Thesis_Presentation

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A brief outline of my thesis at VCU

Transcript of Thesis_Presentation

BY: BY:

VRUSHALI LELEVRUSHALI LELE

THESIS DIRECTOR: DR. PETER DEFURTHESIS DIRECTOR: DR. PETER DEFUR

INTRODUCTION/BACKGROUNDINTRODUCTION/BACKGROUND

METHODSMETHODS

RESULTSRESULTS

DISCUSSION/ CONCLUSIONDISCUSSION/ CONCLUSION

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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

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www.epa.gov

Risk Characterization step widely used in Ecological/Human Risk Assessments

HQ= Estimated Exposure/Expected LevelsScreening 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

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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

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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.

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ECOLOGICAL: Filter FeedersOyster Reefs ECONOMICAL:Creating Jobs

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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

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CBF Report

0

500

1000

1500

2000

2500

3000

35001947

1950

1960

1970

1980

1990

2000

2007

FACTORS FOR DECLINE: Overfishing, Pollution, Disturbance in Habitat, Diseases like MSX and Dermo

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Hypoxia- Decrease in DO levels in water Hypercapnia- Coexists with hypoxia, increase in CO2

Acidosis- Decrease in pH

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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”

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IMPACT OF MULTIPLE STRESSORS TO OYSTERS

Agricultural/Industrial

Runoff

Point/Non Point

Sources

Eutrophication

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 13

+

Study the cumulative risks to the Eastern Oysters in the James River subjected to multiple stressors (S, T, O2, CO2)

Calculate the oxygen uptake under multiple conditions

Evaluate the effectiveness of the HQ Method

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INTRODUCTION/BACKGROUNDINTRODUCTION/BACKGROUND

METHODSMETHODS

RESULTSRESULTS

DISCUSSION/ CONCLUSIONDISCUSSION/ CONCLUSION

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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

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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 Q10 values from the study with O2 uptake from step 1

Calculated relative change and multiplied with O2 uptake values from step 2

SEQUENCE OF STEPS USED TO CALCULATE FINAL OXYGEN UPTAKE

Temperature

Salinity

Shumway and Koehn, 1982Salinity: 7-28pptTemp: 10-30°C

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Final O2 uptake in ml/hr gm-1 wet weight

Final O2 uptake in ml/hr gm-1 wet weight

Multiplied step 4 O2 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 O2 uptake value from step 3

CO2 (Hypercapnia)Willson and Burnett,2000Salinity: 25 pptTemp: 25°C

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Final O2 uptake =

(mx+c)*Q10O2(S)* RC O2(T)*RC’*W*G

where RC & RC’= relative changes for adjusting O2 and CO2 levels

W = weight constant

G = gas constant

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Final O2 uptake in ml/hr gm-1 wet weight (adjusted for S,T, O2, CO2)

Final O2 uptake in ml/hr gm-1 wet weight (adjusted for S,T, O2, CO2)

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)

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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

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Normal Distribution Triangular Distribution

Screenshot of Crystal Ball Model In Excel

Final O2 uptake = (mx+c)*Q10O2(S)* RC O2(T)*RC’*W*G23

INTRODUCTION/BACKGROUNDINTRODUCTION/BACKGROUND

METHODSMETHODS

RESULTSRESULTS

DISCUSSION/ CONCLUSIONDISCUSSION/ CONCLUSION

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CUMULATIVE PROBABILITY DISTRIBUTION OF OXYGEN UPTAKE USING CRYSTAL BALL

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SENSITIVITY ANALYSIS CHART GENERATED BY CRYSTAL BALL

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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

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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)

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HQ= Site Exposure/Expected LevelsScreening 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

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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 =

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0.80.3

= ?

0.30.8

= 0.625 < 1

Add in more stressors like acidosis Trying the model on other river systems Explore vulnerability aspect Laboratory studies

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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

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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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