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F I N A L T E C H N I C A L M E M O R A N D U M

Threshold Values for Selenium in Great Salt Lake: 

Selections by the Science Panel

PREPARED FOR: Great Salt Lake Science Panel

PREPARED BY: Harry Ohlendorf

COPIES: Jeff DenBleyker 

Earl Byron 

Gary Santolo 

Dan Moore 

Principal Investigators

DATE: February 28, 2007

PROJECT NUMBER: 341055.PP.QC

The purpose of this technical memorandum is to provide a summary and documentation 

of the Science Panel’s discussions relative to toxicity thresholds for exposure of birds to 

selenium at the Great Salt Lake. It is generally recognized that the most significant 

exposure of birds occurs through their diet, and that the best­documented and most 

readily­monitored effects are those on reproductive success (particularly egg hatchability). Thus, much of the focus of this technical memorandum is on those exposures and 

endpoints, because they can be most readily applied toward establishment of a site­specific

water quality standard for selenium in the open waters of the Great Salt Lake.

Before the Science Panel meeting on November 29­30, 2006, I prepared a technical

memorandum (Subject: Threshold Values for Selenium in Great Salt Lake; dated 

November 28) to provide the following:

· a summary of potential threshold values identified by Science Panel members for 

consideration in establishing a water quality standard for selenium in the open waters of

the Great Salt Lake, and

· supporting documentation and literature provided by Panel members to be used as the 

basis of discussion by the Panel.

Bill Adams, Anne Fairbrother, Theresa Presser, and Joe Skorupa provided input concerning

threshold values to be considered and sent supporting literature (either as citations or copies

of publications), in addition to providing their views on the threshold values themselves. The entire Panel discussed that material and related information from other sources on 

November 30. From the available information, the Panel narrowed the ranges of values for

bird diets and eggs to those listed in Tables 1 and 2 (Attachment A [tables modified from the 

compilation of field and laboratory data presented in Table 15 of Presser and Luoma, 2006])

and then identified “working values” for the ranges of acceptable selenium concentrations

in bird diets and in bird eggs (those shaded in the tables). It is understood that the values

will likely be refined during future phases of work (including consideration of site­specific
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data currently being generated by the Great Salt Lake research effort) and discussion related 

to establishing a site­specific standard for Great Salt Lake.

A previous draft of this technical memorandum (dated December 8) provided a brief

summary of the threshold values that were selected by the Panel during those discussions. For both diet and eggs, the ranges of selenium concentrations selected by the Panel are the 

lower and upper 95 percent confidence intervals (95% CIs; also referred to as the 5 percent 

lower confidence limit [LCL] and the 95 percent upper confidence limit [UCL]) for the mean 

selenium concentration that is associated with a 10 percent reduction (i.e., the 10 percent 

effect concentration or EC10) in the hatchability of mallard eggs. Those values were reported 

by Ohlendorf (2003), based on the analysis of data from six laboratory studies (Heinz et al. 1987, 1989; Heinz and Hoffman 1996, 1998; Stanley et al. 1994, 1996). Essentially, there is

95 percent confidence that the mean dietary or egg selenium concentration that causes a 

10 percent reduction of egg hatchability is within the identified ranges, which are illustrated

in the figures below.

The Panel agreed by consensus that the 95% CIs on mean selenium concentrations in 

mallard diet and eggs associated with the EC10 for egg hatchability would be reasonably

protective for birds nesting at the Great Salt Lake, and that the ranges of values represented 

by the 95% CIs included the concentrations proposed by various Panel members for 

consideration. Rationale supporting selection of the 95% CIs is provided by the previous

technical memorandum (dated November 28) and through discussion at the Panel meeting.

Panel members provided comments on the December 8 draft version of this technical

memorandum summarizing threshold values (Attachment B), and Bill Adams provided 

further data analyses of effect levels in diets and eggs of mallards that are included in this

revised draft. Additional considerations and qualifications about the selected dietary and 

egg concentrations are presented below in the Discussion section. All concentrations in bird diets or eggs mentioned below are expressed on dry­weight basis.

Selenium in Bird Diets

The dietary selenium EC10 for mallards was reported as 4.87 mg/kg, with 95% CIs of 3.56 to 

5.74 mg/kg based on reproductive toxicity (egg hatchability) (Ohlendorf 2003). The EC10 of

4.87 mg/kg was estimated by fitting a logistic regression model (Figure 1). It should be 

noted, however, that the mallard studies used a “dry diet” that had about 10 percent 

moisture. Ohlendorf (2003) used the reported dietary selenium concentrations without 

adjustment for that moisture content, but an upward adjustment of the values (by

11 percent) would be appropriate to account for the moisture content of the duck diet.

In Adams et al. (2003), hockey­stick regression was used to model relationships between egg

selenium concentrations and adverse effects in order to derive toxicity thresholds, such as

EC10 values. Hockey­stick regression is a model that has been used elsewhere to define a 

threshold when an underlying background level of response is unrelated to the dose (see 

Adams comments in Attachment B). Thus, such a model may be relevant to naturally

occurring elements that are essential to birds and a wide variety of other organisms and 

particularly useful for elements such as selenium, which has a narrow range between levels

that are essential and those that are toxic to birds so that variance around the inflection 

point (threshold) in the model is small. As shown in Figure 2 below, a threshold clearly
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0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

0.1 1 10 100

Dietary Se, mg/kg dry wt. 

Duckling Mortality, %

Empirical data

Predicted mortality 

95% confidence interval 

Inflection point = 3.9 mg/kg

EC10 (predicted) = 4.4 mg/kg

EC10 (LCL) = 3.8 mg/kg

EC10 (UCL) = 4.8 mg/kg

Figure 2.  Hockey stick regression of laboratory mallard duckling 

mortality versus dietary selenium.
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appears to exist when dietary selenium is plotted versus duckling mortality (which 

incorporated the cumulative effects of fertilization success and hatchability). The inflection 

point occurs at a dietary selenium concentration of 3.9 mg/kg. (The Discussion section 

below describes uncertainty around the inflection point.) The predicted EC10 is 4.4 mg/kg

(just slightly above the inflection point) and the 95% CI around the predicted EC10 ranges

from 3.8 to 4.8 mg/kg. The predicted EC10 of 4.4 mg/kg is slightly lower than Ohlendorf’s

(2003) EC10 of 4.9 mg/kg, and the 95% CI is narrower using hockey stick regression than 

when using logistic regression.

Selenium in Bird Eggs

Similar to the dietary values calculated by Ohlendorf (2003) for reproductive toxicity for 

mallards, the EC10 in eggs was reported as 12.5 mg/kg, with 95% CIs of 6.4 to 16.5 mg/kg

(Figure 3). The EC10 of 12.5 mg/kg was estimated by fitting a logistic regression model to 

the results of the six laboratory studies with mallards. As noted in Table 2, the EC10 for duckling mortality, as reported in Adams et al. (2003),

ranged from 12 to 16 mg/kg (see Adams comments in Attachment B). These EC10 values are 

based on a synthesis of laboratory studies in which the final endpoint was duckling mortality

(the same effects data used in the dietary EC10 evaluation with hockey­stick regression above)

and the range of EC10 values reflects different statistical approaches for analyzing the data.

An adaptation from Figure 3 in Adams et al. (2003) is provided below (Figure 4), with the 

95% CI included. As shown, the inflection point occurs at an egg selenium concentration 

of 9.8 mg/kg, with a predicted EC10 comparable to that derived by Ohlendorf (2003).

(See Discussion for comments concerning uncertainty around the inflection point.) However, 

the 95% CI using hockey­stick regression is much narrower (9.7 to 13.6 mg/kg) than that 

derived by Ohlendorf using logistic regression (6.4 to 16.5 mg/kg). Given that there is a clear 

egg­selenium threshold at which effects begin to be observed, a unimodal model, such as

logistic regression, may result in exaggerated confidence intervals, particularly in the tails.

Discussion

Additional discussion is presented below concerning the basis for selection of threshold

values, uncertainty surrounding the hockey­stick regression inflection points, hormetic

effects of selenium, and other qualifications and points discussed during the Panel meeting

in November, as reflected in comments from Panel members (Attachment B).

Basis for Selection of Threshold Values

The Science Panel can choose a scientifically­based threshold value or acceptable 

“benchmark” concentration based on the consensus confidence limits described by analysis

of available data (presented above), but ultimately, a choice of numbers from within the 

consensus confidence limits for regulatory purposes is not a scientific decision. Choices of a 

specific number or numbers from within those confidence ranges are philosophical/legal 

decisions that depend on how precautionary the State of Utah wants to be (a matter of

philosophy) and on how much potential for legal liability the State is comfortable with 

exposing itself to. The key decision the State must make is whether they want to regulate to 

a “NEC” (no effects concentration, which is not the same as a NOEC [no observed effects
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0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

0.1  1  10  100 

Egg Se, mg/kg dry wt.  Duckling Mortality, %

Empirical data 

Predicted mortality

95% confidence interval

Inflection point = 9.8 mg/kg 

EC10 (predicted) = 11.5 mg/kg 

EC10 (LCL) = 9.7 mg/kg 

EC10 (UCL) = 13.6 mg/kg

Figure 4.  Hockey stick regression of laboratory mallard duckling 

mortality versus egg selenium.
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concentration]) standard or to some version of a “tolerably toxic” standard such as an EC10, an EC20, or an EC05, etc. Conceptually, a benchmark concentration is defined as the location on the exposureresponse curve that is the threshold between absence and presence of a given effect or 

endpoint (i.e., the threshold between an EC00 and an EC01 concentration [see:

www.epa.gov/ecotox/ecossl/pdf/ecossl_attachment_3­2.pdf; p. A­6]). Benchmark

concentrations are estimated as the lower 95 percent confidence boundary on the EC10 (see:

Meister and Van Den Brink [2000], pp. 114­116 in particular; and USEPA [2000]).

Uncertainty Surrounding the Hockey­Stick Regression Inflection Points

To determine the inflection point between the hockey­stick “blade” and “handle”, or any

parameter in the model, initial parameter values are input to the software program SPlus®

and an iterative technique is used to search for more exact parameter values that will

minimize the sum of squared deviations between the observed effects data and effects

values predicted by the model. Variance in the estimate of the inflection point value is

affected by the spacing of the measured X values as well as the scatter or trend in Y values

in the vicinity of the estimated inflection point. If, for example, there are few measured 

dietary selenium concentrations near the predicted inflection point, the uncertainty in the 

location of the inflection point will be greater because it will be difficult to determine the 

exact concentration at which the inflection point occurs (i.e., it could be between two of the 

measured values). Uncertainty around the predicted Y (EC) values at the predicted 

inflection point is affected by the number of Y values and the scatter of the Y values at that 

particular X value (which, when calculating the confidence interval around Y, is assumed to 

be estimated without error). Thus, both the spacing of the measured X values and the 

variance in the response variable affects the uncertainty around the inflection point. The 

tighter spacing and less ambiguous effects response after the inflection point causes the 

95% CI around the dietary selenium­based inflection point (3.0 to 4.9 mg/kg) to be narrower 

than that for the egg selenium­based inflection point (6.4 to 14.9 mg/kg). However, although there is uncertainty surrounding the inflection point, use of the best 

estimate of the inflection point results in the best fit of the regression model to the data. In 

Figure 4, for example, if the inflection point occurred at either end of the 95% CI of egg

selenium concentration (6.4 to 14.9 mg/kg dry wt.) one can easily visualize that the fit of the 

regression to the data points above the inflection point would not pass through the 

measured values in the same way.

Hormetic Effects of Selenium

Consideration of the hormetic effects of selenium may result in lowering of thresholds (for 

hormetic substances and endpoints one has to distinguish between valid control responses

and hormetic deficiency responses before a valid baseline to compare toxic responses

against can be identified). The hormetic bias in the data used for the Ohlendorf (2003)

regressions has not yet been fully considered by the Science Panel. If such consideration 

were to result in changes, those changes could only be in the direction of a downward 

shifting of the threshold confidence limits. (For example, preliminary unpublished analyses

that adjusted for hormetic effects in the mallard data yielded a revised EC10 for diet of
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4.1 mg/kg, with a 95% CI of 1.3 to 5.8 mg/kg, and a revised EC10 for eggs of 9.22 mg/kg, with a 95% CI of 4.11 to 13.07 mg/kg.).

Other Qualifications and Points Discussed 

The Panel also discussed the following additional qualifications and points relative to 

toxicity threshold values:

· Applicability of laboratory data to field situations is not certain (note that field data were 

retained in compilation of egg­selenium concentrations in Table 2), and it is important to 

collect site­specific field data on selenium concentrations in bird eggs (e.g., current data 

gathering effort at the Great Salt Lake).

· Applicability of mallard data to species at Great Salt Lake is uncertain, because relative 

sensitivity of all species nesting there is not known.

· Threshold values discussed are for the hatchability endpoint (based on diet and avian 

egg) but non­reproductive adverse effects endpoints (e.g., avian blood endpoint) also 

may be important. However, interpretive values for selenium in avian blood are not 

available; although selenium concentrations in blood indicate exposure of the birds, that 

endpoint is not considered useful for setting a water quality standard.

· Phalaropes are seasonally numerous at the Great Salt Lake and should be added to the 

list of species to be monitored because they represent species with a feeding rate that is a 

large percentage of body weight (affecting energy consideration in determining wildlife 

criterion).

Recommended Next Steps

The issues summarized in this technical memorandum should be discussed/considered 

further by the Panel, particularly to refine the selection of threshold values for bird diets and 

eggs with respect to effects documented elsewhere (in field and laboratory studies) and 

considering the results being developed through research at the Great Salt Lake. In parallel,

it will be important to know what level of protectiveness the State and EPA will apply in the 

development of the site­specific standard for selenium on the Great Salt Lake (i.e., EC20, EC10, EC05, etc.) so that the Science Panel can most effectively make recommendations that 

can be applied toward that purpose.

References

Adams, W.J., K.V. Brix, M. Edwards, L.M. Tear, D.K. DeForest, and A. Fairbrother. 2003. Analysis of field and laboratory data to derive selenium toxicity thresholds for birds.

Environ. Toxicol. Chem. 22: 2,020­2,029.

Harding, L.E., M. Graham, and D. Paton. 2005. Accumulation of selenium and lack of severe 

effects on productivity of American dippers (Cinclus mexicanus) and spotted sandpipers

(Actitis macularia). Arch. Environ. Contam. Toxicol. 48: 414­423. Heinz, G.H., and D.J. Hoffman. 1996. Comparison of the effects of seleno­L­methionine, seleno­DL­methionine, and selenized yeast on reproduction of mallards. Environ. Pollut. 91: 169­175.
THRESHOLD VALUES FOR SELENIUM IN GREAT SALT LAKE: SELECTIONS BY THE SCIENCE PANEL 

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Heinz, G.H., and D.J. Hoffman. 1998. Methylmercury chloride and selenomethionine 

interactions on health and reproduction in mallards. Environ. Toxicol. Chem. 17: 139­145. Heinz, G.H., D.J. Hoffman, A.J. Krynitsky, and D.M.G. Weller. 1987. Reproduction in 

mallards fed selenium. Environ. Toxicol. Chem. 6: 423­433.

Heinz, G.H., D.J. Hoffman, and L.G. Gold. 1989. Impaired reproduction of mallards fed an 

organic form of selenium. J. Wildl. Manage. 53: 418­428.

Lam, J.C.W., S. Tanabe, M.H.W. Lam, P.K.S. Lam. 2005. Risk to breeding success of

waterbirds by contaminants in Hong Kong: evidence from trace elements in eggs. Environ. Pollut. 135: 481­490. Meister, R., and P.J. Van Den Brink. 2000. The analysis of laboratory toxicity experiments. Pages 99­118 in T. Sparks (ed.), Statistics in Ecotoxicology. John Wiley & Sons, LTD, New

York, NY. Ohlendorf, H.M. 2003. Ecotoxicology of selenium. Pages 465­500 in D.J. Hoffman et al., eds. Handbook of Ecotoxicology, Second Edition, Lewis Publishers, Boca Raton, FL.

Presser, T.S., and S.N. Luoma. 2006. Forecasting Selenium Discharges to the San Francisco 

Bay­Delta Estuary: Ecological Effects of a Proposed San Luis Drain Extension. Professional 

Paper 1646. U.S. Geological Survey, Reston, VA.

Skorupa, J.P. 1998. Risk assessment for the biota database of the National Irrigation Water 

Quality Program. U.S. Fish and Wildlife Service.

Skorupa, J.P. 1999. Beware missing data and undernourished statistical models: comment on 

Fairbrother et al.’s critical evaluation. Hum. Ecol. Risk Assess. 5: 1,255­1,262.

Stanley, Jr., T.R., J.W. Spann, G.J. Smith, and R. Rosscoe. 1994. Main and interactive effects of

arsenic and selenium on mallard reproduction and duckling growth and survival. Arch.

Environ. Contam. Toxicol. 26: 444­451.

Stanley, Jr., T.R., G.J. Smith, D.J. Hoffman, G.H. Heinz, and R. Rosscoe. 1996. Effects of

boron and selenium on mallard reproduction and duckling growth and survival. Environ. Toxicol. Chem. 15: 1,124­1,132. U.S. Environmental Protection Agency (USEPA). 2000. Benchmark Dose Technical Guidance 

Document. [External Review Draft]. EPA/630/R­00/001. U.S. Environmental Protection 

Agency, Washington, DC. Yamamoto, J.T., and G.M. Santolo. 2000. Body condition effects in American kestrels fed 

selenomethionine. J. Wildl. Dis. 36: 646­652.
ATTACHMENT A

Tables
ATTACHMENT A: TABLES

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TABLE 1

Diet Concentrations 

mg/kg  Approach or Site  Effects  Species  Reference(s)

4.87

(CI 3.56 ­ 5.74)

Synthesis of lab 

Data 

Hatchability in mallards (10% effect level/95% confidence 

boundaries)

Mallard  Ohlendorf 2003 

4.4 

(CI 3.8 ­ 4.8)

Synthesis of lab 

data 

EC10  for duckling mortality  Mallard  Bill Adams analyses 

presented in Attachment B

3.85 ­ 7.7 (diet based 

on 10% moisture)

Lab Reduced hatching success in mallards (33% at 7.7 μg/g);

reduced growth and weight in hatchlings 

Mallard  Stanley et al. 1996 

7.7 (diet based on 

10% moisture)

Lab Reduction in number of surviving mallard ducklings 

produced per female 

Mallard  Stanley et al. 1996 

8.8 4.4/6.2 (diet based 

on 10% moisture)

Lab 8.8 ­ LOAEL, 4.4 ­ NOAEL, 6.2 ­ Geometric Mean 

Reduction (17%) in survival of mallard ducklings; mean 

decrease (43%) in number of 6­day­old ducklings 

Mallard  Heinz et al. 1989 

6  Lab Adverse effect on body condition of male American 

kestrels 

American Kestrels  Yamamoto and Santolo, 2000

7.7 ­ 8.8 (diet based 

on 10% moisture)

Lab Dietary threshold of teratogenic effects in mallards;

above upper threshold, rate of deformity rises sharply 

Mallard  Stanley et al. 1996 

7.7 ­ 8.8 (diet based 

on 10% moisture)

Lab Dietary threshold of mallard duckling mortality (parental

exposure)

Mallard  Stanley et al. 1996 

Note: Highlighted cells are the threshold values for bird diets identified by consensus of the Science Panel on November 30, 2006.
ATTACHMENT A: TABLES

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TABLE 2

Egg Concentrations 

mg/kg 

(dry wt.) Approach or Site  Effects  Species  Reference(s)

12.5

(CI 6.4 ­ 16.5)

Synthesis of lab 

data 

Hatchability in mallards (10% effect level/95% confidence 

boundaries)

Mallard  Ohlendorf 2003 

10  Synthesis of lab 

data 

NOAEL  Mallard  Adams et al. 2003 

12 ­ 16  Synthesis of lab 

data 

EC10  for duckling mortality  Mallard  Adams et al. 2003 

9  Synthesis of lab 

data 

Impaired clutch viability (8.2% effects level) Mallard  Lam et al. 2005 

8.2 (or 7.3) (egg based 

on 73% moisture)

Field  16% depression in egg viability (7.3 in paper) Spotted Sandpiper Harding et al. 2005 

6  Synthesis of field 

data 

Threshold (3% effect level) of hatchability  Stilts  Skorupa, 1998; Skorupa, 1999 

5.1 (egg based on 

78.4% moisture)

Field  15% depression in egg viability  American dipper Harding et al. 2005 

Note: Highlighted cells are the threshold values for bird eggs identified by consensus of the Science Panel on November 30, 2006.
ATTACHMENT B

Comments on December 8, 2006, 

Draft Technical Memorandum
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ATTACHMENT B

Comments on December 8, 2006, 

Draft Technical Memorandum 

Comments of Bill Adams 

Following are comments on Harry Ohlendorf’s draft technical memorandum to the Great 

Salt Lake Science Panel entitled Threshold Values for Selenium in Great Salt Lake: Selections by 

the Science Panel (December 8, 2006).

Selenium in Bird Diets

As noted in the draft memorandum, the mallard studies used in Ohlendorf (2003) as the 

basis for a dietary selenium EC10 in birds was based on a “dry diet” containing about 

10% moisture. Although the moisture content of the mallard diet was low, we recommend 

that standard convention should be used to properly adjust the dietary selenium

concentrations to a dry weight basis. The equation for the wet weight­to­dry weight 

conversion is included in Attachment 1 to this memorandum.

In Adams et al. (2003), hockey­stick regression was used to model relationships between egg

selenium concentrations and adverse effects in order to derive toxicity thresholds, such as

EC10 values. Hockey­stick regression is a model that has been used to define a threshold

when an underlying background level of response is unrelated to the dose. Thus, such a 

model may be relevant to naturally occurring elements that are essential to birds and a wide 

variety of other organisms and particularly useful for elements such as selenium, which has

a narrow range between levels that are essential and levels that are toxic to birds so that 

variance around the inflection point (threshold) in the model is small. As shown in 

Figure 1 below, a threshold clearly appears to exist when dietary selenium is plotted versus 

duckling mortality (which incorporated the cumulative effects of fertilization success and 

hatchability). The inflection point occurs at a dietary selenium concentration of 3.9 mg/kg

dry wt. (please see discussion at end of comments concerning uncertainty around the 

inflection point). The predicted EC10 is 4.4 mg/kg dry wt. (just slightly above the inflection 

point) and the 95% confidence interval around the predicted EC10 ranges from 3.8 to 

4.8 mg/kg dry wt. The predicted EC10 of 4.4 mg/kg dry wt. is slightly lower than Harry 

Ohlendorf’s EC10 of 4.9 mg/kg dry wt., but the 95% confidence interval is narrower using

hockey stick regression.

Selenium in Bird Eggs

As noted in Table 2 of the draft memorandum, the EC10 for duckling mortality, as reported 

in Adams et al. (2003), ranged from 12­16 mg/kg dry wt. These EC10 values are based on a 

synthesis of laboratory studies in which the final endpoint was duckling mortality (the same 

effects data used in the dietary EC10 evaluation above) and the range of EC10 values reflects

different statistical approaches for analyzing the data. An adaptation from Figure 3 in 

Adams et al. (2003) is provided below, with the 95% confidence interval included. As
ATTACHMENT B: COMMENTS ON DECEMBER 8, 2006, DRAFT TECHNICAL MEMORANDUM 

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shown, the inflection point occurs at an egg selenium concentration of 9.8 mg/kg with a 

predicted EC10 comparable to that derived by Harry Ohlendorf (please see discussion at 

end of comments concerning uncertainty around the inflection point). However, the 

95% confidence interval using hockey stick regression is much narrower (9.7 to 13.6 mg/kg

dry wt.) than that derived by Harry using logistic regression (6.4­16.5 mg/kg dry wt.). Given that there is a clear egg selenium threshold at which effects begin to be observed, a 

unimodal model, such as logistic regression, may result in exaggerated confidence intervals, particularly in the tails.

Uncertainty Surrounding the Hockey­Stick Regression Inflection Points

To determine the inflection point between the hockey­stick “blade” and “handle”, or any

parameter in the model, initial parameter values are input to the software program SPlus®

and an iterative technique is used to search for more exact parameter values that will

minimize the sum of squared deviations between the observed effects data and effects

values predicted by the model. Variance in the estimate of the inflection point value is

affected by the spacing of the measured X values as well as the scatter or trend in Y values

in the vicinity of the estimated inflection point. If, for example, there are few measured 

dietary selenium concentrations near the predicted inflection point, the uncertainty in the 

location of the inflection point will be greater because it will be difficult to determine the 

exact concentration at which the inflection point occurs (i.e., it could be between two of the 

measured values). Uncertainty around the predicted Y (EC) values at the predicted 

inflection point is affected by the number of Y values and the scatter of the Y values at that 

particular X value (which, when calculating the confidence interval around Y, is assumed to 

be estimated without error). Thus, both the spacing of the measured X values and the 

variance in the response variable affects the uncertainty around the inflection point. The 

tighter spacing and less ambiguous effects response after the inflection point causes the 

95% confidence interval around the dietary selenium­based inflection point (3.0 to 

4.9 mg/kg dry wt.) to be narrower than that for the egg selenium­based inflection point 

(6.4 to 14.9 mg/kg dry wt.). However, although there is uncertainty surrounding the inflection point, use of the best 

estimate of the inflection point results in the best fit of the regression model to the data. In 

Figure 2, for example, if the inflection point occurred at the either end of the 95% confidence 

interval of egg selenium concentration (6.4 to 14.9 mg/kg dry wt.) once can easily visualize 

that the fit of the regression to the data points above the inflection point would not pass

through the measured values in the same way.
ATTACHMENT B: COMMENTS ON DECEMBER 8, 2006, DRAFT TECHNICAL MEMORANDUM 

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Figure 1.  Hockey stick regression of laboratory mallard duckling mortality versus dietary  selenium. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.1 1 10 100

Dietary Se, mg/kg dry wt. 

Duckling Mortality, %

Empirical data Predicted mortality

95% confidence interval

Inflection point = 3.9 mg/kg

EC10 (predicted) = 4.4 mg/kg

EC10 (LCL) = 3.8 mg/kg

EC10 (UCL) = 4.8 mg/kg

Figure 2. Hockey stick regression of laboratory mallard duckling mortality versus egg 

selenium.

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

0.1  1  10  100 

Egg Se, mg/kg dry wt.

Duckling

Mortality,

%

Empirical data  Predicted mortality 

95% confidence interval

Inflection point = 9.8 mg/kg 

EC10 (predicted) = 11.5 mg/kg 

EC10 (LCL) = 9.7 mg/kg 

EC10 (UCL) = 13.6 mg/kg
ATTACHMENT B: COMMENTS ON DECEMBER 8, 2006, DRAFT TECHNICAL MEMORANDUM 

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ATTACHMENT 1 

WET WEIGHT­TO DRY WEIGHT CONVERSION FOR DIETARY SELENIUM 

CONCENTRATIONS IN MALLARD STUDIES 

solids

f

Wet Weight Concentration  Dry Weight Concentration =

Where: fsolids = fraction solids in diet (i.e., 0.9 in a diet containing

10% moisture)
ATTACHMENT B: COMMENTS ON DECEMBER 8, 2006, DRAFT TECHNICAL MEMORANDUM 

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Comments of Anne Fairbrother 

I realize that I am late (the last?) on providing comments and feedback on the report you 

pulled together from our last Salt Lake City meeting on threshold values. I was sort of

hoping to see the data from Bill Adams’ re­analysis of the dose­response before replying... Absent that, here are my thoughts and comments.

I think you did an appropriate job pulling together what was discussed at the meeting in 

regard to diet and egg threshold levels. However, the more I look at the data in regard to 

selenium uptake and effects, the more convinced do I become that we are dealing with a 

threshold phenomenon, likely because of the essential nature of the element. I do believe 

that the mean value for the EC10 that was selected for both endpoints is likely to remain 

pretty much the same regardless of what dose­response model is used, but the standard 

error about the mean may be different. Likely it will be smaller when using a threshold

model since a logistic model tends to spread out the CI’s at its tails. So, for now, I am willing

to approve the document as a report of what was discussed at the meeting, but not as a final 

say on what we have agreed to for the EC10 and its confidence intervals.
ATTACHMENT B: COMMENTS ON DECEMBER 8, 2006, DRAFT TECHNICAL MEMORANDUM 

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Comments of Theresa Presser 

Suggested additions to threshold discussion write­up of 12/8/06:

1) Page 1: Note that compilation of data for consideration was adapted from Presser and 

Luoma (2006), table 15.

2) Page 1: Note that in addition to laboratory data, a compilation of field data for egg

concentrations was retained.

3) Page 1: Note that any final determination must take into account site­specific data 

currently being generated by the Great Salt Lake research effort. 

4) Page 2 wording: “The panel agreed by consensus that the 95% CIs on mean selenium

concentrations in mallard diet and eggs would be reasonably protective for birds nesting

at the Great Salt Lake, and the range of values included the concentrations proposed by

various panel members for consideration. Rational supporting selection of the 95% CIs is

provided by the previous technical memorandum and through discussion at the panel

meeting.” 

a) Did you mean here the 95% CIs on the mean EC10 for hatchability?

b) The phrase “would be reasonably protective for birds nesting at the Great Salt Lake” 

does not adequately convey all parts of the extensive discussion that took place. I did 

not perceive that a consensus had been reached as to protectiveness, only that a 

consensus had been reached as to the interpretation of data from mallard lab

experiments. Therefore, I suggest incorporating into the wording of a summary

statement the following qualifications and points that were discussed at the meeting:

1) Applicability of lab data to field situations (note retention of compilation of field 

data in table 2 and current data gathering effort at the Great Salt Lake; points

2 and 3 listed above)

2) Applicability of mallard data to species at Great Salt Lake (sensitivity issue) 

3) Applicability of hatchability endpoint (diet and avian egg) and non­reproductive 

adverse effects endpoints (e.g., avian blood endpoint) 

4) Level of protection and precautionary regulation as exemplified by benchmark

concentration regulation. Specifically add excerpt from page 8 of 11/28/06 

memo as clarification of 95% CI: “Conceptually, a benchmark concentration is

defined as the location on the exposure­response curve that is the threshold

between absence and presence of a given effect or endpoint, i.e., the threshold

between an EC00 and an EC01 concentration (see:

www.epa.gov/ecotox/ecossl/pdf/ecossl_attachment_3­2.pdf; p. A­6)..... Benchmark concentrations are estimated as the lower 95% confidence boundary 

on the EC10 (see: Meister, R., and P.J. Van Den Brink. 2000. The analysis of

laboratory toxicity experiments. Pages 99­118 in T. Sparks (ed.), Statistics in 

Ecotoxicology. John Wiley & Sons, LTD, New York, NY: [pp 114­116 in 

particular]; and see: USEPA. 2000. Benchmark Dose Technical Guidance
ATTACHMENT B: COMMENTS ON DECEMBER 8, 2006, DRAFT TECHNICAL MEMORANDUM 

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Document. [External Review Draft]. EPA/630/R­00/001. U.S. Environmental 

Protection Agency, Washington, DC).” 

5) Addition of phalarope to list of species to be monitored to represent species with 

a feeding rate that is a large percentage of body weight (energy consideration in 

determining wildlife criterion). 

6) Potential lowering of thresholds through consideration of hormesis data (for 

hormetic substances and endpoints one has to distinguish between valid control

responses and hormetic deficiency responses before a valid baseline to compare 

toxic responses against can be identified).

5) References: Add Presser and Luoma, 2006.

6) Table 1:”Bill Adams suggestion” needs to be documented as how his entry differs from 

entry #1 in table 1.
ATTACHMENT B: COMMENTS ON DECEMBER 8, 2006, DRAFT TECHNICAL MEMORANDUM 

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Comments of Joe Skorupa 

In Table 1 I don’t believe the science panel wanted the value of 4.87 to be presented in bold 

type, only the confidence limits (for comparison see Table 2 where I think you have it the 

way the science panel intended). Adjusting for 10% moisture would result in an 11% increase in the dietary values, not an 

upward adjustment of 10% as stated.

I didn’t feel like your draft write­up adequately conveyed our (sci. panel’s) discussion 

concerning the fact that, ultimately, a choice of numbers from within the consensus

confidence limits is not a scientific decision. That confidence range is as far as science can 

bring us... choosing a specific number or numbers from within those confidence ranges are 

philosophical/legal decisions that depend on how precautionary the State of Utah wants to 

be (a matter of philosophy) and on how much potential for legal liability the State is

comfortable with exposing itself to. The key decision the State must make is whether they

want to regulate to a “NEC” (no effects concentration... which is not the same as a NOEC) 

standard or to some version of a “tolerably toxic” standard such as an EC­10, or EC­20, or 

EC­05 etc.

Finally, I think on the scientific side of things we would be remiss in our duty as experts

not to include some discussion indicating that the issue of hormetic bias in the data used for 

the Ohlendorf (2003) regressions has not yet been fully considered by the science panel (at 

Bill Adams request to defer it so that he could preview Beckon’s SETAC presentation before

I presented any of it to the panel... although it seemed to be acceptable to everyone to see 

Kennecott’s U. of Wyoming presentation without any opportunity for anyone other than

Bill A. to preview it... seems like a double standard to me), and that if such consideration 

were to result in changes, those changes could only be in the direction of a downward 

shifting of the threshold confidence limits.

For example, remember that the analysis that Brad Sample re­ran to adjust for hormetic

effects in the mallard data yielded a revised EC­10 for diet of 3.7 ppm ww [4.1 ppm dw]

with a 95% confidence interval of 1.15 ­ 5.18 ppm ww [1.3 ­ 5.8 ppm dw] and a revised 

EC­10 for eggs of 9.22 ppm dw with a 95% confidence interval of 4.11 ­ 13.07 ppm dw.