U.S. Department of the Interior U.S. Geological Survey The accuracy and protectiveness of Biotic Ligand Model (BLM) toxicity predictions with copper Christopher

U.S. Department of the InteriorU.S. Geological Survey

The accuracy and protectiveness of Biotic Ligand Model (BLM) toxicity predictions with copper

Christopher A. Mebane

U.S. Geological Survey, Boise, Idaho, USA

Workshop on Biotic Ligand Model Principles and Applications

Wilfrid Laurier University, Waterloo, Ontario, Canada

May 12-14, 2008

All analyses and data summaries shown in this talk are provisional and subject to revision

In the States, It’s not just a model, it’s the law...

At least, national criteria issued pursuant to the law.

, # 2

March

BLM promoted to provide less stringent effluent limits

“Using the new [BLM-based copper] criteria effectively”

“It is expected that the BLM-based criteria will be less stringent in low hardness waters, but possibly more stringent in harder waters. Therefore, wastewater treatment plants discharging into waters with low hardness, especially with high dissolved organic carbon, should consider performing a BLM and proposing alternative copper effluent limits as appropriate.”

http://www.cdm.com/knowledge_center/monthly_viewpoint/epa_copper_criteria.htm (viewed April 29, 2008)

Yukon River at Eagle, Alaska

USGS Photo

BLM- and hardness based chronic copper criterion, Yukon River at Eagle, AK

0

10

20

30

40

50

60

70

Oct

-20

00

Jan

-20

01

Ap

r-2

00

1

Jul-

20

01

Oct

-20

01

Jan

-20

02

Ap

r-2

00

2

Jul-

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r-2

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-20

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r-2

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Jul-

20

04

Oct

-20

04

Jan

-20

05

Ap

r-2

00

5

Jul-

20

05

Date

Co

pp

er

(µg

/l)

0

2

4

6

8

10

12

14

16

DO

C (

mg

/L)

BLM-CCC

Hardness-basedCCC (µg/L)Cu CWQG (1987)

DOC

Yukon River

USGS Photo

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

Oct

-20

00

Jan

-20

01

Ap

r-2

00

1

Jul-

20

01

Oct

-20

01

Jan

-20

02

Ap

r-2

00

2

Jul-

20

02

Oct

-20

02

Jan

-20

03

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r-2

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3

Jul-

20

03

Oct

-20

03

Jan

-20

04

Ap

r-2

00

4

Jul-

20

04

Date

Flo

w (

m3 /s

)

0

2

4

6

8

10

12

14

16

DO

C (

mg

/L)

Flow DOC

Uncredited photo, www.city-data.com

Columbia River between Northport, WA and Trail, BCBLM-based acute copper criterion, Columbia River

at Northport, WA, 1995-2000

0

2

4

6

8

10

12N

ov-1

995

Feb

-199

6

May

-199

6

Aug

-199

6

Nov

-199

6

Feb

-199

7

May

-199

7

Aug

-199

7

Nov

-199

7

Feb

-199

8

May

-199

8

Aug

-199

8

Nov

-199

8

Feb

-199

9

May

-199

9

Aug

-199

9

Nov

-199

9

Feb

-200

0

May

-200

0

Aug

-200

0

Date

Co

pp

er (

µg

/l)

Ambient Copper

BLM-CCC

Hardness-based CCC

CWQG (1987)

Northwestern soft water salmon stream, Big Soos Creek, WA

Photo King County Department of Parks and Natural Resources

BLM- and hardness based chronic copper criterion, Big Soos Creek, Auburn, WA

0

5

10

15

20

25

30

De

c-1

99

5

Fe

b-1

99

6

Ap

r-1

99

6

Jun

-19

96

Au

g-1

99

6

Oct

-19

96

De

c-1

99

6

Fe

b-1

99

7

Ap

r-1

99

7

Jun

-19

97

Au

g-1

99

7

Oct

-19

97

De

c-1

99

7

Fe

b-1

99

8

Ap

r-1

99

8

Date

Co

pp

er

(µg

/l)

BLM-CCC

Hardness-based CCC (EPA 2002), µg/L)

Ontario 1994 PWQO

CWQG (1987)

Extremely soft water stream

USFS Photo

BLM- and hardness based chronic copper criterion, NF Coeur d'Alene River

0

1

2

3

4

5

6

Mar-1999

Apr-1999

May-1999

Jun-1

999

Jul-1

999

Aug-1999

Sep-1999

Oct-19

99

Nov-1

999

Dec-1

999

Jan-2

000

Feb-2000

Date

Co

pp

er (

µg

/l)

BLM-CCCCWQG (1987)Ontario 1994 PWQO

North Fork Coeur d’Alene River at Enaville, Idaho, Hardness 11-23 mg/L, DOC 0.8 to 1.1 mg/L

Snake River leaving Yellowstone National Park, Wyoming (hardness 25-60 mg/L, pH 7 to 8.5, DOC 0.9 to 4.5 mg/L)

BLM- and hardness based chronic copper criterion, Snake River above Jackson Lake, WY

0

2

4

6

8

10

12

14

16

18

Apr

-199

3O

ct-1

993

Apr

-199

4O

ct-1

994

Apr

-199

5O

ct-1

995

Apr

-199

6O

ct-1

996

Apr

-199

7O

ct-1

997

Apr

-199

8O

ct-1

998

Apr

-199

9O

ct-1

999

Apr

-200

0O

ct-2

000

Apr

-200

1O

ct-2

001

Apr

-200

2O

ct-2

002

Apr

-200

3O

ct-2

003

Apr

-200

4

Date

Co

pp

er

(µg

/l)

BLM-based CCC (µg/L)

Hardness-capped CCC(NTR, µg/L)

Ontario 1994 PWQO

CWQG (1987)

Copper contaminated western mountain stream, Panther Creek, Idaho (DOC 1.1 to 4.6 mg/L, hardness 25-50, pH 7.5 to 8.6)

0

5

10

15

20

25

1994

Co

pp

er

(µg

/l)

0

1

2

3

4

5

DO

C (

mg

/L)

BLM-CCC

Hardness-equation criteria

DOC

Data from Stratus Consulting

Copper and DOC concentrations rose together during early snowmelt

0

20

40

60

80

100

120

140

160

1994

Co

pp

er

(µg

/l)

0

1

2

3

4

5

DO

C (

mg

/L)

BLM-CCC

Ambient CuDOC

Data from Stratus Consulting

Extrapolating patterns to post-remedial conditions

0

5

10

15

20

25

December March May July

Season

Cu

(µ

g/L

)

0

1

2

3

4

5

DO

C (

mg

/L)

BLM-CCC (1994)

Cu (2005)

DOC (1994)

0

5

10

15

20

25

December March May July

BLM-CCC (1994)

Cu (2005)

Hardness-CCC(1994)

DOC and pH data quality are important!

Chronic copper criteria: Teton River at St. Anthony, ID USGS 13055000

0

10

20

30

40

50

60

70

80

90

Jan-93 Aug-93 Mar-94 Sep-94 Apr-95 Oct-95

Cu

(µ

g/L

)

0

2

4

6

8

10

12

DO

C (

mg

/L)

BLM-based CCC (µg/L, diss.)

DOC

What’s happened in September 93?

DOC and pH data quality are important!

Beware USGS DOC data prior to 1994!

25%

75%

50%

95%

5% 25%75%50%

95%

5%

Pre-1994 1994 and later0

2

4

6

8

10

12

DO

C (

mg

/L)

Columbia River between Northport, WA and Trail, BC

APre-1994

B1994 and later

0

2

4

6

8

10

12

DO

C (

mg/

L)Colorado River downstream of Glen Canyon Dam, Arizona

25%

75%

50%

95%

5%

25%

75%

50%

95%

5%

Pre-1994 1994 and later0

2

4

6

8

10

12

14

16

18

20

DO

C (

mg/

L)

Neuse River, North Carolina coastal plain

10

100

1,000

10 100 1,000

Measured Cu LC50s (µg/L)

Pre

dic

ted

Cu

LC

50

s (

µg

/L) y = 0.80x + 40

r2 = 0.88

Data originally from Erickson 1996

Assuming DOC as 1.1 mg/L, HydroQual’s 2003 LA50 of 7.32(DOC not measured)

10

100

1,000

10 100 1,000


Predicted Cu LC50s (µg/L)

10

100

1,000

10 100 1,000



Assuming DOC as 1.35 mg/L, EPA’s 2003 LA50 of 3.56

Fathead minnows in low alkalinity Precambrian Shield Lakes (Data from Welsh et al., 1993).

Photo courtesy of Paul Welch

1

10

100

1,000

1 10 100 1,000



Welsh et al. (1993)

Welsh et al. (1996)

LA50 7.32, no Mg, April 2003DOC 100% reactive as 90% FA, 10% HA

1

10

100

1,000

1 10 100 1,000

Measured Cu LC50s (µg/L)P

red

icte

d C

u L

C5

0s

(µ

g/L

)

Welsh et al. (1993)

Welsh et al. (1996)

Welsh et al. (1993,1996) using HydroQual's 2007 default LA50of 5.48 includes Mg,assuming that 100% DOC is Cu-reactive

1

10

100

1,000

1 10 100 1,000


Pre

dic

ted

Cu

LC

50

s (

µg

/L)

Welsh et al. (1993)

Welsh et al. (1996)

Welsh et al. (1993,1996) using EPA's 2003, recalculating a LA50 6.313 assuming that 50% of DOC is Cu-reactive

DOC 50% Cu-reactiveLA50 6.313, no Mg(Recalculated from EPA 2003)

DOC 100% Cu-reactiveLA50 5.48, includes Mg, (6-10-2007) (default)

Model LA50: 7.32 nmol Cu/g gill

Modified LA50: 0.2 nmol Cu/g gill

Fathead minnows in low alkalinity South Carolina piedmont streams

(VanGenderen et al., 2005).

(top) DOC 50 % Cu-reactive,LA50: 6.313 nmol Cu/g gill

(bottom) DOC 100% Cu-reactive,LA50: 0.2 nmol Cu/g gill

Using EPA’s 2003 updated dataset and assuming 50% of DOC is Cu-reactive

(data from VanGenderen et al., 2005).

1

10

100

1,000

1 10 100 1,000

Measured 48-hr Cu LC50s (µg/L)

Pre

dic

ted

96

-hr

Cu

LC

50

s (

µg

/L)

y = 0.86x + 38

r2 = 0.79

VanGenderen et al. (2005) using EPA's 2003 LA50, recalculated assuming that 50% of DOC is Cu-reactive

Fatmucket, Lampsilis siliquoidea

< 0.3mm

Data from Ning Wang, USGS, Columbia, Missouri, et al., in prep.,

Acute tests in waters with variable hardness and different DOC sources

Photos by Doug Hardesty, USGS

Fatmucket mussel

DOC (mg C/L)

0 2 4 6 8 10 12

Dis

solv

ed C

u E

C50

( g

/L)

0

100

200

300

400Pond, r2=0.92Eagle Bluffs, r2=0.96Ditch #6, r2=0.92Luther Marsh, r2=0.97Humic acid, r2=0.97

A. Assume DOC is 100% reactive as 90% FA, 10% HA, (LA50 0.0605 nmol Cu/g gill)

Fatmucket

1

10

100

1000

1 10 100 1000

Measured Cu EC50s (µg/L)

Pre

dict

ed C

u E

C50

s (µ

g/L)

Pond

Eagle Bluffs

Ditch #6

Luther Marsh

Humic acid

Variablehardness Reference tests

y = 1.376x - 2.67

r 2 = 0.88p <0.001(pooling all groups)

1

10

100

1000

1 10 100 1000

Measured Cu EC50s (µg/L)

y = 0.90x + 12.1

r 2 = 0.87p <0.001(pooling all groups)

B. Assume DOC is 50% reactive as FA ((LA50 0.1916 nmol Cu/g gill)

B.

A.

Fatmucket mussel: hardness vs. BLM as predictor of toxicity

0 100 200 300 400 5000

100

200

300

400

500

Mea

sure

d E

C50

(µ

g/L)

BLM predicted EC50 (µg/L)

Pond Eagle Bluffs Ditch #6 Luther Marsh Humic Acid Variable Hardness Reference tests

50 100 150 200 250 3000

100

200

300

400

500

Mea

sure

d E

C50

(µ

g/L)

Hardness as mg/L CaCO3

y = 0.37x +27.2r2 = 0.05P =0.2(pooling all groups)

y = 0.96x - 0.207r2 = 0.9P <0.001(pooling all groups)

95% prediction bands

Escanaba River, Michigan photo, wikipedia.org

Ceriodaphnia dubia~25 natural waters, Mostly hardwater, (17-185 mg/L CaCO3), DOC 0.8 to 30 mg/L

GLEC, 2006(Tyler Linton)

Escanaba River, Michigan photo, wikipedia.org

1

10

100

1,000

1 10 100 1,000

Measured Cu LC50s (µg/L)P

red

icte

d C

u L

C5

0s

(µ

g/L

)

Natural waters

Mod hard reference tests

1

10

100

1,000

1 10 100 1,000


Pre

dic

ted

Cu

LC

50

s (

µg

/L)

Natural waters

Mod hard water referencetestsDOC 50% Cu-reactive

LA50 0.2378, no Mg(Recalculated from EPA 2003)

DOC 100% Cu-reactiveLA50 0.0701, includes Mg, (6-10-2007) (default)

Ceriodaphnia dubia

Hyalella azteca

1

10

100

1000

1 10 100 1000

Observed Cu LC50s (µg/L)

Pred

icte

d C

u L

C50

s (µ

g/L

)

NOM varies (Welsh 1996)

pH,Ca vary (48hr, Collyard 2002)

pH varies (Schubauer 1993)

NOM series y = 1.3137x - 7.1126r2 = = 0.9923

Doug Hardesty, USGS

Assume DOC is 50% reactive as FA

Assume DOC is 100% reactive as 90% FA, 10% HA

Rainbow trout flow-through tests using natural and lab waters, DOC <0.11 to 2.0 mg/L.

Welsh, Lipton, and Maest, (Stratus Consulting)

Josh Lipton, Stratus Consulting

1

10

100

1 10 100


Pre

dic

ted

Cu

LC

50

s (

µg

/L)

Flow through

Renewal

y = 0.99x + 3.27r2 = 0.58

<

1

10

100

1 10 100


Pre

dic

ted

Cu

LC

50

s (

µg

/L)

y = 0.85x + 4.0

r2 = 0.61

Chinook salmon, Sacramento River and lab waters (default)

Chinook salmon, Sacramento River and lab waters (50% AFA)

1

10

100

1 10 100


Pre

dic

ted

Cu

LC

50

s

(µg

/L)

y = 0.62x + 3.63

r2 = 0.62



Chinook salmon flow-through tests using natural and lab waters, DOC 0.11 to 1.4 mg/L.

Welsh, Lipton, and Maest, (Stratus Consulting)

Josh Lipton, Stratus Consulting

Rainbow trout, renewal exposures

BLM Predicted vs. observed rainbow trout LC50s, in renewal tests using lab and site waters, hardwater, DOC from <1 to 11 mg/L, 3 of 4 seasonal rounds of testing (all data from the 1st of 4 rounds discarded for questionable DOC data).

ENSR. 1996. Development of site-specific water quality criteria for copper in the upper Clark Fork River: Phase III WER Program testing results. ENSR Consulting and Engineering, 0480-277, Fort Collins, Colo.

10

100

1,000

10 100 1,000


Pred

icte

d C

u L

C50

s (µ

g/L

)

Rainbow trout 96-h LC50

1:1 Line (perfect agreement)

2:1 Line (0.5X less toxic thanpredicted)1:2 Line (2X more toxic thanpredicted)

y = 0.6847x + 17.233R2 = 0.4752

10

100

1,000

10 100 1,000


Pred

icte

d C

u L

C50

s (µ

g/L

)

Rainbow trout 96-h LC50

1:1 Line (perfect agreement)

2:1 Line (0.5X less toxic thanpredicted)1:2 Line (2X more toxic thanpredicted)

y = 0.51x + 33.927R2 = 0.617



Some Bad News

1

10

100

1000

1 10 100 1000


Pre

dic

ted

Cu

LC

50

s (µ

g/L

)

Using BLM v2.1.2 (Mg ignored)

Using v2.2.3 (Mg included)

Rainbow trout 96h LC50s, uniform total hardness with varying Ca and Mg, uniform low DOC, Welsh et al 2000

Rainbow trout 96h LC50s, uniform total hardness with varying Ca and Mg, uniform low DOC, Welsh et al 2000

1

10

100

1000

1 10 100 1000


Pre

dict

ed C

u LC

50s

(µg/

L)

DOC cocktail equivalents

Actual DOC cocktail mass

BLM Predicted vs. observed rainbow trout LC50s, varying DOC equivalents from O.3 to 16 mg/L, (actual DOC mass 0.11 to 0.84 mg/L) in lab water of with

hardness of 24 mg/L CaCO3, Marr et al 1999, Panther Creek DOC analogue

Testing DOC “equivalents” that matched natural DOM for binding affinity and complexation. DOC equivalents ranged O.3 to 16 mg/L, (actual DOC mass 0.11 to 0.84 mg/L) in lab water of with hardness of 24 mg/L CaCO3,

Marr et al 1999, Panther Creek DOC

Chronic EC10s

DOC 50% reactive, as AFA

0.1

1

10

100

0.1 1 10 100


Pred

icte

d C

u L

C50

s (µ

g/L

)

Rainbow trout

Brook trout

Fathead minnow

Chinook salmon

DOC 50% reactive, as AFA

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40Observed Cu LC50s (µg/L)

Pre

dict

ed C

u L

C50

s (µ

g/L

)

Rainbow trout

Brook trout

Fathead minnow

Chinook salmon

Rainbow trout (30-120d growth)• Besser et al, 2005• Hansen et al, 2002• Marr et al., 1996• Seim et al. 1984

Brook trout (2-22 months)• McKim et al. 1971, 1974• Sauter et al. 1976

Fathead Minnow (21-days to 11 months)• Mount 1968• Welsh 1996• Besser et al. 2005

Chinook salmon, 120d (treated as a rainbow trout)• Chapman 1982

Reductions in the olfactory response to a natural odorant (serine) following short-term (30 min) exposure to 20 µg/L dissolved copper

(McIntyre et al., ES&T, 2008)

Photo: Carla Stehr, National Marine Fisheries Service, Seattle

Median olfaction IC50s assuming 100% of DOC is Cu reactive (model default)

0

5

10

15

20

25

30

35

40

0 10 20 30 40

Median olfaction IC50s (µg/L)

BL

M P

red

icte

d IC

50

s (

µg

/L)

Varying DOC

Varying Ca

Varying alkalinity

McIntyre olfaction IC50s assuming 50% of DOC is Cu reactive as FA

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40

Median olfaction IC50s (µg/L)

Pre

dic

ted

EC

50

s (

µg

/L)

Shayler Run, Ohio, USA

• Stream experimentally dosed with copper, 1968-1972

• Integrated long-term field, streamside, and laboratory toxicity studies

• High calcium limestone geology

• DOC from natural and sewage sources

Geckler and others, 1976. Validity of laboratory tests for predicting copper toxicity in streams. EPA 600/3-76-116

Photo from Geckler and others, 1976

0

10

20

30

40

50

60

70

80

90

Feb-70 Aug-70 Mar-71 Sep-71 Apr-72 Oct-72 May-73

BLM and field effects –Ohio Stream

• Threshold for adverse effects from • Full life cycle streamside toxicity tests with native fish• Fish behavioral changes in stream

Cu (µg/L)

BLM chronic criterion

Safe from adverse effects (range)

Convict Creek, California, USA

• Sierra Nevada stream experimentally dosed with copper for 1 yr

• Measured effects on stream metabolism and macroinvertebrate community

• Low calcium granitic geology

• Most BLM parameters measured – except DOC

• Single DOC site value of 3.7 mg/L; average DOC in High Sierra Lakes estimated at 1.8 mg/L.

Photo courtesy of Daniel Dawson, Sierra Nevada Aquatic Research Laboratory

0

3

6

9

12

15

18

Aug Oct Jan Apr Jul Oct

BLM-chronic criterion (DOC 3.7 mg/L)

Stream eco-strucure LOEC

Stream eco-function LOEC; eco-structure NOEC

BLM-chronic criterion (avg. high lakes DOC, 1.8 mg/L)

BLM and field effects - Sierra Nevada stream

Copper (µg/L)

1979 1980

Sources:Leland and Carter, Freshwater Biology,1984, 1985, 1989Brooks and others, Ecosystems, 2005

BLM and experimental streams

New River near Blacksburg, VA, New River Valley Bird Club

Chronic BLM-based copper criteria and macroinvertebrate effects concentrations: New River at Glen Lyn, VA

0.0

5.0

10.0

15.0

20.0

25.0

23-Aug-96 1-Dec-96 11-Mar-97 19-Jun-97 27-Sep-97 5-Jan-98

Dis

solv

ed C

op

per

(u

g/L

)

BLM-based chronic criteria (µg/L,diss.)

Loss of 96% of mayflies, 60% of totalabundance, and 47% of taxa; 42-dexposure10-d EC50 (total individuals)

10-d EC50 (total individuals)

Loss of 96% of mayflies, 60% of totalabundance, and 47% of taxa; 42-dexposure

Macroinvertebrate exposures in August 1987, no DOC data.

1997 pH and inorganic data similar, assuming DOC is similar

Clements et al., CJFAS., 1988

Clements et al., Aq. Tox., 1989

30 week aquatic microcosm experiment

S.F. Hedtke, Aquatic Tox., 1984

0.1

1

10

100

1000

Control NOEC LOEC Severe Severe Severe

Microcosm community effects

Dis

s. C

u (

ug

/L)

BLM-CCC-high

BLM-CCC Low

Treatments (µg/L)

I think I learned ...

1. BLM performed well across a broad range of waters and with diverse taxa

2. Paucity of chronic toxicity data from varied waters. Chemosensory testing valuable, esp. tests of whether effects are ecologically relevant

3. Experimental stream studies could be compelling4. BLM too sensitive to DOC?

Assuming 100% of DOC is Cu-reactive may be a factor.Overprotective at low DOC and underprotective higher DOC.

5. Assuming 50% of DOC is Cu-reactive fulvic acid improved predictions in most datasets from natural waters.No datasets were made much worse by the 50% AFA assumption.

6. Adding Mg to the model not helpful in these datasets. Perhaps limit to site-specific situations where Mg is important.

7. Emphasis on equilibrating waters in FT tests seems misplaced.8. Quality of DOC and pH measurements critical. Recommend DOC

detection to at least 0.3 mg/L in field data, 0.1 if testing synthetic waters

Besser, J. M., N. Wang, F. J. Dwyer, F. L. Mayer, and C. G. Ingersoll. 2005. Assessing contaminant sensitivity of endangered and threatened fishes: 2. Chronic toxicity of copper and pentachlorophenol to two endangered species and two surrogate species. Archives of Environmental Contamination and Toxicology. 48(2): 155-165.

Brooks, P. D., C. M. O’Reilly, S. A. Diamond, D. H. Campbell, R. Knapp, D. Bradford, P. S. Corn, B. Hossack, and K. Tonnessen. 2005. Spatial and temporal variability in the amount and source of dissolved organic carbon: implications for ultraviolet exposure in amphibian habitats. Ecosystems. 8(5): 478 - 487.

Chapman, G. A. 1982. Chinook salmon early life stage tests with cadmium, copper, and zinc. Letter of December 6, 1982 to Charles Stephan, U.S. EPA Environmental Research Laboratory, Duluth. U.S. Environmental Protection Agency, Environmental Research Laboratory, Corvallis, Oregon (obtained via the USEPA Water Docket, http://www.epa.gov/ow/docket.html).

Clements, W. H., D. S. Cherry, and J. Cairns, Jr. 1988. The impact of heavy metals on macroinvertebrate communities: a comparison of observational and experimental results. Canadian Journal of Fisheries and Aquatic Sciences. 45(11): 2017-2025.

Clements, W. H., J. L. Farris, D. S. Cherry, and J. Cairns, Jr. 1989. The influence of water quality on macroinvertebrate community responses to copper in outdoor experimental streams. Aquatic Toxicology. 14(3): 249-262.

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Documents

U.S. Department of the Interior U.S. Geological Survey The accuracy and protectiveness of Biotic Ligand Model (BLM) toxicity predictions with copper Christopher