BY:  VRUSHALI LELE THESIS DIRECTOR: DR. PETER DEFUR
INTRODUCTION/BACKGROUND METHODS RESULTS DISCUSSION/ CONCLUSION
Framework developed by the U.S. EPA in 2003 EPA defines CRA as “an analysis, characterization, and possible quantification of the combined risks to health or the environment from multiple agents or stressors” Holistic Approach  www.epa.gov
Risk Characterization step widely used in Ecological/Human Risk Assessments HQ=  Estimated Exposure/Expected Levels Screening Value Levels E.g: HQ= Cd conc. measured at a site= 21.3 mg/kg  Screening Toxicity Value  = 1.9 mg/kg HQ> 1 Adverse effects likely to occur Deer Mouse is at risk! =11.2>1
SCIENTIFIC NAME: Crassostrea virginica A.K.A : American Oyster DISTRIBUTION: Gulf of St. Lawrence, Canada to Gulf of Mexico TEMPERATURE RANGE:  Between 1-36°C SALINITY RANGE:  Between 5-30 ppt
In 1608, Capt. John Smith wrote that “oysters lay as thick as stones”. In 1701, a Swiss visitor to the Chesapeake Francis Louis Michel observed “The abundance of oysters is incredible. There are whole banks of them so that the ships must avoid them. . . . ” By 1875,  a total of 17 million bushels removed from  the Chesapeake and grew into Oyster Wars. About 1959, Oyster Wars ended.
ECOLOGICAL:  Filter Feeders Oyster Reefs ECONOMICAL: Creating Jobs Three quarters of the Bay’s oyster reefs were removed between the Civil War and the 1920s, leaving huge mounds of shells like this
Adding up the cumulative annual losses over the last three decades shows that the decline of oysters has meant a loss of more than $4 billion for the economies of Maryland and Virginia. —NOAA CBF  Report
FACTORS FOR DECLINE: Overfishing, Pollution, Disturbance in Habitat,  Diseases like  MSX and Dermo
Hypoxia-  Decrease in DO levels in water Hypercapnia- Coexists with hypoxia, increase in CO 2 Acidosis- Decrease in pH
Temperature and salinity affects every physiological function including the oxygen uptake of oysters Hypoxia makes them more vulnerable to infectious diseases ( like MSX and Dermo) ↑  Salinity, ↓ Temp    ↓ Oxygen Uptake (hypoxia) Moderate hypercapnia    ↓ Oxygen Uptake All co-exist, considered as “Multiple Stressors”
IMPACT OF MULTIPLE STRESSORS TO OYSTERS
Agricultural/Industrial Runoff Point/Non Point Sources Eutrophi cation overharvesting of natural resources Sources Changes in Salinity, Temperature Hypoxia, Hypercapnia, Acidosis Vulnerability to infection Water quality deterioration, habitat alteration Physiological functions like reproduction, respiration Eastern Oysters Invertebrates depending on oyster reefs, fishes etc. Sea food consumers, economy Oxygen Uptake of Oysters Vulnerability to diseases Stressors Pathways Receptors Endpoints CONCEPTUAL MODEL FOR THE STUDY +
Study the cumulative risks to the Eastern Oysters in the James River subjected to multiple stressors (S, T, O 2 , CO 2 ) Calculate the oxygen uptake under multiple conditions Evaluate the effectiveness of the HQ Method
INTRODUCTION/BACKGROUND METHODS RESULTS DISCUSSION/ CONCLUSION
Water quality monitoring data collected from VA- Dept of Environmental Quality Experimental Data from two studies : Shumway and Koehn, 1982 Willson and Burnett, 2000 Data sorted on two conditions : Salinity Range - 7 to 28 ppt Temp Range - 10 to 30 °C
Map of monitoring stations used in the study
DO (Hypoxia) Calculated slope (m), intercept (c), and substituted salinity values (x) from dataset (y = mx+c) Multiplied Q 10  values from the study with O 2  uptake from step 1 Calculated relative change and multiplied with  O 2  uptake  values from step 2 SEQUENCE OF STEPS USED TO CALCULATE FINAL OXYGEN UPTAKE Temperature Salinity Shumway and Koehn, 1982 Salinity: 7-28ppt Temp: 10-30°C
Final O 2  uptake in ml/hr  gm -1  wet weight  Multiplied step 4  O 2  uptake by 0.0224  to convert µmol/hr to ml/hr and 14.8 to convert dry  weight to wet weight Calculated the relative change  and multiplied with O 2  uptake value from step 3 CO 2  (Hypercapnia) Willson and Burnett,2000 Salinity: 25 ppt Temp: 25°C
Final O 2  uptake =  (mx+c)*Q 10 O 2(S) * RC O 2(T) *RC’*W*G where RC & RC’= relative changes for adjusting O 2  and CO 2  levels   W = weight constant   G = gas constant Final O 2  uptake in ml/hr gm -1  wet weight (adjusted for S,T, O 2 , CO 2 )
Statistical Analysis software (Oracle) that uses probability distributions for each parameter Monte-Carlo Analysis: randomly generates values to produce a probability distribution Using same model equation created the CB model Assumptions (uncertain variables): Salinity, Temperature, and DO Forecast: Calculated Oxygen Uptake (ml/hr)
Triangular Distributions- choose min, max and likeliest values to accommodate S and T ranges Ran 10,000 trials/simulations SENSITIVITY ANALYSIS: Understand the influence and variance of each parameter (assumption) on the forecast and model Normal Distribution Triangular Distribution
Screenshot of Crystal Ball Model In Excel Final O 2  uptake = (mx+c)*Q 10 O 2(S) * RC O 2(T) *RC’*W*G
INTRODUCTION/BACKGROUND METHODS RESULTS DISCUSSION/ CONCLUSION
CUMULATIVE PROBABILITY DISTRIBUTION OF OXYGEN UPTAKE USING CRYSTAL BALL
SENSITIVITY ANALYSIS CHART GENERATED BY CRYSTAL BALL
Salinity was the most influential assumption in the model followed by temperature  Conditions are favorable for pathogens growth and make the oysters “vulnerable” to diseases like MSX and Dermo When multiple risks presented as probability, the risk could be the product of individual risks, not sum
Traditional Risk Assessment Single endpoints, sources,  stressors, pathways and route of exposure One-size fits all responses Eg: Studying the health risks of consuming methylmercury contaminated fish. Emerging Risk Assessment  Multiple endpoints, sources, stressors, pathways and routes of exposure Case-specific responses Eg: Present Study ( Refer Conceptual Model Handout)
HQ=  Site Exposure/Expected Levels Screening Value Levels E.g: HQ= Cd conc. measured at a site= 21.3 mg/kg  Screening Toxicity Value  = 1.9 mg/kg HQ> 1 Adverse effects likely to occur LIMITATIONS  Does not represent magnitude of the risk Measure of hazard and not risk =11.2>1
Could be inappropriate for quantifying multiple risks  LIMITATIONS: Estimates calculated for single-stressor, single-response Does not represent probability of the risk or vulnerability of populations exposed to the risk Cannot capture risks associated to social, psychologic, economical  stresses  DO Sat =  0.8 0.3  = ? 0.3 0.8  = 0.625 < 1
Add in more stressors like acidosis Trying the model on other river systems Explore vulnerability aspect Laboratory studies
Special thanks to Dr. Peter deFur, Dr. Clifford Fox and Dr. Jeffery Chanat. Dr. Greg Garman, Director of CES and ex-officio. My friends, Paras Gandhi, Dr. Richard Gayle, Monika Patel, Rachel Bullene, and Maurice Coles, Mr. and Mrs. Sarkozi and my parents
?
Slide 3: www.epa.gov Slide 5: www.whoi.edu  Slide 7: www.aquaviews.net, CBF Report, www.easternshoremagazine.com Slide 8: CBF Report Slide 9: http://www.chesapeakebay.net/status_oysterspatjames.aspx?menuitem=19686 Slide 10: www.epa.qld.gov.au Slide 12: http://chesapeakebay.noaa.gov/oysters/oyster-reefs Slide 33: www. mchumor.com

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Thesis_Presentation

  • 1. BY: VRUSHALI LELE THESIS DIRECTOR: DR. PETER DEFUR
  • 3. Framework developed by the U.S. EPA in 2003 EPA defines CRA as “an analysis, characterization, and possible quantification of the combined risks to health or the environment from multiple agents or stressors” Holistic Approach www.epa.gov
  • 4. Risk Characterization step widely used in Ecological/Human Risk Assessments HQ= Estimated Exposure/Expected Levels Screening Value Levels E.g: HQ= Cd conc. measured at a site= 21.3 mg/kg Screening Toxicity Value = 1.9 mg/kg HQ> 1 Adverse effects likely to occur Deer Mouse is at risk! =11.2>1
  • 5. SCIENTIFIC NAME: Crassostrea virginica A.K.A : American Oyster DISTRIBUTION: Gulf of St. Lawrence, Canada to Gulf of Mexico TEMPERATURE RANGE: Between 1-36°C SALINITY RANGE: Between 5-30 ppt
  • 6. In 1608, Capt. John Smith wrote that “oysters lay as thick as stones”. In 1701, a Swiss visitor to the Chesapeake Francis Louis Michel observed “The abundance of oysters is incredible. There are whole banks of them so that the ships must avoid them. . . . ” By 1875, a total of 17 million bushels removed from the Chesapeake and grew into Oyster Wars. About 1959, Oyster Wars ended.
  • 7. ECOLOGICAL: Filter Feeders Oyster Reefs ECONOMICAL: Creating Jobs Three quarters of the Bay’s oyster reefs were removed between the Civil War and the 1920s, leaving huge mounds of shells like this
  • 8. Adding up the cumulative annual losses over the last three decades shows that the decline of oysters has meant a loss of more than $4 billion for the economies of Maryland and Virginia. —NOAA CBF Report
  • 9. FACTORS FOR DECLINE: Overfishing, Pollution, Disturbance in Habitat, Diseases like MSX and Dermo
  • 10. Hypoxia- Decrease in DO levels in water Hypercapnia- Coexists with hypoxia, increase in CO 2 Acidosis- Decrease in pH
  • 11. Temperature and salinity affects every physiological function including the oxygen uptake of oysters Hypoxia makes them more vulnerable to infectious diseases ( like MSX and Dermo) ↑ Salinity, ↓ Temp  ↓ Oxygen Uptake (hypoxia) Moderate hypercapnia  ↓ Oxygen Uptake All co-exist, considered as “Multiple Stressors”
  • 12. IMPACT OF MULTIPLE STRESSORS TO OYSTERS
  • 13. Agricultural/Industrial Runoff Point/Non Point Sources Eutrophi cation overharvesting of natural resources Sources Changes in Salinity, Temperature Hypoxia, Hypercapnia, Acidosis Vulnerability to infection Water quality deterioration, habitat alteration Physiological functions like reproduction, respiration Eastern Oysters Invertebrates depending on oyster reefs, fishes etc. Sea food consumers, economy Oxygen Uptake of Oysters Vulnerability to diseases Stressors Pathways Receptors Endpoints CONCEPTUAL MODEL FOR THE STUDY +
  • 14. Study the cumulative risks to the Eastern Oysters in the James River subjected to multiple stressors (S, T, O 2 , CO 2 ) Calculate the oxygen uptake under multiple conditions Evaluate the effectiveness of the HQ Method
  • 15. INTRODUCTION/BACKGROUND METHODS RESULTS DISCUSSION/ CONCLUSION
  • 16. Water quality monitoring data collected from VA- Dept of Environmental Quality Experimental Data from two studies : Shumway and Koehn, 1982 Willson and Burnett, 2000 Data sorted on two conditions : Salinity Range - 7 to 28 ppt Temp Range - 10 to 30 °C
  • 17. Map of monitoring stations used in the study
  • 18. DO (Hypoxia) Calculated slope (m), intercept (c), and substituted salinity values (x) from dataset (y = mx+c) Multiplied Q 10 values from the study with O 2 uptake from step 1 Calculated relative change and multiplied with O 2 uptake values from step 2 SEQUENCE OF STEPS USED TO CALCULATE FINAL OXYGEN UPTAKE Temperature Salinity Shumway and Koehn, 1982 Salinity: 7-28ppt Temp: 10-30°C
  • 19. Final O 2 uptake in ml/hr gm -1 wet weight Multiplied step 4 O 2 uptake by 0.0224 to convert µmol/hr to ml/hr and 14.8 to convert dry weight to wet weight Calculated the relative change and multiplied with O 2 uptake value from step 3 CO 2 (Hypercapnia) Willson and Burnett,2000 Salinity: 25 ppt Temp: 25°C
  • 20. Final O 2 uptake = (mx+c)*Q 10 O 2(S) * RC O 2(T) *RC’*W*G where RC & RC’= relative changes for adjusting O 2 and CO 2 levels W = weight constant G = gas constant Final O 2 uptake in ml/hr gm -1 wet weight (adjusted for S,T, O 2 , CO 2 )
  • 21. Statistical Analysis software (Oracle) that uses probability distributions for each parameter Monte-Carlo Analysis: randomly generates values to produce a probability distribution Using same model equation created the CB model Assumptions (uncertain variables): Salinity, Temperature, and DO Forecast: Calculated Oxygen Uptake (ml/hr)
  • 22. Triangular Distributions- choose min, max and likeliest values to accommodate S and T ranges Ran 10,000 trials/simulations SENSITIVITY ANALYSIS: Understand the influence and variance of each parameter (assumption) on the forecast and model Normal Distribution Triangular Distribution
  • 23. Screenshot of Crystal Ball Model In Excel Final O 2 uptake = (mx+c)*Q 10 O 2(S) * RC O 2(T) *RC’*W*G
  • 24. INTRODUCTION/BACKGROUND METHODS RESULTS DISCUSSION/ CONCLUSION
  • 25. CUMULATIVE PROBABILITY DISTRIBUTION OF OXYGEN UPTAKE USING CRYSTAL BALL
  • 26. SENSITIVITY ANALYSIS CHART GENERATED BY CRYSTAL BALL
  • 27. Salinity was the most influential assumption in the model followed by temperature Conditions are favorable for pathogens growth and make the oysters “vulnerable” to diseases like MSX and Dermo When multiple risks presented as probability, the risk could be the product of individual risks, not sum
  • 28. Traditional Risk Assessment Single endpoints, sources, stressors, pathways and route of exposure One-size fits all responses Eg: Studying the health risks of consuming methylmercury contaminated fish. Emerging Risk Assessment Multiple endpoints, sources, stressors, pathways and routes of exposure Case-specific responses Eg: Present Study ( Refer Conceptual Model Handout)
  • 29. HQ= Site Exposure/Expected Levels Screening Value Levels E.g: HQ= Cd conc. measured at a site= 21.3 mg/kg Screening Toxicity Value = 1.9 mg/kg HQ> 1 Adverse effects likely to occur LIMITATIONS Does not represent magnitude of the risk Measure of hazard and not risk =11.2>1
  • 30. Could be inappropriate for quantifying multiple risks LIMITATIONS: Estimates calculated for single-stressor, single-response Does not represent probability of the risk or vulnerability of populations exposed to the risk Cannot capture risks associated to social, psychologic, economical stresses DO Sat = 0.8 0.3 = ? 0.3 0.8 = 0.625 < 1
  • 31. Add in more stressors like acidosis Trying the model on other river systems Explore vulnerability aspect Laboratory studies
  • 32. Special thanks to Dr. Peter deFur, Dr. Clifford Fox and Dr. Jeffery Chanat. Dr. Greg Garman, Director of CES and ex-officio. My friends, Paras Gandhi, Dr. Richard Gayle, Monika Patel, Rachel Bullene, and Maurice Coles, Mr. and Mrs. Sarkozi and my parents
  • 33. ?
  • 34. Slide 3: www.epa.gov Slide 5: www.whoi.edu Slide 7: www.aquaviews.net, CBF Report, www.easternshoremagazine.com Slide 8: CBF Report Slide 9: http://www.chesapeakebay.net/status_oysterspatjames.aspx?menuitem=19686 Slide 10: www.epa.qld.gov.au Slide 12: http://chesapeakebay.noaa.gov/oysters/oyster-reefs Slide 33: www. mchumor.com

Editor's Notes

  • #6: The species name, virginica, was assigned because of the oysters’ predominance in the Virginia waters of the Chesapeake. Abundant in the Long Island Sound, Chesapeake Bay and Gulf of Mexico The American oyster typically lives in shallow, well-mixed estuaries, lagoons, and oceanic bays where it tolerates widely fluctuating water Temperatures and salinities. Why are temperature and salinity important?
  • #7: Descriptions of the oyster beds have been found in writings dating back to 1642, demonstrating the social and economic significance of the resource to early European settlers.
  • #8: Filter feeding activity may enhance water clarity, increasing light penetration and trapping contaminants entering coastal waters. Ecosystem Engineers
  • #10: Oyster spat are the juvenile &amp;quot;young of year&amp;quot; or yearling stage. Spat data indicate that oysters are still able to spawn and have the potential for restoration. The data do not reflect survival to harvestable size, nor do they reflect population size in the Bay. Data are from the VIMS Fall Public Oyster Grounds Survey. Oyster spat per bushel of bottom cultch sampled are averaged from seven bars on the James River: Horsehead, Long Shoal, Wreck Shoals, Point of Shoals, Dry Shoal, Thomas Rock and Nansemond Ridge. The historical peak in the James is around 10 times that of the Maryland peak. Oyster spat set and growth to adult stages are affected by freshwater flows to the Bay. At lower salinities, although growth is slower and potential for spat set is lower, oyster diseases caused by MSX and Dermo are kept in check. However, extremely low salinities may result in high oyster mortality. At higher salinities, growth and spat set are generally higher, but the potential for diseases caused by MSX and Dermo is greater. Virginia waters are generally higher in salinity compared to Maryland waters. Although spat set is higher in VA (compared to MD), survivorship to market size is typically lower than in MD.
  • #11: Chesapeake bay- as a hypoxic body
  • #12: Amongst all the abiotic factors, synergistic effects of temperature and salinity probably have the most significant effects on C. virginica . As numerous researchers have pointed out “two or more environmental factors acting in concert have profound biological consequences than any one of those factors acting independently”.
  • #14: Integrating the concepts of CRA in this study by taking elements from CRA Anthropogenic activities like
  • #21: (mx+c) = equation for a straight line Q 10 = factor by which the reaction rate increases for every 10-degree rise O 2(S) = Salinity adjusted O2 uptake RC = Relative change calculated relative change for adjusting changing DO oxygen uptake adjusted to temperature in ml/hr gm wet weight RCʹ = calculated relative change for adjusting changing CO 2 levels W = weight constant for converting dry weight into wet weight of the organism G = gas constant for converting µmole/hr into ml/hr
  • #28: Sensitivity analysis calculated when multiple risks of two or more independent stressors act simultaneously and are presented as a probability, the risk is the product of individual risks, not the sum (S. Ferenc et al., 1999). In this study, in order to calculate the oxygen uptake of oysters, cumulative risks (salinity, temperature, hypoxia and hypercapnia) were sequentially multiplied to understand if there was “synergy” between the risks. Therefore, cumulative risks need to multiplied and not added.
  • #29: stressors are not limited to chemicals. They could be biological, physical, social, economical, psychological, behavioral stresses, or natural or anthropologic activities that could disturb the equilibrium of any system. The third feature calls for combining the risks from the multiple stressors.
  • #31: 0.8- Loose distribution, loose the tail-single estimate