1. Acute and Chronic Toxicity Testing

2. Standard Methods  Multiple methods have been standardized (certified) by multiple organizations American Society for Testing and Materials (ASTM) Organization for Economic Cooperation and Materials (OECD) – (Europe based) National Toxicology Program (NTP)  All above standardized protocols available from US EPA, Federal Register and researchers that developed the programs

3. Advantages of Standard Methods  Tests are uniform and comparable to previous results within the same or other laboratories  Can be replicated (confirmed) by other laboratories  Makes it easier for decision makers to accept test results  Logistics are simplified, developmental work already done  Methods establish baseline from which modifications can be made if necessary  Data generated can be combined with those from other laboratories for use in QSAR, ERA’s

4. Advantages of Standard Methods (con’t)  Detailed listing of apparatus, dilution water, test material, test organisms, etc  Experimental, analytical and documentation procedures are detailed  Acceptability criteria are listed

5. Disadvantages of Standard Methods  Often very specific  hard to apply to other situations or answer other questions  Tend to be used in inappropriate situations (research, cause and effect evaluation)  May not be applicable to natural environment

6. Acute vs. Chronic Toxicity Tests Can broadly classify toxicity tests based on length of exposure  Acute Toxicity test Drop dead testing Time = 2 days (invertebrates) to 4 d. (fish)  LD 50  LC 50  TLm (median tolerance dose)  EC 50 (effective concentration) Lose equilibrium, sit on bottom  “ecologically” dead Not very ecologically relevent but quick, relatively cheap (but still ~$700-1,200 per test)

7. Acute vs chronic toxicity testing (con’t)  Chronic toxicity testing Growth, reproduction More ecologically relevant data but takes longer, more expensive Shows effect at much lower dose Test requires much more “baby-sitting”

8. Acute Testing - theory  Population of organisms has normally distributed resistance to toxicants  acute toxicity test designed to identify mean response  Regulations allow 5% of species to be impacted  Most tests only use 2-3 species (up to 6)  not really enough to protect 95% of all species!

9. Acute Toxicity Test Organisms  Use of test species based on Lab hardiness Common Known life cycle Cheap Short-lived

10. Normal distribution of resistance/sensitivity Resistance (log [X] Frequency 5% allowable impact 0 100 Mean response Protected

11. Experimental design for toxicity tests Percent mortality Log [X] Integration of Freg. of response (i.e death) Looking for this area of response To save money while finding area of mean response  use a two step process

12. Step 1 – Screening test  Expose 5–10 organisms to 10 x increasing [ ] for 24-96 hours  Trying to determine range in which median lethal concentration (LC 50 ) will fall

13. Screening test 100%30%100% % Responding [X] mg/L 0 100 # dead none none some all RIP all RIP 00 Concen. 10 -3 10 -2 10 -1 10 0 10 1

14. Step 2 – Definitive test From previous results low = 10 -2 = 0.01 mg/L high = 10 0 = 1.0 mg/L  Run test using logarithmic scale of concentrations because organisms usually respond logarithmically to toxicants  Usually use at least 5 concentrations + control Control – checks toxicity of dilution water, health of test organisms, stress level of testing environment (test chambers, lighting, temperature, etc) If >10% of control organisms die  throw out test!  Use 10 – 30 organisms  randomly split up among tanks

15. Set up for definitive test – example 1 TreatmentDivisionConcentration (mg/L) 110 -2 0.01 2 10 -1.5 0.032 310 -1 0.1 4 10 -0.5 0.32 510 0 1.0 Control0.0

16. Set up for definitive test – example 2 low = 10 1 µg/L high = 10 3 TreatmentDivisionConcentration ( µ g/L) 110 3 1000 210 2.5 316 310 2 100 410 1.5 31 510 1 10 control0

17. Analysis of Toxicity Tests  Based on hypothesis that resistance to toxicants is normally distributed  Use a probit transformation to make data easier to analyze  Based on SD so each probit has a percentage attached to it  Mean response defined as probit = 5 so all probits are positive  easier to visualize  Can use probit analysis to calculate LC 50 because probit transformation will straighten the cumulative distribution line

18. Probit Analysis  Response of organisms to toxic chemicals = normal distribution  Cannot measure normal distribution directly because effect is cumulative, so graph as cumulative distribution Log Dose Cumulative distribution Dose # Responding Normal distribution

19. Log Dose Cumulative distribution % Mortality 0 50 100% Converting a curvilinear line to straight line  Difficult to evaluate a curved line  Conversion to a straight line would make evaluation easier Log Dose Probit Units 3 5 7 Straight line (easier to analyze) LD 50, TLM) Probit transformed

20. Note: probit forces data towards middle of distribution  good because most organisms are “average” in their response

21. Relationship between normal distribution and standard deviations 34.13% 13.6% 2.13% -2 -1 0 1 2 Standard deviations Mean

22. Difficult to deal with SD (34.13, 13.6, etc) so rename SD to probits 34.13% 13.6% 2.13% 3 4 5 6 7 Probits Mean

23. Example probit analysis Concentration (mg/L) Deaths% Control0/100 0.30/100 1 0 31/1010 4/1040 309/1090 10010/10100 Look at data  should be able to tell immediately that LC50 should be between 10 and 30 mg/L Graph  fit line by eye (approximately equal number above and below line)

24. Uses of LC 50 1. 1. Application factor LC 50 x n = ___ = allowable dose Good if do not have better information (chronic tests) 2. Rank hazards  lower LC 50 = more toxic 3. Lead to chronic testing  Remember: LC 50 does not provide an ecologically meaningful result  bad because trying to protect ecosystem  need more ecosystem level testing  Probit is trade-off between cost and getting sufficient data to make a decision about the environmental toxicity of a chemical

25. Chronic toxicity testing  Sublethal  Time = 7d. to 18 months  Endpoints are growth Reproduction  brood size (Ceriodaphnia dubia can have 2-3 broods in seven days)  Hatching success

26. Analysis of chronic tests  Analysis of Variance (hypothesis testing) Test for significant difference from control (C + 5 doses)  Regression analysis EC20 (concentration that causes 20% reduction relative to control)

27. Results of Analysis of Variance test C 1 3 10 30 100 Community Respiration (gC/L/d.) * * * Concentration of Hg (mg/L)

28. Determination of EC 20 10 μg 8 μg Control EC 20 eg. 1 mg/L = discharge limit Response (growth) Control response 20% reduction relative to control Dose

29. Ecosystem Tests ( microcosms, mesocosms)  AOV design (4 reps X 3 treat., 3 rep X 4)  Time = 1 – 2 years  $10 6 /year  Endpoints are Biomass Diversity Species richness Etc.

30. All toxicity tests try to determine level of toxicant which will or will not cause an effect  NOEC – No Observable Effect Concentration Highest conc not signficantly different from control  LOEC – Lowest Observable Effect Concentration Lowest test concentration that is significantly different from control  MATC – Maximum Allowable Toxicant Concentration Geometric mean of NOEC and LOEC Often called the “chronic value”

31. MATC MATC = √NOEC + LOEC

32. Results of Analysis of Variance test C 1 3 10 30 100 Community Respiration (gC/L/d.) * * * Concentration of Hg (mg/L)

33. Photo by R. Grippo If there is magic on earth, it is in water