ANALISIS EKOTOKSIKOLOGI Oleh Sudrajat FMIPA UNMUL 2010

1. ANALISIS EKOTOKSIKOLOGI Oleh Sudrajat FMIPA UNMUL 2010

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

3. Step 1 – Screening test • Expose 5–10 organisms to 10x increasing [ ] for 24-96 hours • Trying to determine range in which median lethal concentration (LC50) will fall

4. Screening test 0 100 % Responding [X] mg/L # dead none none some all RIP all RIP 30% 100% 100% 0 0 Concen. 10-3 10-2 10-1 100 101

5. Step 2 – Definitive test From previous results low = 10-2 = 0.01 mg/L high = 100 = 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

6. Set up for definitive test – example 1

7. Set up for definitive test – example 2 low = 101 µg/L high = 103

8. 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 LC50 because probit transformation will straighten the cumulative distribution line

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

10. Difficult to evaluate a curved line Conversion to a straight line would make evaluation easier Log Dose Log Dose Converting a curvilinear line to straight line Cumulative distribution Probit transformed % Mortality 0 50 100% Probit Units 3 5 7 Straight line (easier to analyze) LD50, TLM)

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

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

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

14. Example probit analysis 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)

15. Uses of LC50 • 1. Application factor • LC50 x n = ___ = allowable dose • Good if do not have better information (chronic tests) • Rank hazards  lower LC50 = more toxic • Lead to chronic testing • Remember: LC50 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