

it is non-resident. Alternatively, there may be data from experiments that violate other 

requirements of acceptable toxicity data under the Guidelines, but still provide insight into 

sensitive exposure periods or life processes. Even though CVs from such data may not be used 

directly to calculate a chronic criterion, it seems reasonable to use such data to evaluate the 

question of where in the life-cycle there are important windows of exposure and/or effect and 

how that constrains the adequacy of ELS tests to represent chronic toxicity. In other cases, there 

may be sufficient information from other types of research to demonstrate to a reasonable level 

of certainty that a chemical’s toxicological mechanism(s) would not preclude the use of ELS 

tests as indicators of chronic toxicity. 

Where life-cycle toxicity data are available, the results of those experiments should be carefully 

examined to determine the likelihood that important windows of exposure or effect lie outside 

ELS test protocols. Obviously, if there is meaningful potential for effects outside the ELS 

exposure period, ELS tests should not be used as surrogates for more involved chronic tests. It 

may also be that the knowledge of toxicological mechanism for a particular chemical may be 

sufficient that meaningful chronic toxicity data could be developed from exposures that have a 

structure different from the life-cycle, partial life-cycle, and ELS protocols defined explicitly in 

the Guidelines. While defining such alternate protocols is beyond the scope of this document, we 

recognize the potential for such a situation and leave it to appropriate implementation of the 

“Good Science” clause to allow for inclusion of such alternative exposure protocols as surrogates 

for chronic toxicity data, most likely in addition to, rather than instead of, data from life-cycle 

toxicity tests. 

At the other end of the spectrum lie toxicity tests that extend beyond the definition of a full lifeDRAFT DOCUMENT
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cycle test, often referred to as multi-generational tests. Because they encompass the full range of 

life processes as a life-cycle test, we feel that they should be included as acceptable chronic tests, 

assuming they meet all other requirements for test acceptability. Some studies have reported 

effects from EDC or other chemicals in which exposure to one generation creates effects in a 

later generation that were not observed in prior generations even at the same life stage (Nash et 

al. 2004). If substantial, such effects could create a situation where even full life-cycle toxicity 

tests might underestimate the chronic toxicity of a chemical and therefore produce criteria that 

are potentially under-protective. While we recognize the potential for this situation, at present we 

believe there is not sufficient reason to make multi-generational testing a requirement for criteria 

development, unless there is specific, compelling information that a criterion would be 

substantially under-protective if multi-generational effects were not rigorously considered. 

3.2.4 Selecting Effect Endpoints Upon Which to Base ALC

The selection of endpoints appropriate to the derivation of ALC must be tied to the narrative 

intent of the overall Guidelines. The stated goal of ALC is to “protect aquatic organisms and 

their uses” (see Water Quality Standards Handbook; U.S. EPA 1994b). While the exact meaning 

of “protection” is not defined, there is considerable discussion in the Guidelines document that 

makes clear that protection does not mean the prevention of any measurable biological effect in 

any organism. Instead, there is discussion of endpoints that are “biologically important” and 

prevention of “unacceptable effects”; this implies that in the context of criteria there are effects 

that are “biologically unimportant” and/or levels of effect that are “acceptable.” Related concepts 

include the idea that natural populations can withstand some magnitude/frequency of disturbance 

and still meet the intent of the Guidelines. 

With “protection of aquatic organisms and their uses” as the assessment endpoint, a decision 

must be reached as to which biological responses (measurement endpoints in risk assessment 

parlance) are appropriate to address this goal. Survival, growth, and reproduction are processes 

that are generally accepted as being directly related to this goal, as these are all demographic 

parameters that directly affect population dynamics (although, the exact quantitative relationship 

is not always fully determined). However, there are many more biological responses that have 

been observed in response to toxicant exposure, both at the whole organism level (e.g., behavior) 

and at lower levels of biological organization (e.g., biochemical or histological changes). For 

many of these endpoints, their relationship to the assessment goal, “protection of aquatic 

organisms and their uses,” is less clear. In this regard, we must consider an additional goal of the 

Guidelines – that criteria “provide a reasonable and adequate amount of protection, with only a 

small possibility of considerable overprotection or under-protection” (page 5 of the Guidelines). 

In keeping with this intent, it is important that criteria focus on endpoints that affect the 

assessment endpoint, but not create overprotection by preventing any measurable effect (or 

possibility of that effect). There must be a reasonable, affirmative connection between the 

measured response and the assessment endpoint. 

The Agency’s Framework for Ecological Risk Assessment (U.S. EPA 1992) identifies this 

problem: 

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In many cases, measurement endpoints at lower levels of biological organization 

may be more sensitive than those at higher levels. However, because of 

compensatory mechanisms and other factors, a change in a measurement 

endpoint at a lower organizational level (e.g., a biochemical alteration) may not 

necessarily be reflected in changes at a higher level (e.g., population effects). (p. 

14) 

And later on: 

Ideally, the stressor-response evaluation quantifies the relationship between the 

stressor and the assessment endpoint. When the assessment endpoint can be 

measured, this analysis is straightforward. When it cannot be measured, the 

relationship between the stressor and measurement endpoint is established first 

then additional extrapolations, analyses, and assumptions are used to predict or 

infer changes in the assessment endpoint. (p. 23) 

Measurement endpoints are related to assessment endpoints using the logical 

structure presented in the conceptual model. In some cases, quantitative methods 

and models are available, but often the relationship can be described only 

qualitatively. Because of the lack of standard methods for many of these analyses, 

professional judgment is an essential component of the evaluation. It is important 

to clearly explain the rationale for any analyses and assumptions. (p. 23) 

Existing criteria documents contain many types of data that were not used in the criteria 

derivation (the documents collate and review these data, but they are not used to actually define 

the criterion concentration) and it is useful to the discussion here to consider how such data have 

been interpreted. For example, the following text is derived from the most recent criteria 

document for ammonia (U.S. EPA 1999, see Appendix 5): 

Endpoint indices of abnormalities such as reduced growth, impaired 

reproduction, reduced survival, and gross anatomical deformities are clinical 

expressions of altered structure and function that originate at the cellular level. 

Any lesion observed in the test organism is cause for concern and such lesions 

often provide useful insight into the potential adverse clinical and subclinical 

effects of such toxicants as ammonia. For purposes of protecting human health or 

welfare these subclinical manifestations often serve useful in establishing ‘safe’ 

exposure conditions for certain sensitive individuals within a population. 

With fish and other aquatic organisms the significance of the adverse effect can 

be used in the derivation of criteria only after demonstration of adverse effects at 

the population level, such as reduced survival, growth, or reproduction. Many of 

the data indicate that the concentrations of ammonia that have adverse effects on 

cells and tissues do not correspondingly cause adverse effects on survival, 

growth, or reproduction. No data are available that quantitatively and 

systematically link the effects that ammonia is reported to have on fish tissues 

with effects at the population level. This is not to say that the investigators who 

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reported both tissue effects and population effects within the same research did 

not correlate the observed tissue lesions and cellular changes with effects on 

survival, growth, or reproduction, and ammonia concentrations. Many did, but 

they did not attempt to relate their observations to ammonia concentrations that 

would be safe for populations of fish under field conditions nor did they attempt to 

quantify (e.g., increase in respiratory diffusion distance associated with gill 

hyperplasia) the tissue damage and cellular changes (Lloyd 1980; Malins 1982). 

Additionally, for the purpose of deriving ambient water quality criteria, ammoniainduced lesions and cellular changes must be quantified and positively correlated 

with increasing exposures to ammonia. 

In summary, the following have been reported: 

1. Fish recover from some histopathological effects when placed in water that 

does not contain added ammonia. 

2. Some histopathological effects are temporary during continuous exposure of 

fish to ammonia. 

3. Some histopathological effects have occurred at concentrations of ammonia 

that did not adversely affect survival, growth, or reproduction during the same 

exposures. 

Because of the lack of a clear connection between histopathological effects and 

effects on populations, histopathological endpoints are not used in the derivation 

of the new criterion, but the possibility of a connection should be the subject of 

further research.

As discussed in greater detail below, chemicals such as EDCs have been shown to produce a 

wide variety of measurable changes at many different levels of biological organization. The 

challenge is to select from among those the endpoints that have sufficiently clear connection to 

expected effects on populations of aquatic organisms. 

3.2.4.1 Specific Examples of Measurable Changes at Different Levels of Biological 

Organization 

The range of organismal endpoints that have been reported in the literature is vast, and varies to 

some degree on the organism and toxicant. With respect to only the HPG axis in vertebrates, this 

range of endpoints over and above direct measures of survival, growth, and reproduction 

includes: 

• Biochemical measures (e.g., the female-specific yolk precursor protein vitellogenin; 

native hormones estradiol, testosterone, 11-ketotestosterone); 

• Histopathological measures (e.g., proportion of spermatogonia, presence of testis-ova, 

oocyte atresia, Leydig cell hyperplasia/hypertrophy); 

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• Gross morphology (e.g., secondary sex characteristics: nuptial tubercles, coloration, 

ovipositors); and 

• Behavioral measures (e.g., nest building, defense/aggression). 

A comprehensive survey and evaluation of all such endpoints is far beyond the scope of this 

document. In lieu of that, this section presents in depth discussion of several individual measures 

relevant to the HPG axis, including their strengths and weaknesses as direct indicators of likely 

population level effects. The point of this discussion is simply to provide examples of the issues 

that must be considered in making a decision as to the biological importance and scientific 

defensibility for a specific endpoint, organism, or toxicant as it pertains to ALC derivation. 

These decisions will likely require case by case consideration; in certain circumstances, the 

suitability of a particular endpoint may vary across chemicals depending on how an individual 

chemical influences that endpoint. 

One of the challenges that arises when incorporating alternative endpoints into criteria derivation 

is the need to not only conclude that the endpoint warrants consideration, but also establish some 

definition of what level of effect on that endpoint is unacceptable. While these links may not be 

completely quantitative, one would not want the definition of an unacceptable effect on one 

endpoint to be grossly disproportional to that considered unacceptable for another (i.e., if a 20% 

reduction in reproduction is considered unacceptable, what degree of estradiol (E2) suppression 

is equivalent to a 20% reduction in reproduction?). 

In the text that follows, endpoints are categorized as being either “organizational” or 

“activational.” Organizational endpoints are those that are a result of changes to the normal 

growth and development of an organism, and are generally not reversible with cessation of 

exposure. Activational endpoints are those that occur in comparatively plastic tissues in response 

to exposure, but which may revert to their prior or normal condition with cessation of exposure. 

Organizational Endpoint: Sex Reversal 

Exposure of developing fish to endocrine-active materials during sensitive “windows” in early 

development can skew phenotypic sex dramatically toward either females (estrogenic chemicals) 

or males (androgenic chemicals). This response has been exploited by aquaculturists, who for 

many years have used potent natural or synthetic steroids to produce mono-sex stocks. The 

sensitivity of fish to this type of “sex reversal” is species-specific, and critical windows of 

exposure can vary markedly across species. The response can be manifested in several different 

ways, ranging from more or less completely sex-reversed animals (i.e., occurrence of gonads and 

secondary sex characteristics completely reflective of the opposite sex) to more subtle changes, 

such as the occurrence of intersex gonads (discussed further below). A significant challenge in 

assessing this condition-either in the lab or field-is knowledge of actual genetic sex of the fish. 

Since the molecular basis of sex determination in many fish is not known, reliable genetic 

markers of what sex an animal is programmed to be are not available for most test species (one 

notable exception here is the Japanese medaka, which is commonly used for endocrine testing in 

some parts of the world; Ankley and Johnson 2004). The net result of this is that the only way to 

practically monitor sex reversal in most fish species is indirectly, through analysis of sex ratios 

(generally based on phenotypic sex). This requires, of course, considerable background 

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knowledge concerning “normal” sex ratios for a species (or even strain) of fish. For some lab test 

species (e.g., fathead minnow), the normal sex ratio appears to be about 1:1, while for other 

commonly-tested small fish models (e.g., zebrafish), the ratio can be quite variable (Ankley and 

Johnson 2004). In field studies, collection of accurate sex ratio data also can be exceedingly 

difficult, depending on variables such as sampling gear and location and timing of collections. 

Changes in the sex ratio of populations of fish, either in the lab or field, can be quite indicative of 

an endocrine-specific MOA, indicating exposure to estrogenic or androgenic chemicals (or even 

chemicals that block the actions of sex steroids). Significantly, from a risk assessment 

perspective, alterations in sex ratio could also have direct implications for spawning success and 

population viability. The degree to which sex ratios are critical in determining embryo 

production will vary based on reproductive strategies of the species of concern (e.g., broadcast 

versus paired spawners); however, from an evolutionary perspective, one would speculate that 

any departure from normal sex ratios for a species/population might be considered maladaptive. 

Organizational Endpoint: Intersex 

Exposure to certain classes of endocrine-active chemicals during critical windows in early 

development can produce intersex gonads (commonly termed testis-ova), a situation in which the 

gonads simultaneously contain both ovarian and testicular tissue. Different studies from around 

the world have shown an elevated occurrence of intersex fish downstream of municipal effluents 

containing natural and synthetic steroidal estrogens, including EE2 (WHO 2002). In fact, 

collection of intersex fish from the field has been one of the most visible manifestations of the 

effects of EDCs on fish/wildlife. For example, in a widely publicized USGS study, Blazer et al. 

(2007) recently reported that in the South Branch of the Potomac River and select nearby 

drainages, more than 80 percent of all the male smallmouth bass sampled had oocytes growing 

within their testicular tissue. Although histology is required to determine and quantify intersex, 

the techniques involved are relatively straight-forward. What is more challenging than 

measurement is interpretation of the results. For example, it appears that some degree of 

background intersex can occur, even in species held under carefully-controlled conditions (Grim 

et al. 2007). The degree of background intersex and sensitivity to chemically-induced intersex 

appear to be quite species-specific, requiring a thorough understanding of normal gonad 

differentiation and development in the species of concern. 

Even in species for which background intersex is low, there is uncertainty as to the degree to 

which the condition could occur and not interfere with normal reproductive function. For 

example, in a field study in the UK, Jobling et al. (1998) noted a wide range of intersex in roach 

collected, even from the same site, with severity of the response ranging from occurrence of a 

few primary oocytes in otherwise normal testicular tissue to instances where there was a 

complete absence of sperm ducts in the males. Arguably, the former fish could produce viable 

sperm, while the latter certainly would not. So, although intersex is an intuitively reasonable 

endpoint upon which to base predictions of possible adverse effects of endocrine-active 

chemicals on reproductive success, determination of the relationship between severity of the 

condition and production of viable embryos is required to conduct this analysis. 

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Activational Endpoint: Behavior 

Although not usually considered a biomarker in the traditional sense, behavior is an endpoint that 

historically has been seldom used for ecological risk assessment, including the derivation of 

ALC. There are several reasons for this: (1) the types of assays used to assess behavior can be 

quite labor-intensive, (2) many methods for assessing toxicant-induced behavior have some 

degree of subjectivity, (3) many behavioral changes (e.g., gill ventilation in fish) are relatively 

non-specific in that they do not necessarily reflect exposure to chemicals with a specific MOA, 

and (4) translation of behavioral changes into adverse effects on endpoints such as survival, 

growth and reproduction can be difficult. Nonetheless, virtually all environmental toxicologists 

recognize the potential for chemically-induced alterations in behavior to influence the health of 

individual animals and populations. 

There are some compelling reasons to consider behavior as a potentially useful/important 

endpoint in assessing the ecological risk of certain classes of endocrine-active chemicals. First, 

estrogens and androgens are known to play relatively specific roles in a variety of reproductive 

behaviors in fish, including competition for mates, courtship and nest-holding/guarding. 

Alterations in any of these behaviors theoretically could affect reproductive success and, hence, 

population status. In recognition of this there have been several recent papers describing straightforward, relatively quantitative assays for assessing the effects of endocrine-active substances on 

fish reproductive behavior. For example, Martinovic et al. (2007) conducted a study in which 

they showed that male fathead minnows exposed to a relatively low concentration of 17βestradiol, and subsequently placed in a competitive spawning situation with non-exposed males, 

failed to compete successfully for nesting sites/females. Similar types of results have been 

reported for other fish species exposed to steroidal estrogens (e.g., EE2; see Part II of this white 

paper), suggesting that behavioral alterations could be important to consider, especially if they 

occur at exposure concentrations below those that cause effects on more traditional endpoints 

such as development and egg production. 

Activational Endpoint: Secondary Sex Characteristics 

As described above, exposure of developing animals to endocrine-active chemicals can alter 

phenotypic sex, resulting in skewed sex ratios in populations. These organizational changes 

observed in secondary sex characteristics (in sexually dimorphic species) and/or gonads typically 

are not reversible. However, it also is possible to alter secondary sex characteristics, usually in a 

reversible manner, in sexually-mature fish through exposure to endocrine-active substances. For 

example, estrogens or anti-androgens can reduce expression of androgen-dependent secondary 

sex characteristics in males. Similarly, androgenic chemicals can cause female fish to develop 

male secondary sex characteristics, such as nuptial tubercles in the fathead minnow or elongated 

anal fins in the Japanese medaka (Seki et al. 2006). Alterations in secondary sex characteristics 

are much less useful indicators of endocrine-mediated responses in test species, such as 

zebrafish, with limited sexual dimorphism (Seki et al. 2006). 

Alterations in secondary sex characteristics in adult fish can, in some instances, be subtle and 

somewhat subjective with respect to interpretation. For example, reductions in the status of 

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existing structures in fish (such as nuptial tubercles in male fathead minnows or anal fin length in 

male medaka) can be difficult to quantify. However, when there is a de novo synthesis of 

structural characteristics where none previously existed (such as tubercles in female fathead 

minnows), the response is not only quite specific (in this case to an androgenic MOA), but very 

easy to detect (i.e., the baseline, control condition is zero). 

Although changes in secondary sex characteristics appear to be reasonable mechanistic 

biomarkers for some endocrine MOA, their utility as a predictor of adverse outcomes (e.g., egg 

production) is uncertain. Specifically, given our current understanding of fish reproductive 

physiology/endocrinology, causative links between secondary sex characteristics and gamete 

quality would be difficult to define. At best, a correlative association may be identified between 

the two parameters. For example, in studies with the synthetic androgenic steroid 17βtrenbolone, egg production appeared to be reduced at about the same test concentration that 

caused some degree of nuptial tubercle formation in females (Ankley et al. 2003). 

Activational Endpoint: Vitellogenin 

Vitellogenin status is probably the most commonly measured endpoint in studies with endocrineactive chemicals in fish. Measurement of the lipoprotein (or its mRNA) is relatively easy via a 

variety of methods (although most techniques have some degree of species specificity; Wheeler 

et al. 2005). Production of mRNA (vtg) and protein (VTG) in the liver of female oviparous (egglaying) vertebrates is normally stimulated by activation of the estrogen receptor by endogenous 

estradiol. The protein is released to the plasma and subsequently deposited in the ovary where it 

forms a key constituent of developing oocytes. VTG levels in male oviparous animals typically 

are non-detectable due largely to very low circulating estradiol concentrations; however, males 

retain the molecular “machinery” in the liver necessary to produce VTG. Hence, exposure to 

even relatively low amounts of exogenous estrogen or estrogen mimics can stimulate a marked 

induction of VTG in males. The response not only is specific and sensitive (in part due to a 

baseline of essentially zero), but relatively sustained after exposure, as the males have no 

mechanism whereby to clear the protein from their blood. 

Although vtg and/or VTG induction in male fish is an excellent biomarker of exposure to 

estrogens (Lattier et al. 2002), the response appears to have little direct (i.e., causative) value in 

terms of predicting adverse effects on reproduction (e.g., Wheeler et al. 2005). This perhaps 

should not be surprising given that VTG production in males is not part of any normal 

physiological pathway. It is possible, however, that correlative relationships between vtg and 

VTG induction in males by exogenous estrogens (such as EE2) and overall effects on fish 

population status could be derived (e.g., Kidd et al. 2007). This certainly merits additional study, 

but at present, it appears that the most technically-defensible use of VTG occurrence in male fish 

is as an indicator of exposure to estrogenic substances in the field and/or confirmation of 

chemical MOA in laboratory studies. 

As opposed to males, VTG has a clear physiological role in females in that the protein is 

essential to egg production. Concentrations of VTG in females can be reduced by endocrineactive chemicals that directly or indirectly inhibit steroid (ultimately estradiol) production. For 

example, aromatase inhibitors such as some conazole fungicides decrease steroid production by 

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inhibiting enzymes involved in steroidogenesis, while other androgenic chemicals like 

trenbolone decrease steroid production through feedback inhibition in the HPG axis. As a 

consequence, these classes of endocrine-active chemicals reduce normal VTG production in 

female fish, thereby reducing fecundity and, ultimately, affecting population status (Miller et al. 

2007). Therefore, in the case of females, VTG status may be effectively used as a biomarker both 

of exposure and effects. Kidd et al. (2007) found that VTG was elevated in female fathead 

minnows outside of their spawning season. Therefore, elevated VTG in females outside of the 

spawning season may also be an important measure of stress. 

3.3 Pathways and Receptors Beyond the HPG-Axis 

As was explained at the outset, this section (Section 3) has a substantial focus on the HPG-axis 

not because it is the only MOA that is of concern in this document, but because it is currently 

prominent in both social and scientific arenas. However, it is important to re-emphasize that the 

use of HPG-active chemicals as a basis for discussion does not imply that this is the only group 

of CECs of concern with respect to the development of ALC, or the only group for which there 

may be need for supplementation of the explicit procedures outlined in the Guidelines. 

As an example, the hypothalamic-pituitary-thyroid (HPT) axis is another endocrine system 

present in vertebrates that governs important biological pathways and is potentially subject to 

disruption. Similar to the role of steroid hormones in the HPG axis, actions of the HPT axis are 

mediated through thyroid hormone, which is involved in the regulation of metabolic activity, 

energy consumption and muscular activity in adult animals, and the regulation of postembryonic 

or perinatal growth and development in developing animals, especially in the central nervous 

system (Chatterjee and Tata 1992). Thyroid hormone is also responsible for the obligatory 

induction and maintenance of metamorphosis in amphibian and other poikilotherms, and may 

also play a role in male reproduction (Peterson et al. 1997). Since the actions of thyroid hormone 

are mediated via binding to highly-conserved nuclear thyroid hormone receptors and modulating 

transcription of specific genes, disruption of the HPT axis can be disrupted in many ways parallel 

to those discussed for the HPG axis (Farwell and Braverman 2006), and in doing so, create 

similar challenges for the development of ALC. Only a few of the developmental actions of 

thyroid hormones, however, are the result of the direct interaction of the hormone and receptor. 

Instead, most are indirect via the influence of thyroid hormone on other hormone or growth 

factors. For example, some of the growth-promoting effects of thyroid hormones on juveniles are 

indirectly mediated via growth hormone released from the pituitary gland (Chatterjee and Tata 

1992). 

The amphibian metamorphosis assay is one of the thyroid-relevant in vivo screening assays EPA 

has developed to detect chemicals that interfere with the thyroid hormone system. The assay 

represents a generalized vertebrate model to the extent that it is based on the conserved structure 

and functions of the thyroid systems, and thus mirrors some of the assays developed and 

discussed earlier for the HPG axis. This particular assay is important because amphibian 

metamorphosis provides a well-studied, thyroid-dependent process which responds to substances 

active within the HPT axis (Fort et al. 2007). The utility of this and other similar HPT-specific 

assays for development of ALC is predicated on the principle that the dramatic morphological 

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changes that occur during post-embryonic development of vertebrates are dependent on the 

normal function of the HPT axis, and that interference with this process leads to quantifiable 

effects (Zoeller and Tan 2007). 

Other pathways relevant to this discussion could include any of a number of those regulated by 

different nuclear hormone-type transcription factors, such as the progesterone, glucocorticoid 

and aryl hydrocarbon (Ah) receptors. Of these the Ah receptor is of particular interest because it 

has been well studied and is key to the toxicity of several important environmental contaminants 

such as dioxins and PCBs. Ah receptor agonists are extremely toxic to early life stages of some 

vertebrates species (e.g., adult fish are at least 10 times less sensitive than early life stages), can 

induce delayed mortality not captured in short-term (e.g., 96-hour) toxicity tests, and are not very 

toxic to invertebrates, which lack the receptor (Cook et al. 1993; Mount et al. 2003; Tanguay et 

al. 2005). Hence, as is true for HPG-active chemicals, knowledge that a contaminant may be an 

Ah receptor agonist can help focus testing to determine ecological risk (Cook et al. 1993). 

Although the previous systems are generally found in vertebrates but not invertebrates, parallel 

developmental, reproductive, and homeostatic systems exist in invertebrates (Lintelmann et al. 

2003) and are most likely just as susceptible to disruption by xenobiotic chemicals. In fact, many 

pesticides are designed explicitly to disrupt biochemical pathways specific to invertebrates or 

sub-groups of invertebrates as a means to reduce effects on non-target (vertebrate) organisms. 

Some endocrine-mediated processes unique to certain taxa of invertebrates include molting, limb 

generation, diapause, pheromone production, pigmentation and coloration, and metamorphosis. 

For these processes, the most important endocrine regulators in arthropods are ecdysone and 

related compounds (ecdysteroids), which are involved in embryonic development, molting, 

metomorphosis, reproduction, and pigmentation (Lintelmann et al. 2003). Juvenile hormones in 

insects and methylfarnesoate in crustaceans (both belonging to the class of sexual hormones 

called terpenoids) are also deemed necessary to mediate the regulatory functions of ecdysteroids 

(DeFur et al. 1999). Research on the effects of CECs on these systems is still in its early stages, 

but the parallels with other systems that are susceptible to disruption are clear, and may therefore 

create similar issues for the development of ALC. 

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4.0 SUMMARY AND RECOMMENDATIONS 

Through its deliberations, the workgroup concluded that the basic framework and conceptual 

underpinnings of the Guidelines apply to CECs as well as other chemicals. Further, the “Good 

Science” clause of the Guidelines provides the flexibility to adopt procedures that will produce a 

technically rigorous and protective criterion. The focus of this report has been the interpretation and 

adaptation of the principles set forth in the Guidelines with respect to common toxicological 

characteristics of CECs. In that regard, the workgroup identified a number of possible modifications 

or alternate interpretations that might aid those developing criteria for CECs to do so in a resource 

efficient manner that takes best advantage of existing knowledge. 

Although some of the recommendations involve increasing flexibility in meeting certain data 

requirements, the intent is to guide the generation of ALC for CECs that have the same technical 

rigor as 304(a) criteria developed for other chemicals; these are not methods for “short-cut” 

criteria. This is a significant point, because an important feature of the Guidelines is defining a 

minimum technical rigor that criteria must have; if insufficient information exists to achieve a 

minimum level of confidence in the calculated criterion, then criteria should not be derived. The 

important consequence of this for risk assessors and managers is that when criteria are used to 

make regulatory decisions, one can have confidence that uncertainty regarding the criterion is not 

excessive. In other words, criteria derived using the Guidelines are often used as both “walk 

away values” (i.e., there is high confidence that there is little or no risk when exposures are 

below criteria) and as indicators of risk (implying that effects are likely when criteria are 

exceeded). If greater uncertainty were allowed in criteria, then the ability to use the values in this 

way would be compromised. 

A negative aspect to establishing a minimum level of information for criteria is that there may be 

chemicals for which regulatory guidance is needed, but for which toxicological data are 

insufficient to meet the minimum standards of the Guidelines. In such cases, there may still be a 

need for alternate approaches to derive interim regulatory guidance values on which to base 

decisions that must be made before sufficient information for a complete water quality criterion 

can be gathered. While much of the discussion in this report might be useful to inform the 

development of such an approach, it must be emphasized that developing procedures to derive 

interim regulatory guidance values based on limited toxicity information is a separate matter and 

would require considerable additional analysis. 

The subsequent sections summarize the issues and recommendations of the workgroup according to 

the areas of concern identified above. 

4.1 Relevance of Acute Toxicity Effect Levels in Setting ALC for CECs 

Some CECs may not be acutely toxic, or may only be acutely toxic at environmentally irrelevant 

concentrations. Thus, if the minimum data requirements for acute toxicity data are not already 

met by existing data, conducting additional acute tests might be unwarranted. Indication of lack 

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of acute toxicity in key aquatic species might also warrant direct calculation of the CCC rather 

than using the FAV/FACR approach, and thus eliminate the need for the full suite of acute 

toxicity tests normally required. 

For a CEC of interest, available information should be reviewed to determine if the CMC would 

be sufficiently higher than the CCC such that developing the CMC is not needed. Exactly how 

much data is a risk management judgment, and probably does not have a unique answer. We 

recommend that the following information be considered when addressing this issue: 

• the amount and phylogenetic spread of acute toxicity data available; 

• toxicity data from short-term exposures that may not meet the strict definitions in the 

Guidelines of acute toxicity data acceptable for criteria derivation, but from which 

information on responses to acute exposures can be inferred; 

• data on short-term exposures garnered from longer-term exposures; 

• information from closely related chemicals thought to have the same MOA that have 

more robust acute data sets; and 

• knowledge of the degree of phylogenetic distribution of the toxicity pathway of concern. 

4.2 Defining Minimum Data Requirements in Terms of Taxonomic Coverage 

One consequence of dropping acute testing requirements in criteria derivation is the inability to 

calculate a CCC using the ACR approach, i.e., as the quotient of the FAV and FACR. In 

addition, for chemicals with large ACRs, it is likely that the mechanisms for acute and chronic 

toxicity differ (Welshons et al. 2003) and that the sensitivity of different taxa to acute and/or 

chronic toxicity varies widely. Both of these issues introduce uncertainty into the interpretation 

of ACRs, and probably make it inadvisable to use the FAV/FACR approach. Under such a 

circumstance, a prudent approach would generally be to develop a CCC directly from a 

sufficiently robust set of chronic data, using the procedures outlined in the Guidelines. If there is 

insufficient data from actual toxicity tests to fulfill the MDRs to develop a CCC directly from 

chronic toxicity data, a reasonable understanding of the toxicological MOA for the chemical may 

allow inferences as to what taxa (and endpoints) are most likely to be insensitive, such that 

measured chronic values for those taxa might not be needed. One important consideration in this 

process is to avoid an excessive number of taxa estimated to be insensitive, relative to those for 

which actual test results are available, and thus to distort the phylogenetic distribution from that 

implicit in the MDRs and typical of ALC. 

Accordingly, the workgroup recommends that, for chemicals without complete chronic toxicity 

data sets fulfilling all MDRs, there be an evaluation of whether sufficient information exists to 

conclude that certain taxa would not be sensitive to the chemical. Given the variation in 

understanding and availability of data likely to exist for different CECs, it is presumed that at 

least initial application of this approach would have to be justified on a chemical-by-chemical 

basis using appropriate scientific judgment. However, lines of evidence that might be applicable 

to this determination include: 

• an in depth understanding of the toxicological (or, in the case of drugs, therapeutic) 

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MOA; 

• information on the basic physiology of other taxa in relation to the MOA; 

• toxicity data from chronic exposures or other relevant experiments that do not meet the 

strict definitions of acceptable chronic data given in the Guidelines, but from which 

information on relative taxon sensitivity can be inferred; and 

• information from closely related chemicals thought to have the same MOA that have 

more robust acute or chronic data sets. 

4.3 Use of Non-Resident Species in ALC Development 

Historically, EPA has not used data derived from toxicity testing with non-resident species in the 

actual criteria derivation process. Excluding species simply because they are not resident may be 

unnecessarily restrictive for the purposes of deriving national criteria, and may actually increase 

rather than decrease uncertainty. Because ALC are intended to protect “most of the species, most 

of the time” and use distributions of test data for point estimation, increasing the species 

representation in the toxicological database should allow better estimation of species sensitivity 

distributions. 

The workgroup recommends that some non-resident species be considered for use in criteria 

derivation calculations, focusing on those species with widely used and standardized test 

methods and for which there is no reason to believe would misrepresent the sensitivity of 

comparable resident species. Furthermore, we specifically suggest accepting data for zebrafish 

(Danio rerio) and Japanese medaka (Oryzias latipes), to reflect international efforts toward data 

equivalency (Ankley and Johnson 2004). This recommendation pertains to the direct use of 

chronic toxicity data in the calculation of a CCC as is currently done for resident species. It is 

worth noting that even non-resident species that are not included in criteria calculations may still 

provide important information on MOA, sensitivity of endpoints, etc., as expanded on further 

below. 

4.4 Defining Appropriate Chronic Toxicity Data 

The Guidelines state that acceptable chronic tests for criteria derivation are full life-cycle 

exposures (egg/birth to egg/birth) for both vertebrates and invertebrates, as well as partial lifecycle (adult to juvenile) and early life-stage (ELS; egg to juvenile) tests for fish. For chemicals 

for which sexual development/maturation or reproductive effects are of most concern, the 

allowance in the Guidelines for using ELS or partial life-cycle fish tests might need 

reconsideration. The Guidelines already give priority to life-cycle tests when they are available 

and show greater sensitivity than other tests. However, other information indicating the 

importance of sexual development and reproduction (from other species, similar chemicals, 

knowledge of the MOA) might also establish a basis for not considering ELS data and for 

requiring life-cycle or partial life-cycle tests for fish. 

At present, a CCC could be derived for a chemical for which chronic toxicity data for fish are 

limited to ELS exposures. Because of the importance of sexual maturation and reproduction for 

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determining the chronic toxicity of chemicals like EDCs, the workgroup recommends 

strengthening the Guidelines such that the chronic toxicity data requirements require that either: 

1) Full life-cycle data be available for at least one fish species; or 

2) There is a body of experimental information indicating that life processes outside 

the ELS or partial life-cycle exposure/observation windows would not be 

important to capturing the important toxicological effects of the chemical. 

We note further that although this report is focused on CECs, this recommendation may be 

important to implement for all chemicals, not just CECs. 

Regarding the latter, we recognize that there may be circumstances where the information that 

shows the sensitivity of different life stages comes from studies that, while scientifically valid, 

for some reason do not meet all the requirements of a valid life-cycle test as defined in the 

Guidelines. Alternatively, there may be data from experiments that violate other requirements of 

acceptable toxicity tests under the Guidelines, but still provide insight into sensitive exposure 

periods or life processes. Even though chronic values from such data may not be used directly to 

calculate a CCC, it seems a reasonable use of such data to evaluate the question of where in the 

life-cycle there are important windows of exposure and/or effect, and how that impinges on 

criteria derivation. 

It may also be that meaningful chronic toxicity data could be developed from exposures that 

have a structure different from the life-cycle, partial life-cycle, and ELS protocols defined 

explicitly in the Guidelines; e.g., a short-term (21-day) reproduction assay with the fathead 

minnow (U.S. EPA 2001) or a multi-generational study – see example for EE2 reported in Nash 

et al. (2004). While defining such alternate protocols is beyond the scope of this document (see 

Ankley and Johnson 2004 for more detail), we recognize the potential for such a situation and 

leave it to appropriate implementation of the “Good Science” clause to allow for inclusion of 

such alternative test protocols as surrogates for chronic toxicity data, most likely in addition to, 

rather than instead of, data from life-cycle toxicity tests. 

4.5 Selection of Effect(s) Endpoints Upon Which to Base ALC 

Although chronic criteria typically are based on direct effects on reproduction, growth, and 

survival, there may be other endpoints indirectly related to these responses that could be useful 

for criteria derivation. The selection of endpoints appropriate to the derivation of ALC must be 

tied to the narrative intent of the overall Guidelines. The stated goal of ALC is to “protect aquatic 

organisms and their uses.” While the exact meaning of “protection” is not defined, there is 

considerable discussion in the Guidelines document that makes clear that protection does not 

mean the prevention of any measurable biological effect in any organism. Instead, there is 

discussion of endpoints that are “biologically important” and prevention of “unacceptable 

effects”; this implies that in the context of criteria there are effects that are “biologically 

unimportant” and/or levels of effect that are “acceptable.” 

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Chronic test data and other data should be examined to determine whether, for the specific 

chemical or MOA, endpoints beyond those traditionally used for criteria derivation may have 

intrinsic “biological importance” and therefore could be used as a basis for defining threshold of 

effect (e.g., sex ratio). Specifically, in the context of EDCs: 

• Other “endocrine-sensitive endpoints” (e.g., VTG, testis-ova) should be examined to 

determine whether they can be relied upon as definitive indicators of other biologically 

important endpoints (e.g., reproduction), with the idea that they may be incorporated into 

calculation of the criterion. Important sources of this information would include full lifecycle tests in which these other endpoints were measured alongside traditional chronic 

endpoints, and may include tests with other chemicals with the same MOA (e.g., E2 for 

EE2). 

• If endpoints, such as VTG or testis-ova, are used as direct or indirect indicators of effect, 

it is critically important that the baseline condition (e.g., variation during normal 

development) be understood sufficiently to define when changes are biologically 

meaningful. 

• Selection of appropriate endpoints (and their associated effect thresholds) may, in some 

instances, transcend “biological importance” (the focus of the Guidelines) to reflect 

societal concerns (e.g., physical appearance of wild-caught fish). 

4.6 Involvement of an Expert Panel 

As becomes clear from the preceding issues, development of appropriate criteria for CECs may 

be unusually dependent on technical interpretations of a wide range of toxicological information 

pertinent to specific chemicals. One of the recommendations from a SETAC Pellston workshop 

(Mount et al. 2003), consistent with much of the above, was that expert panels be used to provide 

professional judgment during stages of the problem formulation and data interpretation 

associated with criteria development, particularly for chemicals with specific MOA. The 

involvement of the panel would “ensure consideration of other existing data for the chemical of 

concern, enable a significant degree of up-front technical input, and provide a level of peer 

review that should facilitate wider and more ready acceptance of the recommended criteria.” The 

workgroup agrees with this recommendation and suggests that it be incorporated into criteria 

development of CECs. 

To maximize effectiveness, this panel should be convened very early in the criteria development 

process such that it will be able to assist in problem formulation, identification of important data, 

and scoping of particular issues that will be important. We envision these panels as being formed 

around specific chemicals, or groups of chemicals with a similar MOA, in order to access the 

most specialized expertise available. 

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WHITE PAPER 

AQUATIC LIFE CRITERIA FOR CONTAMINANTS OF 

EMERGING CONCERN 

PART II 

 

ILLUSTRATION OF RECOMMENDATIONS USING DATA FOR 

17α-ETHYNYLESTRADIOL (EE2) 

Prepared by the 

OW/ORD Emerging Contaminants Workgroup 

June 03, 2008 

NOTICE 

THIS DOCUMENT IS AN INTERNAL PLANNING DOCUMENT 

It has been prepared for the purpose of Research & Development Planning. 

It has not been formally released by the U.S. Environmental Protection Agency and should 

not at this stage be construed to represent Agency guidance or policy. 

DRAFT DOCUMENT
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TABLE OF CONTENTS 

1.0 INTRODUCTION .................................................................................................................4 

2.0 DESCRIPTION OF THE ACUTE AND CHRONIC TOXICITY DATA SUMMARIZED 

FOR EE2................................................................................................................................6 

3.0 EE2 DATA EVALUATION AND CONSIDERATIONS FOR ALC DEVELOPMENT....7 

3.1 RELEVANCE OF ACUTE TOXICITY EFFECT LEVELS IN SETTING ALC FOR 

EDCS.................................................................................................................................7 

3.2 USE OF NON-RESIDENT SPECIES IN ALC DEVELOPMENT ..................................8 

3.3 MINIMUM DATA REQUIREMENTS REGARDING TAXONOMIC COVERAGE....9 

3.4 DEFINING APPROPRIATE CHRONIC TOXICITY DATA..........................................12 

3.5 SELECTION OF EFFECT(S) ENDPOINTS UPON WHICH TO BASE ALC ...............15 

4.0 REFERENCES ......................................................................................................................17 

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TABLE OF TABLES 

Table 3.1. Potential GMAVs for Application to EE2 CMC. ............................................................7 

Table 3.2. Potential Chronic Values for Application to EE2 CCC...................................................11 

Table A.1. Effects of EE2 on Aquatic Animals (Short-term survival).............................................28 

Table A.2. Effects of EE2 on Aquatic Animals (Long-term survival). ............................................29 

Table A.3. Effects of EE2 on Aquatic Animals (Growth)................................................................31 

Table A.4. Chronic Reproductive Effects of EE2 on Aquatic Animals (Fecundity, Fertility, and 

Population Growth). .......................................................................................................33 

Table A.5. Chronic Reproductive Effects of EE2 on Aquatic Animals (Sex Reversal)...................35 

Table A.6. Chronic Reproductive Effects of EE2 on Aquatic Animals (Intersex)...........................37 

Table A.7. Chronic Reproductive Effects of EE2 on Aquatic Animals (Sexual Behavior). ............39 

Table A.8. Data on Effects of EE2 on Aquatic Animals (Secondary Sexual Characterstics). .........40 

Table A.9. Chronic Reproductive Effects of EE2 on Aquatic Animals (Vitellogenin)....................42 

Table A.10. Chronic Effects of EE2 on Aquatic Animals (Other Relevant Endpoints)...................44 

LIST OF APPENDICES 

APPENDIX A....................................................................................................................................27 

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1.0 INTRODUCTION

In Part I of this white paper, toxicological characteristics of some contaminants of emerging 

concern (CECs) important to the derivation of ambient water quality criteria for aquatic life 

(aquatic life criteria, ALC) were described, and recommendations were made to facilitate ALC 

derivation for these chemicals. In Part II of this white paper, toxicity data for a model CEC, 17αethynylestradiol (EE2), are used to further illustrate and explore those recommendations. 

Ethynylestradiol was chosen as a model compound for a several reasons. First, it possesses many 

of the toxicological characteristics described in Part I, and sufficient toxicity data exist to allow 

evaluation of the principles underlying the Part I recommendations. Second, toxicological 

effects of EE2 have been found both in the laboratory, the source of toxicological data for 

criteria development, and in the field, where criteria are used to enforce the regulatory authorities 

of the Clean Water Act. Finally, there is interest in deriving an EE2 ALC, and using EE2 as a 

basis for discussion should help advance that goal. While acknowledging that interest, it is 

important to note that the data and discussion presented are not intended to represent the 

formulation of an actual ALC, and potential ALC concentrations should not be inferred. The 

information from the ecotoxicological literature used here is for illustrative purposes and should 

not be considered as comprehensive, nor have all the data been fully examined for quality and 

applicability to ALC development. 

The synthetic estrogenic steroid EE2 is the active pharmacological component of most oral 

contraceptives, and acts as a potent estrogen receptor agonist in vertebrates. After use and 

excretion of the contraceptive, domestic sewage treatment plant (STP) effluents become the 

primary source of EE2 entering the aquatic environment (Damstra 2002). Kolpin et al. (2002) 

found EE2 in 5.7% of 139 streams monitored in the U.S. While the concentrations of EE2 in 

Kolpin et al. (2002) have been debated (Ericson et al. 2002; Till 2003), other studies have noted 

concentrations ranging from 0.1 – 5.1 ng/L in surface waters (as reviewed by Campbell et al. 

2006). Overall, it is somewhat uncertain at this time how high environmental concentrations of 

EE2 may be. Reliable analytical methods for the detection of EE2 have not been in existence 

very long, nor have they been widely validated in independent multi-laboratory studies. Some 

modeling efforts by the pharmaceutical industry indicate that based on the level of production 

and use of EE2 in the U.S., concentrations found in effluents should be less than 1 ng/L 

(Anderson, P.D. and D'Aco, V, personal communication, 2008). Complicating assessment of 

the possible risk of EE2 is the fact it co-occurs in STP effluents with the natural steroid 

hormones estradiol and estrone, though EE2 is generally found at lower concentrations. These 

three estrogens reportedly account for the majority of the estrogenic activity present in domestic 

wastewater effluents (Desbrow et al. 1998; Snyder et al. 2001), but EE2 is the most potent and 

resistant to degradation of the three (Nash et al. 2004; Gross-Sorokin et al. 2006). Data collected 

from fish and surface waters downstream of STPs over the past decade have implicated steroidal 

estrogens as the primary constituents in domestic effluents leading to the occurrence of intersex 

fish (Gross-Sorokin et al. 2006). 

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The remainder of this part of the white paper consists of a brief description of some relevant 

acute and chronic toxicity data available for EE2 (Section 2) and the evaluation of these data 

with respect to the recommendations made in Part I (Section 3). 

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2.0 DESCRIPTION OF THE ACUTE AND CHRONIC TOXICITY DATA 

SUMMARIZED FOR EE2 

Acute and chronic toxicity data were identified via a literature search and review of relevant 

articles from EPA’s ECOTOX database in April 2007. This list of potentially useful articles was 

supplemented with a few additional reports and articles as they became published or available. 

Only those studies with EE2 effect data on individual aquatic organisms or their populations 

were retained. For this particular effort, all endpoints expressing effects of EE2 at the whole 

animal and cellular levels were initially considered. Because the EE2 dataset is relatively large, 

and because many studies report more than one endpoint of possible consideration for ALC 

development, the data have been broadly summarized in an appendix (Appendix A). The tables 

comprising Appendix A are organized by endpoint, and include separate tables for endpoints 

typically used to derive ALC (survival, growth and reproduction) as well as for other endpoints 

relevant to the estrogenic mode of action of EE2. Table A.1 contains the data available on the 

acute (lethal) toxicity of EE2 to aquatic animals. This table is followed by others containing the 

chronic (long-term) effects of EE2 on survival (Table A.2) and growth of aquatic animals (Table 

A.3). Tables A.4 through A.9 present data directly (fecundity, fertility) or indirectly (sex 

reversal, intersex, sexual behavior, vitellogenin) related to the effects of EE2 on reproduction. 

Finally, Table A.10 presents a summary of the significant effects of EE2 on aquatic animals 

based on other potentially relevant endpoints. In vitro effects were not considered in the data 

analysis. 

Within each table in Appendix A, data are first separated by studies where significant effects 

were observed, and then by studies where significant effects were not observed (i.e., where no 

effect was observed at the highest concentration tested). Each table in the appendix combines 

data for aquatic vertebrates and invertebrates for both freshwater and saltwater species, the latter 

designated by asterisks. All tables are organized by increasing effect concentrations, and all 

chronic effect endpoints are as reported by the authors. 

Many studies of the effects of EE2 on aquatic organisms did not use standard toxicity test 

protocols, particularly those measuring sublethal responses. This is probably due in part to these 

studies having been designed for purposes other than ALC development, such as exploration of 

toxicity mechanisms, identification of sensitivity windows, bioassay development, etc. Adequate 

quantification of effect concentrations is also difficult for some of these studies because of the 

use of widely spaced treatment concentrations and by problems with analytical detection of 

exposure concentrations near the threshold for reproductive effects. While the results from such 

studies might limit their use in ALC development according to the definitions in the Guidelines, 

they were included in this document because they may inform other aspects of criteria 

derivation, as explained in general terms in Part I and in detail in the sections that follow. 

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3.0 EE2 DATA EVALUATION AND CONSIDERATIONS FOR ALC DEVELOPMENT 

This section considers the application of the data in Appendix A toward criteria derivation in the 

context of the several areas of concern and general recommendations identified in Part I of this 

white paper. 

3.1 RELEVANCE OF ACUTE TOXICITY EFFECT LEVELS IN SETTING ALC FOR 

EDCS 

One of the recommendations from Part I of this document was to determine whether the acute 

sensitivities of aquatic organisms to a chemical of interest are sufficient, relative to chronic 

sensitivity and expected exposures, to warrant derivation of a criterion maximum concentration 

(CMC) under the Guidelines procedures. This is especially important if there is not sufficient 

acute toxicity data to meet the minimum data requirements of the Guidelines, in order to avoid 

wasting resources on unnecessary additional testing. EE2 provides a good example of a 

chemical having insufficient acute toxicity data to derive a CMC according to Guidelines

procedures, but enough data to demonstrate that deriving a CMC is not necessary. 

Table 3.1 provides information on GMAVs that might be considered in CMC derivation. These 

values were derived from Table A.1 for any tests meeting Guidelines requirements, including 

"greater than" values indicative of the highest tested concentration eliciting less than 50% 

mortality. For genera without such acceptable tests, EC50/LC50s from Table A.1 for tests of 24 

h duration and from Table A.2 for tests up to 30 days were also used. The EC50/LC50 values for 

these longer tests are designated as "greater than" values to indicate the expectation that acute 

EC50/LC50s would be higher. Values for medaka and zebrafish are included in accordance with 

the recommendation from Part I of this document that some latitude be adopted regarding species 

not resident to North America. Acute tests with embryos, not usually included in CMC 

calculations, are also included here because they suggest greater sensitivity of this life stage. 

Table 3.1. Potential GMAVs for Application to EE2 CMC.

Genus GMAV (ng/L) Comments 

Freshwater 

Rana >760,000 14-d test 

Gammarus >840,000 10-d test 

Medaka >1,000,000 

Danio 1,700,000 

Ceriodaphnia 1,800,000 

Hydra 3,800,000 

Sida >4,100,000 24-h test 

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Genus GMAV (ng/L) Comments 

Daphnia >5,000,000 

Chironomus 9,100,000 24-h test 

Saltwater 

Lytechinus 30,000 Embryo 

Strongylocentrotus 30,000 Embryo 

Acartia 88,000 Embryo 

Tisbe >100,000 21-d test 

Acartia 1,100,000 

Neomysis 1,200,000 

The data summarized in Table 3.1 show several deficiencies in meeting the minimum data 

requirements for deriving a CMC under the Guidelines. For freshwater application, only four 

genera, rather than the minimum of eight, meet the acute test requirements, even if the 

prohibition for non-resident species is ignored. If the shorter and longer tests are included, the 

requirement of at least eight genera is met, but the requirement for a salmonid fish is not. Even 

if this requirement is also ignored, two of the lowest four genera are "greater than" values, 

whereas CMC calculations can only be made if the four most sensitive genera have definite 

values ("greater than" values are permitted only for more tolerant genera.) For saltwater, there 

are even greater deficiencies in meeting the minimum data requirements. 

Although these data are insufficient for deriving CMCs, they do provide ample evidence that a 

CMC is not needed and that it is unnecessary to conduct further tests to meet the minimum data 

requirements. For freshwater, there is still a rather broad taxonomic representation, including 

three vertebrates from two different classes, four crustaceans from two orders, and a third 

phylum. The acute LC50s/EC50s are consistently near and above 1 mg/L, several orders of 

magnitude above both the most sensitive chronic endpoints (Tables A.4 – A.9) and the highest 

environmental concentrations that organisms might be exposed to. The saltwater data do show 

greater sensitivity for the embryonic stages of some genera, but whether this reflects a lifestage 

or taxa sensitivity issue, these LC50s/EC50s are still four orders of magnitude above the most 

sensitive chronic endpoints and environmentally-relevant exposures. 

3.2 USE OF NON-RESIDENT SPECIES IN ALC DEVELOPMENT 

Under the Guidelines, toxicity values from aquatic species not resident to the contiguous 48 

United States, Alaska, or Canada are excluded from ALC derivation. One of the 

recommendations in Part I of this white paper is that this prohibition be relaxed and that data for 

non-resident species be allowed where deemed suitable, especially for species such as medaka 

and zebrafish which have become standard test organisms commonly used worldwide. Any 

tested species, whether resident or not, serves as a surrogate for estimating a sensitivity 

DRAFT DOCUMENT
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distribution relevant to assessing risks in a variety of aquatic communities with a multitude of 

untested species. Therefore, the issue here is whether a non-resident species can serve as a 

reasonable surrogate for assessing the sensitivity of untested resident species. The use of such 

species would still be contraindicated if there is reason to believe they are significantly more or 

less sensitive than resident species. 

The data in Appendix A support the use of medaka and zebrafish data in criteria calculations. 

Although there are no resident fish species with which to compare the acute sensitivities of 

medaka and zebrafish (see Table 3.1 and Table A.1), their lack of acute sensitivity is consistent 

with that of resident amphibians and invertebrates in the available data. The sensitivities of these 

fish species for long-term survival (Table A.2), growth (Table A.3), and reproduction (Table 

A.4) are interspersed with those of resident fish species, so there is no indication of either 

substantially higher tolerance or sensitivity to contraindicate their use. This is also generally true 

of the other endpoints summarized in Appendix A. The similarity among fish species of 

different geographic origins is not surprising, since the MOA of EE2 involves receptors and 

pathways that are highly conserved among vertebrates. If similar trends are seen in the data once 

they are thoroughly examined for quality and applicability to ALC development, data from these 

non-resident species should be included in criteria development. 

The data in Appendix A also underscore pragmatic advantages of including non-resident species 

in criteria development. Medaka and zebrafish provided a large fraction of the available data 

regarding EE2 effects on fish. Removing them from the dataset simply because they are not 

resident would limit information on the distribution of species sensitivity and may actually 

increase rather than decrease uncertainty regarding resident species. Another use of data from 

non-resident species could be to assist in extrapolations of information across species, chemicals, 

and endpoints. For example, life-cycle tests with medaka could be used to evaluate whether 

early life-stage or partial life-cycle tests with resident species should or should not be accepted in 

criteria calculations for specific classes of chemicals with a defined MOA. The relationship of 

reproductive effects in non-resident fish (Table A.4) to other endpoints (Tables A.5-A.9) could 

also be used to determine how to apply information on these other endpoints for resident species 

lacking direct toxicological information on reproduction. 

3.3 MINIMUM DATA REQUIREMENTS REGARDING TAXONOMIC COVERAGE 

As discussed in section 3.1, deriving a CMC for EE2 is not useful because acutely-toxic 

concentrations are so much higher than both chronic effects concentrations and expected 

environmental concentrations. In addition, developing a CMC would require additional acute 

toxicity tests to meet the minimum data requirements (MDRs) specified in the Guidelines. 

Without a CMC, the criterion continuous concentration (CCC) must be calculated directly from 

the available data, rather than through extrapolation using an acute to chronic ratio (ACR); this is 

probably not advisable anyway for such large ACRs. Since the ACR method is moot, the 

Guidelines calculation procedures for the CCC require that there be sufficient chronic toxicity 

tests to satisfy the MDRs for estimating the fifth percentile of the chronic database. For 

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freshwater criteria, these MDRs include a species from: the family Salmonidae; a species from a 

second family in the class Osteichthyes; a species from a third family in the phylum Chordata; a 

planktonic species from the Class Crustacea; a benthic species from the Class Crustacean; a 

species from the Class Insecta; a species from a phylum other than Chordata or Arthropoda; and 

a species from an order of insects or a phylum not otherwise represented. 

Few existing ALC have chronic data that meet the MDRs, and this will likely be true of CECs as 

well. Significant expense would be incurred conducting new chronic tests to satisfy all the 

requirements. As recommended in Part I of this white paper, because only the four most 

sensitive genus mean chronic values (GMCVs) are used in the criteria 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. A 

value (or values) for this taxon would still be included in the data set, but its GMCV would 

simply be specified to be greater than the fourth lowest GMCV. 

Table 3.2 lists chronic values for the toxicity of EE2 to various freshwater genera to illustrate 

data that might be included in freshwater criteria calculations. These chronic values were 

obtained from Tables A.2-A.4, using Guidelines data selection procedures where possible, but 

also included some additional data to support discussion of how certain data deficiencies might 

be addressed. For invertebrates, the Guidelines require life-cycle tests that include reproductive 

endpoints, but if that type of test was not available, then other tests are reported here, with their 

limitations noted. For fish, the Guidelines preference order of life-cycle, partial life-cycle, and 

early life stage (ELS) was followed, but other tests were also reported as needed for illustrative 

purposes, with their limitations also noted. For all genera, the most sensitive endpoint among 

chronic survival, growth, and reproduction was selected, which was from the reproduction data 

of Table A.4, except for Chironomus (for which development from egg to pre-emergence was 

tested and the effects concentration was from Table A.3). Each chronic value (CV) was 

calculated as the geometric mean of the reported no observed and lowest observed effect 

concentrations (NOEC and LOEC) for an adverse effect. When the LOEC was the lowest 

exposure concentration, a "less-than" concentration is reported for the CV and, when the NOEC 

was the higher exposure concentration for insensitive species, a "greater-than" concentration is 

reported. As explained in Sections 1 and 2, these data are still under review and subject to 

modification. The specific values here should not be misconstrued as final, but rather as 

examples to illustrate trends and indicate needs that support the recommendations being 

addressed here. 

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Table 3.2. Potential Chronic Values for Application to EE2 CCC. 

Genus CV(s) (ng/L) Notes 

Danio 0.6, 1.5, <1.1 Life-cycle tests; for 1.5 ng/L CV, there was a 9-fold 

difference between LOEC and NOEC and the LOEC 

was a 100% effect 

Pimephales <0.32, 1.5 Life-cycle tests; for <0.32 ng/L CV, LOEC showed 

reduced fertilization but increased egg production so 

total reproduction not adversely affected; for 1.5 CV, 

4-fold difference between NOEC and LOEC 

Oryzias 3.2 F0 from 1 d through spawning; 10-fold difference 

between NOEC and LOEC 

Oncorhynchus <16 Adult exposure only; fertilization success only 

endpoint examined 

Potamopyrgus 50 Adult exposure only; embryo production over 9 wk 

test 

Gammarus >7,600 Population size over 100 d test; increased population 

size at 760 and 7,600 ng/L 

Daphnia 45,000 5-fold difference between NOEC and LOEC 

Tisbe >100,000 Saltwater copepod included to further indicate 

arthropod insensitivity 

Chironomus 320,000 Larval growth and molting schedule only; did not 

include emergence and reproduction 

Brachionus 800,000 Intrinsic rate of population increase over 72 hr test 

The data in Table 3.2 indicate high sensitivity of vertebrates to EE2. Significant reproductive 

effects in the life-cycle tests for zebrafish (Danio rerio) and fathead minnow (Pimephales 

promelas) occur at concentrations near and perhaps below 1 ng/L. Although the chronic test for 

medaka (Oryzias latipes) did not cover the entire life cycle, it included life stages likely 

important for reproduction and indicated a sensitivity similar to zebrafish and fathead minnow. 

For rainbow trout (Oncorhynchus mykiss), a more limited exposure addressing only effects on 

fertilization suggests that reproductive effects on this species should also be present in the low 

ng/L range. However, the absence of a definite toxicity value for rainbow trout will be an 

important impediment to criteria calculations, both for leaving an MDR unsatisfied and for being 

one of the four most sensitive genera in this set. Actual criteria development will require a 

decision whether to (a) require more information for this species, (b) use other information to 

help estimate rainbow trout sensitivity or (c) justify setting the MDR aside (see Section 3.5). 

The invertebrate data in Table 3.2 indicate lower sensitivity, especially for arthropods 

(Gammarus, Daphnia, Tisbe, Chironomus) and rotifers (Brachionus). Some data, like the 

Chironomus test, fail to satisfy the Guidelines requirement for a life-cycle test and the copepod 

Tisbe is a saltwater species included here only to reinforce conclusions about arthropod 

sensitivity. Also, the tests for Gammarus and Brachionus are not standard life-cycle tests, but 

could be considered to satisfy Guidelines requirements because exposures span a life cycle and 

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include reproductive effects. The snail (Potamopyrgus) toxicity test showed moderate 

sensitivity, although still about an order of magnitude less than the fish, and also does not 

involve a full life-cycle test. 

These data demonstrate the potential for a situation in which the GMCVs for taxa reasonably 

expected to be insensitive do not need to be quantified. For example, although the Chironomus

test was not a full life-cycle test and thus could not fully define the GMCV under Guidelines

requirements, it indicates such a degree of insensitivity for growth and development, such that it 

can be reasonably presumed that a full life-cycle test would still show much less sensitivity than 

the vertebrates, especially because other arthropods are observed to be similarly insensitive. 

Likewise, the snail test, although not for a full life-cycle, involved the effects of long exposures 

on reproduction, and can be argued to be sufficiently less sensitive than fish reproduction so that 

it would not reasonably be expected to be among the four most sensitive genera if a life cycle test 

was conducted. These inclusions, along with the data for Daphnia, Gammarus, and Brachionus, 

satisfy the Guidelines MDRs for invertebrates, and would allow an ALC to be calculated from 

the four sensitive vertebrate genera, provided the value for the rainbow trout was resolved. 

Assessing that taxa are likely to be insensitive could involve other lines of evidence, especially 

for CECs with more limited chronic toxicity data than EE2. Tests involving endpoints such as 

those in Tables A.5-A.10 could be used to establish that certain taxa are sufficiently less 

sensitive than others to preclude the need for tests on their chronic survival, growth, and 

reproduction (Tables A.2-A.4), the endpoints typically used in ALC development. Information 

from other chemicals might also be used, such as using the insensitivity of arthropods to EE2 to 

preclude testing this taxonomic class with chemicals with the same MOA. Such a strategy could 

be used to help the evaluation of EE2, particularly regarding the snail sensitivity. For example, 

the sensitivity of this or similar species relative to that of vertebrates for other chemicals could be 

used to strenghten a conclusion that they are less sensitive to EE2 than are fish. 

3.4 DEFINING APPROPRIATE CHRONIC TOXICITY DATA 

As discussed in Part I of this white paper, characteristics of some CECs require that careful 

consideration be given to the selection of chronic toxicity data appropriate for ALC 

development. Specifically, the use of data from early-life stage (ELS) or partial-life cycle (PLC) 

exposures as estimates of life-cycle chronic effect thresholds is inadvisable for chemicals whose 

MOA would result in biological effects for which critical periods of induction and/or expression 

would lie outside the exposure/observation window provided by the test procedure. 

An examination of data specifically for EE2 provides evidence to support emphasis on full lifecycle exposures for determining the chronic toxicity of EE2. Länge et al. (2001) conducted a full 

life-cycle chronic exposure with fathead minnows which were exposed from fertilized eggs (F0) 

through maturation, spawning, and early-life stage development of the F1 generation. Nominal 

exposure concentrations of EE2 were 0.2, 1, 4, 16, and 64 ng/L (for convenience, nominal 

concentrations are used in this discussion as the important point is relative endpoint sensitivity 

DRAFT DOCUMENT
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rather than absolute concentrations inducing effects). As part of this exposure, measurements of 

growth (as length) and survival were made at 28 days post hatch (dph) which would correspond 

to the end of a standard ELS exposure with fathead minnows. At 28 dph, there were no effects 

on survival. The length endpoint showed a 16% reduction at 64 ng/L, a smaller but significant 

reduction of 6% at 16 ng/L, and no effect at 4 ng/L. Accordingly, the NOEC and LOEC for an 

ELS test with EE2 would have been 4 and 16 ng/L, respectively, and an EC20 based on length 

would be >64 ng/L. However, as exposure continued throughout the life cycle, pronounced 

effects were observed for other endpoints at lower exposures. There was no reproduction at all 

in fish exposed to 4 ng/L, and a trend, though not significant, toward lower reproduction at 0.2 

and 1 ng/L. Other significant effects observed included a 16% reduction in weight of adult 

female fish at 1 ng/L after 301 d exposure, and 5 to 10 percent reductions in weight of F1

offspring at 28 dph, though the authors questioned the biological significance of the F1 growth 

effects. Regardless, the clear indication is that life-cycle exposure showed substantially greater 

sensitivity to EE2 than was evidenced from ELS endpoints alone. This was much larger than the 

factor of 2 difference generally found for other chemicals by McKim et al. (1978). 

A similar conclusion can be drawn from the study of Parrott and Blunt (2005). This involved 

exposure from fertilized egg through reproduction, including measures of fertilization success 

(but not ELS development) in the F1 generation. Exposure was to nominal concentrations of 

0.32, 0.96, 3.2, 9.6, and 32 ng/L EE2. Measurements of survival and growth at 30 dph showed 

no effects (NOEC ≥ 32 ng/L). However, continuation of exposure through adulthood showed no 

reproduction in the 3.2, 9.6 and 32 ng EE2/L treatments, and all fish in these treatments were 

phenotypic females. There was also suggestion of effects on fertilization success at 0.32 and 

0.96 ng/L, although interpretation of these effects is complicated by an increase in number of 

eggs produced in these same treatments, such that the total number of fertilized eggs was not as 

dramatically affected. Regardless, the message relative to definition of chronic sensitivity is the 

same in that effects were apparent after life-cycle exposure at concentrations well below those 

that would be expected to show effects in an ELS test. 

Additional comparisons can be extracted from the work of Wenzel et al. (2001), who conducted 

a multi-generational study of zebrafish exposed to EE2 concentrations from 0.05 to 10 ng EE2/L. 

Observations of survival and length of exposed fish showed no effects at 21 and 42 dph (NOEC 

≥10 ng/L). However, with continued exposure, a variety of effects were observed around an EE2 

test concentration of 1 ng/L, including effects on adult length, time to spawning, egg production 

and fertilization. As for the fathead minnow studies, survival and growth measured during the 

period comparable to an ELS study were far less sensitive to EE2 exposure than were endpoints 

measured in full life-cycle studies (Tables A.2, A.3, A.4). 

The reason for these differences between ELS and full life-cycle tests is obvious when one 

considers the MOA for EE2, which interferes with sexual differentiation, development, 

maturation, and spawning. Because the endpoints measured in ELS tests are limited to survival 

and growth, and because the effects of EE2 on sexual differentiation are not apparent (at least not 

at a gross morphological level) in the tested species by 28-30 dph, the ELS test is comparatively 

insensitive to toxicity mediated through an estrogen receptor signaling pathway. It is interesting 

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to note that even though a standard ELS test is relatively insensitive to detecting the effects of 

EE2 exposure, other work has shown that key windows of exposure do in fact occur during the 

ELS exposure window. Van Aerle et al (2002) demonstrated that larval fathead minnows 

exposed to EE2 only during brief windows during early development (e.g., 10-15 dph) showed 

altered sexual development of male fish at 100 dph, including the development of an ovarian-like 

cavity and changes in the distribution of testicular cell types (Table A.6). The issue for 

interpreting chronic toxicity data is that, even though effects may be induced during ELS 

exposure, they are not expressed unless exposed fish are observed later in sexual development. 

This latter observation also has implications for the suitability of PLC tests for detecting the 

effects of EE2 or other chemicals acting through a similar pathway. As discussed in the 

Guidelines, PLC tests are acceptable chronic tests for fish species that require more than one year 

to reach sexual maturity, such as the common species of trout. PLC tests are to begin exposure 

“with immature juveniles at least 2 months prior to active gonad development, continue through 

maturation and reproduction, and end not less than 24 days (90 days for salmonids) after the 

hatching of the next generation.” If salmonids (or other species for which PLC tests might be 

conducted) were to express effects from larval exposure to EE2 as observed by Van Aerle et al. 

(2002) for fathead minnows, one would expect that a PLC exposure would not be as sensitive as 

a full life-cycle exposure. That is, even though a PLC test includes the observation periods 

shown to be sensitive in full life-cycle exposures, it might not include the exposure windows 

important to inducing chronic effects on sexual differentiation and development. 

While the rationale for emphasizing full life-cycle chronic tests has clear grounding in the MOA 

for EE2, it has practical implications in terms of the fish species likely to be tested. Most species 

for which life-cycle chronic tests are most commonly conducted (primarily fathead minnow, 

zebrafish, medaka, flagfish, and sheepshead minnow), are small fish that develop rapidly and are 

continuous spawners (as opposed to annual spawners like rainbow trout or bluegill sunfish). 

Whether or not these life history traits influence sensitivity to EE2 is unknown, but because of 

the investment necessary to conduct true life-cycle exposures with annually spawning fish that 

take much longer to develop, it may be unlikely that comparative data will be developed. Better 

understanding these implications is a worthy subject for future research. 

Finally, there are some scattered indications in the literature for trans-generational effects of EE2 

exposure. As mentioned above, Länge et al. (2001) found small effects on growth in the F1 

generation that were not observed after comparable exposure of the F0. Wenzel et al. (2002) also 

report some suggestions of growth inhibition in subsequent generations at exposure below those 

causing such effects in the first exposed generation (Table A.3). The mechanisms by which such 

effects might occur are not clear, nor are their implications (in fact, Länge et al. actively dismiss 

them as being biologically unimportant). At this point, it does not seem that the evidence for 

trans-generational effects is sufficient for requiring their inclusion in the definition of an 

acceptable chronic test, but the potential for the existence and importance of trans-generational 

effects should be re-evaluated in the future as additional data become available. 

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3.5 SELECTION OF EFFECT(S) ENDPOINTS UPON WHICH TO BASE ALC 

Aquatic studies with EE2, particularly those using fish, have measured a variety of endpoints not 

traditionally used for criteria derivation, including reproductive behavior, abnormal sex ratios, 

changes in secondary sexual characteristics, altered histopathology (typically gonadal), changes 

in steroid hormones, and modifications in the expression (or activity) of a variety of 

proteins/enzymes. Many of these endpoints were evaluated because they are known (or 

hypothesized) to be responsive to estrogenic MOA, and not because the intended result was the 

quantitative assessment of risk. Among the challenges in using data from these types of 

mechanism-based endpoints is that such measurements are seldom standardized or 

straightforward in their interpretation. For example, alterations in behavior are difficult to 

objectively quantify, it is challenging to accurately measure steroid hormone concentrations in 

small fish, and the capability of measuring gene expression or enzyme activity can be quite 

lab/method-specific. A second source of uncertainty in using most of the mechanism-specific 

endpoints evaluated in EE2 studies is a lack of knowledge concerning the functional relationship 

between changes in endpoints and responses of primary concern for risk assessment, such as 

survival, growth and reproduction. Even in considering these challenges related to measurement 

and interpretation, however, there are a handful of mechanistic endpoints/responses that exhibit 

utility for supporting ALC derivation for EE2 (or other xenobiotic compounds with estrogenic 

activity). Three of these are discussed in greater detail below. 

A frequently measured mechanism-specific endpoint in fish exposed to EE2, is induction of 

vitellogenin mRNA (vtg) or expression of circulating vitellogenin protein (VTG) in males (Table 

A.9). The most attractive attribute of this endpoint is its specificity for an estrogenic MOA, 

since there are no other chemically linked biological phenomena known to consistently activate 

the vitellogenin gene or elevate vitellogenin protein in male fish. Further, since the vitellogenin 

gene is quiescent in male fish, which implies a zero baseline of vitellogenin, the response is 

unambiguous with regard to exposure. Additionally, this exposure mediated induction of vtg is 

sensitive to low levels of exogenous estrogen. Because vitellogenin protein has been frequently 

evaluated in fish studies, accurate methods of measurement (including several commercial kits) 

are available for many fish species, including the small fish models for which much of the EE2 

chronic toxicity data exist. Given these attributes, male VTG has and should continue to be a 

very useful endpoint for monitoring the occurrence of estrogenic chemicals (including EE2) in 

the environment. A major drawback to using male-specific circulating protein to assess exposure 

and risk of EE2 (or other estrogens), including the derivation of ALC, is the lack of an 

established functional linkage between expression of the protein and adverse endpoints related to 

early development or reproduction (Wheeler et al. 2005). This is in large part due to the fact that 

VTG plays no physiological role in male reproductive processes. As such, any associations that 

might exist between VTG induction in males and reproductive success is likely more correlative 

than causal. 

Despite the fact that the appearance of VTG in males appears not to be a robust predictor of 

adverse effects on reproduction, the response could nonetheless play an important role in 

reducing the uncertainty of ALC for EE2, or the development of ALC for other chemicals which 

DRAFT DOCUMENT
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might be estrogenic. From Table 3.2 above, it is apparent that data from life-cycle tests with fish 

would be appropriate (and critical) to setting the final ALC for EE2 and, by extension, other 

estrogens. Hence, knowledge that a less well-studied chemical than EE2 induces VTG in males 

could be used to help identify those instances when one (or more) life-cycle fish assay(s) would 

be recommended for generating robust data for ALC derivation. Another possible use of protein 

data, that could have more direct applicability to developing an ALC for EE2, involves use of the 

endpoint as a basis for evaluating relative species sensitivity. Specifically, reproductive data 

suitable for an EE2 ALC are largely from three species: fathead minnow, medaka and zebrafish 

(Table 3.2); however, there are studies with numerous species that have evaluated the ability of 

EE2 to induce vitellogenin mRNA and protein in males. Provided that a common dose metric 

could be established across these studies, a dataset could be developed to provide an indication 

of the relative sensitivity distribution of fish species to EE2, in addition to other estrogens. This 

would enable a direct comparison of values along the continuum of estrogen sensitivity for those 

fish species wherein chronic data exist (based on VTG induction) and, as such, could provide a 

quantitative indication of uncertainty for a proposed EE2 criterion. 

There are two mechanism-specific endpoints that have been measured in a number of EE2 

studies that might, with additional research and analysis, have a direct bearing on criteria 

derivation: alterations in sex ratio (i.e., generation of genotypic males with a female phenotype) 

and the occurrence of intersex/testis-ova (Tables A.5, A.6). As opposed to VTG induction in 

males, the functional linkage between skewed sex ratios or abnormal gonad development and 

reproductive success in fish, at both the individual and population levels, is readily apparent. 

Specific endpoints, however, can be difficult to measure. For example, detailed histological 

analyses are needed to identify and, especially, quantify testis-ova. To detect an alteration in sex 

ratio, a genotypic marker of gender (available in medaka but not fathead minnow or zebrafish) or 

a relatively large representative sample is required to reliably detect chemically-induced changes 

within a proportion of males and females in a population. Probably more difficult than 

measurement of the endpoints is definition of the quantitative linkage between changes in sex 

ratio or occurrence of testis-ova and effects on reproductive success for individuals and 

populations. For example, unless one assumes that any deviation in sex ratio from the norm 

(e.g., 1:1) is adverse, it is necessary to know (in the case of estrogenic effects) the magnitude of 

shift in respective gender numbers that is likely to result in cases where fewer young are 

produced. Similarly, it is probable that some degree of testis-ova would not be considered 

adverse in terms of reducing reproductive success, especially considering that the condition can 

exist at some degree, even in control animals (Grim et al. 2007). It is certain that at some level 

of manifestation, the condition will impair gonad function sufficiently such that acceptable levels 

of normal sperm cannot be produced. The frequency of this phenomenon, however, is currently 

unknown for any fish species. Definition of this relationship would support use of testis-ova 

occurrence in fish not only for prospective assessments (like criterion derivation), but in 

environmental monitoring studies focused on chemicals with an estrogenic MOA. 

At present, uncertainties regarding measurement and interpretation hamper use of data from any 

of the mechanism-specific endpoints mentioned above as a basis for derivation of an ALC for 

EE2. Eith appropriate research, however, induction of vitellogenin in males, changes in sex 

DRAFT DOCUMENT
17 

ratios and occurrence of testis-ova, all have the potential to contribute insights to different facets 

of quantitative risk assessment for estrogenic chemicals, including derivation of ALC. There is 

one noteworthy additional observation relative to use of non-traditional endpoints for an EE2 

ALC. Several fish life-cycle studies using EE2 have been conducted in which typical measures 

of reproductive success (e.g., fecundity, fertility) have been made in conjunction with induction 

of VTG, sex ratio and/or testis-ova data (e.g., Länge et al 2001; Wenzel et al. 2001; Nash et al. 

2004; Parrott and Blunt 2005). Although experimental design variables make some of the 

endpoint sensitivity comparisons challenging, it does not appear that there are substantial 

differences in EE2 test concentrations that produce adverse effects on egg production/fertility, 

versus those that alter the mechanism-specific endpoints. Hence from a pragmatic perspective, 

at least for the near-term, it seems reasonable to base an EE2 ALC on traditional measures of 

long-term reproductive success in fish. 

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APPENDIX A

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Table A.1. Effects of EE2 on Aquatic Animals (Short-term survival). 

Species Life stage Method Duration 

EC50 or LC50 

(ng/L) Reference Remarks 

Traditional Acute (1-7 day timeframe) *Sea urchin, Strongylocentrotus purpuratus embryo S,U 96 h 30,000 Roepke 2005 EC50 - abnormal 

development 

*Sea urchin, Lytechinus anamesus embryo S,U 96 h 30,000 Roepke 2005 EC50 - abnormal 

development 

*Copepod, Acartia tonsa egg R,U 5 d 88,000 Andersen et al. 2001 EC50-Inhibition of 

naupliar developme

Medaka, Oryzias latipes adult - 96 h >1,000,000 Thompson 2000 

*Copepod, Acartia tonsa 10-12 d adult S,U 48 h 1,100,000 Andersen et al. 2001 *Opossum shrimp, Neomysis integer Juv, 2-4 mm R, U 96 h 1,200,000 Verslycke et al. 2004 

Zebrafish, Danio rerio adult - 96 h 1,700,000 Wenzel et al. 2001 

Cladoceran, Ceriodaphnia reticulata S,U 24 h 1,800,000 Jaser et al. 2003 EC50 mobility 

Cnidarian, Hydra vulgaris Adult male R, U 96 h 3,800,000 Pascoe et al. 2002 

Cladoceran, Sida crystallina S,U 24 h >4,100,000 Jaser et al. 2003 EC50 mobility 

Cladoceran, Daphnia magna <24 h S,U 48 h >5,000,000 Goto and Hiromi 2003 

Midge, Chironomus riparius 4th instar S,M 24 h 9,100,000 Lee and Choi 2006 

*Indicates saltwater species. 

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Table A.2. Effects of EE2 on Aquatic Animals (Long-term survival). 

Species Life Stage Method Duration 

NOECsurvival 

(ng/L) 

LOEC - 

survival 

(ng/L) Reference Remarks 

Significant Effect Observed 

Zebrafish, Danio rerio 1 d old R,U 38 d 10 100 Orn et al 2006 100% mo

Zebrafish, Danio rerio 2 dph R,U 58 d 10 100 Hill and Janz 2003 90% mort

control m

Medaka, Oryzias latipes 1 d R,M LC: 85 to 110 dph 29 290 Metcalfe et al. 2001 83% mort

*Sheepshead minnow, Cyprinodon variegatus juv F,M PLC:59-7 dph F1 120 330 Zillioux et al. 2001 50% mor

Medaka, Oryzias latipes 6 mo. F,M 21 d 260 490 Seki et al. 2002 42% mort

dead male

Rainbow trout, Oncorhynchus mykiss 1+ year F,M 62 d pre-spawning 130 750 Schultz et al. 2003 100% mo

Medaka, Oryzias latipes 4 mo. R,U 14 d 500 2,000 Thompson 2000; Tilton 

et al. 2005 

Significan

Zebrafish, Danio rerio fert. eggs R,U 5 wk - 5,000 Ortiz-Zarragoitia et al. 

2006 

50% mor

*Copepod, Tisbe battagliai <24 h R,U 10 d - >100,000 Hutchinson et al. 1999 Value is a

Wood frog, Rana sylvatica Gosner 26 R,U 14 d - 560,000 Hogan et al. 2006 Value is a

Amphipod, Gammarus pulex 3-5 mm R,M 10 d - 840,000 Watts et al. 2001 Value is a

Leopard frog, Rana pipiens Gosner 26 R,U 14 d - 890,000 Hogan et al. 2006 Value is a

Leopard frog, Rana pipiens Gosner 36 R,U 14 d - 1,200,000 Hogan et al. 2006 Value is a

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration) *Sand goby, Pomatoschistus minutus juv F,U 7 mo 6 - Robinson et al. 2003 

Fathead minnow, Pimephales promelas fert eggs F,U 125 d 10 - Parrot et al. 2003 

Fathead minnow, Pimephales promelas juvenile F,M 21 d 20 - Panter et al. 2002 Conc. onl

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Species Life Stage Method Duration 

NOECsurvival 

(ng/L) 

LOEC - 

survival 

(ng/L) Reference Remarks 

Chinese rare minnow, Gobiocypris rarus 7 mo F,U 28 d 25 - Zha et al. 2007 10% mort

Zebrafish, Danio rerio fert. eggs F,U 3 mo 25 - Van den Belt et al. 2003 40% mort

Fathead minnow, Pimephales promelas mature male F,U 35 d 50 - Schmid et al. 2002 

Snail, Potamopyrgus antipodarum adult R,U 9 wk 100 - Jobling et al. 2004 

Medaka, Oryzias latipes 1 d R,U 2 mo 100 - Scholz and Gutzeit 2000 8% morta

Zebrafish, Danio rerio 4 wk R,U 33 d 100 - Versonnen and Janssen 

2004 

6.6% morsolvent 

Guppy, Poecilia reticulate (male) < 7 d F,M 108 d 110 - Nielsen and Baatrup 2006 Sturgeon, Acipenser fulvescens 1 yr F,M 25 d 120 - Palace et al. 2001 

Rainbow trout male, Oncorhynchus mykiss F,M 3 wk 130 - Hook et al. 2007 

African clawed frog, Xenopus laevis adult R,U 4 wk 2,960 - Urbatzka et al. 2007 Wood frog, Rana sylvatica Gosner stage 25 R,M 76 d 4,100 - Mackenzie et al. 2003 

Amphipod Gammarus pulex mixed age F,M 100 d 7,600 - Watts et al. 2002 

Amphipod adult, Hyalella azteca pre-copulatory R,M 10 wk - 2 x gen 10,000 - Vandenbergh et al. 2003 

*Copepod, Tisbe battagliai <24 hr R,U 21 d 100,000 - Hutchinson et al. 1999 

*Copepod, Tisbe battagliai <24 hr R,U 21 d 100,000 - Pounds et al. 2002 Cladoceran, Sida crystallina R,U 34 d 500,000 - Jaser et al. 2003 

Cladoceran, Daphnia magna R,U 25 d 500,000 - Goto and Hiromi 2003 

*Indicates saltwater species. 

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Table A.3. Effects of EE2 on Aquatic Animals (Growth). 

Species Life Stage Method Duration 

NOECgrowth 

(ng/L) 

LOECgrowth 

(ng/L) Reference Remarks 

Significant Effects Observed Zebrafish , Danio rerio fert egg F,M LC – F1 0.10 0.3 Wenzel et al. 2001 7% reductiZebrafish , Danio rerio fert egg F,M PLC 0.30 1.1 Wenzel et al. 2001 2% reducti

Zebrafish, Danio rerio 20 dph R,M 40 d 0.60 1.5 Orn et al. 2003 Increased j

Fathead minnow, Pimephales promelas <24 hr F,M LC 0.76 2.8 Länge et al. 2001 

Zebrafish , Danio rerio fert egg F,U 3 mo 1 10 Van den Belt et al. 2003 

Zebrafish, Danio rerio 2 dph R,U 58 d 1 10 Lin and Janz 2006 

Fathead minnow, Pimephales promelas embryo F,M 114 d - 12 Bogers et al. 2006b 

Chinese rare minnow, Gobiocypris rarus 7 mo F,U 28 days 5 25 Zha et al. 2007 

Fathead minnow, Pimephales promelas fert eggs F,U 60 dph 10 32 Parrot and Wood 2002 

Zebrafish , Danio rerio 4 wk R,U 33 d 10 100 Versonnen and Janssen 2004 Excessive c

Guppy, Poecilia reticulata <7d F,M 108 d 44 112 Nielsen and Baatrup 2006 Increased 

Medaka, Oryzias latipes 1 day old R,M LC 29 290 Metcalfe et al. 2001 

Midge, Chironomus riparius 4th instar S,U 48 hr 50 500 Lee et al. 2006 Increased 

Midge, Chironomus riparius 1st instar R,M egg - pupa 100,000 1,000,000 Watts et al. 2003 

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration) 

Zebrafish, Danio rerio fert egg F,M 2xGen 4.5 - Nash et al. 2004 

*Three-spined stickleback, Gasterosteus aculeatus fry R,U 14 days 7.3 - Hahlbeck et al. 2004b 

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Species Life Stage Method Duration 

NOECgrowth 

(ng/L) 

LOECgrowth 

(ng/L) Reference Remarks 

Fathead minnow, Pimephales promelas fert eggs F,U 60 dph 10 - Parrot et al. 2003 

Fathead minnow, Pimephales promelas juv F,M 21 days 20 - Panter et al. 2002 

Prosobranch mollusc, Potamopyrgus antipodarum adult R,U 9 wk 100 - Jobling et al. 2004 

*Sheepshead minnow , Cyprinodon variegatus juv F,M PLC 330 - Zillioux et al. 2001 

Wood frog , Rana sylvatica Gosner stage 25 R,M 76 d 4,100 - Mackenzie et al. 2003 

*Indicates saltwater species. 

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Table A.4. Chronic Reproductive Effects of EE2 on Aquatic Animals (Fecundity, Fertility, and Population Growth). 

Species Life Stage Method Duration Endpoint 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Significant Effects Observed Fathead minnow, Pimephales promelas 40-60 h F,M LC Percent fertilized of eggs laid - 0.32 Parrott and Blun

Zebrafish, Danio rerio fert egg F,M LC Number of fertilized eggs per female 0.30 1.1 Wenzel et al. 200

Fathead minnow, Pimephales promelas <24 hr F,M LC Mean no. eggs laid per breeding day 0.76 2.8 Länge et al. 2001 Zebrafish, Danio rerio fert egg F,M 118 d No. eggs spawned and prop fertilized - 3 Fenske et al. 200

Fathead minnows, Pimephales promelas - Field 3 yrs Population crash - 3.2 – 8.9 Kidd et al. 2007 Green frog, Rana clamitans fert egg Field 2 yr Hatching success - 3.2 – 8.9 Park and Kidd 20

Zebrafish, Danio rerio fert egg F,M 2 x gen Proportion of non-viable eggs 0.50 4.5 Nash et al. 2004 

*Sand goby, Pomatoschistus minutus juv F,U 7 months Fertile eggs and hatching success - 6 Robinson et al. 2

Fathead minnow, Pimephales promelas 6-11 mo. F,M 3 wk Fert rate and no. eggs spawned 0.75 7.5 Pawlowski et al. 

Zebrafish, Danio rerio 2 dph R,U 60 d % viable eggs, % hatch, % swim-up 1 10 Hill and Janz 200

Medaka, Oryzias latipes 1 d R,U 2 mo Female egg production 1 10 Scholz and Gutz

Zebrafish, Danio rerio fert egg F,U 3 mo No. spawning females & egg prod 1 10 Van den Belt et a

Zebrafish, Danio rerio 8 mo R,U 14 d Absence of intact eggs in ovaries 1 10 Versonnen and J

2004 

Rainbow trout, Oncorhynchus mykiss 1+ year F,M PLC Fertilization success - 16 Schultz et al. 200Snail, Potamopyrgus antipodarum adult R,U 9 wk Embryo production 25 100 Jobling et al. 200

*Sheepshead minnow, Cyprinodon variegatus

juv F,M PLC Hatching success 18 120 Zillioux et al. 20

Medaka, Oryzias latipes 6 mo. F,M 21 d Fecundity 260 490 Seki et al. 2002 

DRAFT DOCUMENT
34 

Species Life Stage Method Duration Endpoint 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Medaka, Oryzias latipes 4 mo. R,U 14 d Spawning frequency, % fertilized 

and % hatch. 

5 500 Thompson 2000; 

al. 2005 

Cladoceran, Daphnia magna - R,U 25 d Embryo production 20,000 100,000 Goto and Hiromi 

Rotifer, Brachionus calyciflorus S,U 72 hr Ratio of ovigerous/non-ovigerous 

females 

202,000 510,000 Radix et al. 2002 

Rotifer, Brachionus calyciflorus S,U 72 hr Intrinsic rate population increase r 510,000 1,300,000 Radix et al. 2002 

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration)

Fathead minnow, Pimephales promelas >6 mo. F,M 3 wk No. spawnings and eggs per spawn 1.5 - Brian et al. 2007 Mink frog, Rana septentrionalis fert egg Field 2 yr Hatching success 3.2 – 8.9 - Park and Kidd 20

Zebrafish, Danio rerio (females) 5-6 mo R,U 15 d Sterility in females 5,000 - Ortiz-Zarragoitia 

2006 

Amphipod, Gammarus pulex mixed ages F, M 100 d Population growth (total pop. size) 7,600 - Watts et al. 2002 

*Copepod, Tisbe battagliai <24 hr R,U 21 days Fecundity 100,000 - Hutchinson et al

*Copepod, Tisbe battagliai <24 hr R,U 21 days Reproduction 100,000 - Pounds et al. 200

*Indicates saltwater species. 

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35 

Table A.5. Chronic Reproductive Effects of EE2 on Aquatic Animals (Sex Reversal). 

Species Life Stage Method Duration Effect 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Significant Effects Observed Zebrafish, Danio rerio fert egg F,U 3 mo Delayed sexual differentiation - 0.10 Van den Belt et al. 2003 

Zebrafish, Danio rerio 20 dph R,M 40 d Male:female sex ratios - 0.60 Orn et al. 2003 Fathead minnow, Pimephales promelas 40-60 h old F,M LC Male:femal sex ratio 0.32 0.96 Parrott and Blunt 2005 

Fathead minnow, Pimephales promelas fert. eggs F,U 60 d Male:female sex ratio 0.32 1.0 Parrot and Wood 2002 

Zebrafish, Danio rerio 2 dph R,U 58 d Male:female sex ratio - 1.0 Lin and Janz 2006 

Fathead minnow, Pimephales promelas <24 hr F,M LC Sex reversal - all female 0.76 2.8 Länge et al. 2001 

Zebrafish, Danio rerio fert egg F,M 42 d Male feminization - 3.0 Fenske et al. 2005 

Fathead minnow, Pimephales promelas fert eggs F,U 125 d Sex reversal - all female - 10 Parrot et al. 2003 

Zebrafish, Danio rerio 1 dph R,U 60 d Complete feminization - 10 Orn et al 2006 

Zebrafish, Danio rerio 1 dph R,U 60 d Complete feminization - 10 Yamani 2004 

Fathead minnow, Pimephales promelas embryo F,M 114 d 75% female gonads; 15% undeveloped - 12 Bogers et al. 2006b Zebrafish, Danio rerio fert egg R,M 60 d Complete feminization - 15 Andersen et al. 2003b 

Medaka, Oryzias latipes 1 d R,M LC Male:female sex ratio 2.9 29 Metcalfe et al. 2001 

*Three-spined stickleback, Gasterosteus aculeatus

Larvae R,U 42 d Sex reversal and intersex - 50 Hahlbeck et al. 2004a 

Medaka, Oryzias latipes 1 d R,U 2 mo Sex reversal with ovary 10 100 Scholz and Gutzeit 2000 

Medaka, Oryzias latipes 1 d R,U 60 d 88% female, 2% male, 10% 

intersex 

10 100 Yamani 2004 and Orn et 

2006 

Amphipod, Gammarus pulex mixed ages F, M 100 d Male:femal ratio - 104 Watts et al. 2002 

DRAFT DOCUMENT
36 

Species Life Stage Method Duration Effect 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Guppy, Poecilia reticulate < 7 d F,M 108 d Male:female sex ratio 44 110 Nielsen and Baatrup 2006 

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration)

Green frog, Rana clamitans fert egg Field 2 yr Male:female sex ratio 3.2 – 8.9 - Park and Kidd 2005 Mink frog, Rana septentrionalis fert egg Field 2 yr Male:female sex ratio 3.2 – 8.9 - Park and Kidd 2005 

Amphipod, Hyalella azteca adult R,M 10 wk; 2 gen Male:femal sex ratio 10,000 - Vandenbergh et al. 2003 

*Copepod, Tisbe battagliai <24 hr R,U 21 d Male:female sex ratio 100,000 - Hutchinson et al. 1999 

Cladoceran, Daphnia magna - R,U 25 d Male:female ratio 500,000 - Goto and Hiromi 2003 

*Indicates saltwater species. 

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37 

Table A.6. Chronic Reproductive Effects of EE2 on Aquatic Animals (Intersex). 

Species Life Stage Method Duration Effect 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Significant Effects Observed Pearl dace, Margariscus margarita mature Field 3 yr Presence of testis-ova - 3.2 – 8.9 Palace et al. 2006 

Fathead minnows, Pimephales promelas Field 3 yr Presence of testis-ova - 3.2 – 8.9 Kidd et al. 2007 Mink frog, Rana septentrionalis fert eggs Field 2 yr Intersex gonads (5 – 12 %) - 3.2 – 8.9 Park and Kidd 2005 Chinese rare minnow, Gobiocypris rarus 7 mo F,U 28 d Testis-ova in males 1.0 5.0 Zha et al. 2007 

Fathead minnow, Pimephales promelas egg F,U 5 d Ovarian cavities in males (8%) - 10 Van Aerle et al. 2002 

Fathead minnow, Pimephales promelas 5-10 dph F,U 5 d Ovarian cavities in males (38%) - 10 Van Aerle et al. 2002 

Fathead minnow, Pimephales promelas 10-15 dph F,U 5 d Ovarian cavities in males (64%) - 10 Van Aerle et al. 2002 

Fathead minnow, Pimephales promelas 15-20 dph F,U 5 d Ovarian cavities in males (43%) - 10 Van Aerle et al. 2002 

Fathead minnow, Pimephales promelas egg F,U 20 d Ovarian cavities in males (22%) - 10 Van Aerle et al. 2002 

Medaka, Oryzias latipes 1 d R,M LC Sex inversion and testis-ova 2.9 29 Metcalfe et al. 2001 

*Three-spined stickleback, Gasterosteus aculeatus

Larvae R,U 42 d Intersexed gonads - 50 Hahlbeck et al. 2004a 

Medaka, Oryzias latipes 6 mo F,M 21 d Testis-ova in males (33%) 33 64 Seki et al. 2002 

Medaka, Oryzias latipes 1 d R,U 2 mo All males developed an ovary 10 100 Scholz and Gutzeit 2000 

Medaka, Oryzias latipes 1 d R,U 60 d Intersexed gonads (10%) 10 100 Yamani 2004 and Orn e

al 2006 

Guppy, Poecilia reticulata < 7 d F,M 108 d Feminization of male 

reproductive ducts 

44 110 Nielsen and Baatrup 20

Amphipod, Hyalella azteca fert eggs R,M 2 x gen Oocyte-like structures in males 23 320 Vandenbergh et al. 2003 

Leopard frog, Rana pipiens Gosner 25 R,M 162 d Intersex and altered testicular 

develepment 

414 4,140 Mackenzie et al. 2003 

DRAFT DOCUMENT
38 

Species Life Stage Method Duration Effect 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Wood frog, Rana sylvatica Gosner 25-

28 

R,M 76 d Intersex and altered testicular 

development 

- 4,140 Mackenzie et al. 2003 

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration)

Green frog, Rana clamitans fert eggs Field 2 yr Intersexed gonads 3.2 – 8.9 - Park and Kidd 2005 

Zebrafish, Danio rerio 2 dph R,U 58 d Testis-ova 10 - Lin and Janz 2006 

Zebrafish, Danio rerio 2 dph R,U 58 d Testis-ova 10 - Hill and Janz 2003 

Zebrafish, Danio rerio adult F,U 21 d Feminization of testes 25 - Islinger et al. 2003 

*Indicates saltwater species. 

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39 

Table A.7. Chronic Reproductive Effects of EE2 on Aquatic Animals (Sexual Behavior). 

Species Life Stage Method Duration Effect 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Significant Effects Observed *Sand goby, Pomatoschistus minutus juv F,U 7 mo Male nesting behavior - 6 Robinson et al. 2003 

Fathead minnow, Pimephales promelas mature F,M 27 d Impaired ability to compete and 

acquire territory 

2.0 8.9 Majewski et al. 2002 

*Three-spined stickleback, Gasterosterus aculeatus

mature R,U 12 d Time spent near nest and glueing 

frequency, but effect short-lived 

- 10 Brian et al. 2006 

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration)

Zebrafish, Danio rerio fert egg F,M 2 x gen Natural spawning behavior of adult 

male fish 

4.5 - Nash et al. 2004 

Amphipod, Gammarus pulex 3-5 mm R,M 10 d Pre-copulatory guarding behavior 3,700,000 - Watts et al. 2001 

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Table A.8. Data on Effects of EE2 on Aquatic Animals (Secondary Sexual Characterstics). 

Species Life Stage Method Duration Effect Event Association 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Significant Effects Observed Fathead minnow, Pimephales promelas

6-11 mo. F,M 3 wk Number of male nuptial 

tubercles 

Activational - 0.80 Pawlowski et 

Fathead minnow, Pimephales promelas

40-60 h F,M LC Ovipositor size, nuptial 

tubercles, banding strength 

Organizational 0.32 0.96 Parrott and Bl

Fathead minnow, Pimephales promelas

156 dph F,M LC Nuptial tubercles, banding 

strength, dorsal fin dot, dorsal fat pad 

Activational 0.32 0.96 Parrott and Bl

Fathead minnow, Pimephales promelas

fert eggs F,U 60 dph Male sex index: nuptial 

tubercles, dorsal fat pad, dorsal fin dot, banding strength 

Organizational 0.32 1.0 Parrot and Wo

Fathead minnow), Pimephales promelas

<24 hr F,M LC Secondary sex characteristics – 

not specified 

Organizational 0.76 2.8 Länge et al. 20

Fathead minnow, Pimephales promelas

fert eggs F,U 60 dph Development and length of 

ovipositors 

Organizational 1.0 3.2 Parrot and Wo

Zebrafish, Danio rerio fert egg F,M 2 x gen Coloration and bright anal fin 

markings 

Organizational - 4.5 Nash et al. 20

*Sand goby, Pomatoschistus minutus juv F,U 7 mo Delayed and inhibited nuptial 

coloration in males 

Activational - 6.0 Robinson et a

Fathead minnow, Pimephales promelas

fert eggs F,U 125 d Ovipositor size, nuptial 

tubercles, banding strength 

Organizational - 10 Parrot et al. 20

Fathead minnow, Pimephales promelas

maturing F,M 21 d Number and prominence of 

nuptial tubercles and dorsal fat pad 

Activational - 11 Filby et al. 20

Fathead minnow, Pimephales promelas

embryo F,M 114 d Number and prominence of 

nuptial tubercles 

Organizational - 12 Bogers et al. 2

Amphipod, Hyalella azteca fert eggs R,M 2 x gen Male second gnathopods Organizational - 23 Vandenbergh 

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration)

Fathead minnow, Pimephales promelas

>6 mo. F,M 3 wk Relative fat pad weight, 

number of nuptial tubercles, nuptial tubercle prominence 

Activational 1.5 - Brian et al. 20

Medaka, Oryzias latipes 4 mo R,U 14 d Anal and dorsal fin shape Organizational 500 - Thompson 20

et al. 2005 

DRAFT DOCUMENT
41 

*Indicates saltwater species. 

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Table A.9. Chronic Reproductive Effects of EE2 on Aquatic Animals (Vitellogenin). 

Species Life Stage Method Duration Effect 

NOEC 

(ng/L) 

LOEC 

(ng/L) Reference 

Significant Effects Observed Zebrafish, Danio rerio adult males F,M 40 d Increased whole-blood VTG level - 0.50 Nash et al. 

Fathead minnow, Pimephales promelas 6-11 mo F,M 3 wk Increased plasma VTG levels - 0.80 Pawlowski 

Rainbow trout, Oncorhynchus mykiss immature 

female 

F,M 14 d Increased liver vtg mRNA expression 

and plasma VTG 

0.21 1.0 Thomas-Jo

Zebrafish, Danio rerio 20 dph R,M 40 d Increased whole body VTG levels - 1.5 Orn et al. 2

Zebrafish ,Danio rerio adult male R,U 21 d Increased plasma VTG level - 1.6 Fenske et a

Rainbow trout, Oncorhynchus mykiss Adult male F,M 3 wk Increased plasma VTG level - 1.8 Jobling et aZebrafish, Danio rerio fert egg F,M 42 d Increased vitellogenin level - 3.0 Fenske et a

Fathead minnow, Pimephales promelas - Field 5 mo Increased plasma VTG levels - 3.2 – 8.9 Palace et al

see Kidd et 

Pearl dace, Margariscus margarita - Field 3 yrs Increased whole body VTG level - 3.2 – 8.9 Palace et al

Zebrafish, Danio rerio adult male F,M 8 d Increased whole-body VTG level 2.2 3.6 Rose et al. 

Zebrafish, Danio rerio adult females F,M 40 d Increased whole-blood VTG level 0.50 4.5 Nash et al. 

Fathead minnow, Pimephales promelas juv F,M 21 d Increased whole-body VTG level 2.0 5.0 Panter et al

Fathead minnow, Pimephales promelas 8 mo R,M 48 hrs Increased liver vtg levels 2.5 5.0 Biales et al

Ide, Leucisus idus juv F,M 7 d Increased plasma VTG levels - 6.0 Allner et al

Zebrafish, Danio rerio fert egg R,M 4 d Increased whole body VTG level 2.6 7.8 Bogers et a

Zebrafish, Danio rerio adult females R,M 21 d Increased plasma VTG level 4.1 8.5 Van den Be

Zebrafish, Danio rerio adult males F,M 24 d Increased plasma VTG level - 9.0 Van den Be

DRAFT DOCUMENT
43 

Rainbow trout, Oncorhynchus mykiss 11 mo F,M 2 wk Increased plasm VTG level 0.87 10 Samuelsson *Eelpout, Zoarces viviparus adult female F,M 3 wk Increased plasma VTG level 5.0 10 Korsgaard 

Fathead minnow), Pimephales promelas <24 hr F,M LC Increased whole body VTG level 2.8 12 Länge et al

Zebrafish, Danio rerio adults F,M 168 hrs Increased plasma VTG level - 14 Hoffmann 

Sturgeon, Acipenser fulvescens 1 yr F,M 25 d Increased plasma VTG levels - 14 Palace et al

Lake trout, Salvelinus namaycush immature F,M 21 d Increased plasma VTG level - 15 Werner et a*Baltic flounder, Platichthys flesus adult F,M 21 d Increased plasma VTG level in male 

and female fish 

- 15 Allen et al. 

Medaka, Oryzias latipes 6 mo. F,M 21 d Increased liver Vtg levels 33 64 Seki et al. 2

Rainbow trout, Oncorhynchus mykiss juvenile R,M 14 d Increased plasma VTG level 10 100 Verslycke e

*Sheepshead minnow, Cyprinodon variegatus

male F,M 16 d Increased liver vtg mRNA expression 24 110 Folmar et a

Rainbow trout, Oncorhynchus mykiss mature male F,M 61 d Increased plasma VTG levels - 140 Skillman et 

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration)

Zebrafish, Danio rerio adult males F,M 310 dpf 

F1 

No effect on whole-blood VTG level 4.5 - Nash et al. 

Zebrafish, Danio rerio adult females F,M 310 dpf 

F1 

No effect on whole-blood VTG level 4.5 - Nash et al. 

*Indicates saltwater species. 

DRAFT DOCUMENT
44 

Table A.10. Chronic Effects of EE2 on Aquatic Animals (Other Relevant Endpoints). 

Species Life Stage Method Duration Effect Concentration (ng/L) ReferenSignificant Effects ObservedZebrafish , Danio rerio 17-20 dpf R,U 3 d Enhanced effect on CYP19A2 gene 

expression 

0.30 Kazeto e

Zebrafish, Danio rerio 2 dph R,U 58 d Suppression of gametogenesis for males 

(no testes discernable) and females 

1.0 Weber e

Chinese rare minnow, Gobiocypris rarus

7 mo F,U 28 d Increased GSI and renal somatic index 

(RSI) in males 

1.0 Zha et al

Fathead minnow, Pimephales promelas 40-60 h F,M LC Reduced GSI in females 3.5 Parrott a

Atlantic salmon, Salmo salar immature S,U 7 d Increased AchE and GST activities and 

lactate content after 3 days, but no effect at 7 days 

5.0 Greco et 

Chinese rare minnow, Gobiocypris rarus

7 mo F,U 28 d Reduced GSI in females 5.0 Zha et a

Chinese rare minnow, Gobiocypris rarus

7 mo F,U 28 d Increased RSI in females 5.0 Zha et al

Medaka, Oryzias latipes 4 mo R,U 14 d Increased male and female plasma E2 

levels 

5.0 Thompo

2005 

Fathead minnow, Pimephales promelas 6-11 mo F,M 3 wk Reduction on male GSI 7.5 PawlowZebrafish, Danio rerio Adult female R,M 21 d Reduced female ovarian somatic index 8.5 Van den 

Rainbow trout, Oncorhynchus mykiss 11 mo F,M 2 wk Higher hepatosomatic index (HSI) 10 Samuels

Fathead minnow, Pimephales promelas fert eggs F,U 125 d Increased liver somatic index 10 Parrot et 

Medaka, Oryzias latipes 1 d R,U 4 mo In both males and females, significantly 

increased number of necrotic hepatocytes and kidney tubule cells 

10 Weber e

*Baltic flounder, Platichthys flesus adult F,M 21 d Increased HSI in males 15 Allen et 

Zebrafish, Danio rerio adult male S,M 21 d Increased levels of cyp19a2 mRNA 

(aromatase) 

21 Kallivre

Chinese rare minnow, Gobiocypris rarus

7 mo F,U 28 d Increased HSI in males 25 Zha et a

DRAFT DOCUMENT
45 

Species Life Stage Method Duration Effect Concentration (ng/L) ReferenChinese rare minnow, Gobiocypris rarus

7 mo F,U 28 d Ovary degeneration in females 25 Zha et a

Zebrafish, Danio rerio adult male F,M 7 d Decreased testrosterone and 11-

ketotestosterone levels 

26 Anderse

Atlantic salmon, Salmo salar immature S,U 72 hr Induced expression of brain P450 

Aromatase 

50 Lyssima

Sturgeon, Acipenser fulvescens 1 yr F,M 25 d Increased plasma Vit E, A1 and A2; 

Decreased Vit E and A in kidney 

60 Palace e

*Sheepshead minnow, Cyprinodon variegatus

juv F,M PLC Increased pathological condition of 

kidneys 

120 Zillioux 

Rainbow trout, Oncorhynchus mykiss mature male F,M 3 wk Changed gene expression profile 130 Hook et 

Zebrafish , Danio rerio 18-21 d R,U 72 hr Stimulated expression of Cytochrome 

P450 aromatase (Aro-B) 

300 Le Page 

Medaka, Oryzias latipes mature R,U 14 d Induced ER protein and aromatase activity 500 Contract

Medaka, Oryzias latipes adult R,U 14 d Increased hepatic estrogen receptor (ER) 500 Thomps

Medaka, Oryzias latipes 4 mo. R,U 14 d Decreased female and male GSI 500 Thomps

2005 

African clawed frog, Xenopus laevis adult R,U 4 wk Reduced Leutinizing hormone B mRNA 

expression 

3,000 Urbatzk

African clawed frog, Xenopus laevis adult R,U 4 wk Reduced testosterone levels in both sexes 3,000 UrbatzkAfrican clawed frog, Xenopus laevis adult R,U 4 wk Reduced E2 level in females 3,000 UrbatzkMidge, Chironomus riparius 4th instar S,U 24 h Increased expression of heat shock 

proteins 

8,000 Lee et al

Medaka, Oryzias latipes mature male R,U 6 d Increased mRNA expression of liver 

choriogenin L 

10,000 Lee et al

Medaka, Oryzias latipes mature male R,U 6 d Increased mRNA expression of liver 

choriogenin H levels 

20,000 Lee et al

Medaka, Oryzias latipes mature male R,U 6 d Increased mRNA expression of liver 

choriogenin H levels 

20,000 Lee et al

Medaka, Oryzias latipes juv R,U 6 d Increased mRNA expression of whole 

body Choriogenic H 

50,000 Lee et al

No Signficiant Effects Observed (NOEC Equals Highest Test Concentration)

DRAFT DOCUMENT
46 

Species Life Stage Method Duration Effect Concentration (ng/L) Referen*Sand goby, Pomatoschistus minutus juv F,U 7 mo No effect on GSI in males or females 6.0 Robinso

Rainbow trout, Oncorhynchus mykiss juvenile R,M 14 d No effect on GSI or HSI 100 VerslyckAfrican clawed frog, Xenopus laevis adult R,U 4 wk No effect on Gonadotropin Releasing 

Hormone mRNA expression 

3,000 Urbatzk

*Indicates saltwater species. 

DRAFT DOCUMENT