Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

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Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014 http://wp.vcu.edu/jamesriver/

Transcript of Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

Page 1: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

Science Advisory PanelData Analysis Workgroup

Paul BukaveckasJuly 23 2014

http://wp.vcu.edu/jamesriver/

Page 2: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

Are current CHLa standards protective of designated uses?

What are the threats to designated uses? Objective 1: identify metrics (e.g., DO, pH, water clarity,

algal community diversity, occurrence of HABs). Does the risk vary with CHLa?

Objective 2: relate probability of threshold exceedence to CHLa.

What is the risk if CHLa standard is attained? Objective 3: assess risk based on expected distribution of

CHLa at attainment.

Page 3: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

General Approach

Define metrics and thresholds of interest (e.g., DO < 5 mg/L; pH > 9).

Calculate the probability of exceeding thresholds for observations pooled within CHLa ranges (e.g., 0-10, 10-20 µg/L).

Calculate probability of occurrence for these CHLa ranges at attainment (mean = 23 µg/L for TF).

Derive combined probability of exceeding threshold at a given CHLa, and probability of occurrence for that CHLa at attainment of standard.

Page 4: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

Metrics

Water quality and clarity (Paul, Joe, Tish) DO < 5 mg/L pH > 9 algal contributions to suspended particulate matter

Phytoplankton community metrics (Todd, Roger) diversity, evenness, IBI scores*

Phytoplankton HAB metrics (Todd, Anne, Alex) cell densities of harmful taxa*

*How do we establish impairment thresholds where there is not a precedent (e.g., for evenness, Cochlodinium densities)?

Page 5: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

Results: Tidal Fresh – DO and pH

Probability of exceeding nighttime DO minima and daytime pH maxima in relation to CHLa. DO and pH from continuous monitoring; CHLa (extracted) from weekly monitoring.

Page 6: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

CHLa & Water Clarity

Algal contributions to suspended particulate matter (TSS) shown as probability of exceeding specified threshold values. For this analysis, CHLa data were converted to algal-C based on a system-specific C:CHLa ratio, and then converted to dry mass for comparison to TSS.

Page 7: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

CHLa & Algal Toxins (Microcystin) A prior study (Harding et al. 2014) used human

health end points (e.g., drinking and recreational contact standards) to assess impairment of designated uses. However, MC levels in the James have rarely (drinking) or never (contact) exceeded these standards (risk of impairment too low to assess with available data).

For aquatic life, LC50’s for aquatic invertebrates are ~ 100’s – 1000’ µg/L (Smith et al. 2008); mortality effects unlikely in this system.

Our focus: ecological, sub-lethal effects.

Page 8: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

R² = 0.94

CR50 = 0.40 µg L-1

0.00

0.02

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0 1 2 3 4

Microcystin (µg L-1)

Cle

aran

ce r

ate

(L g

DW

-1 h

-1)Assessing MC

Thresholds

Approach #1: effects on ecosystem services provided by benthic filter-feeders.

Top: effects of exposure to dissolved Microcystin on clearance rates of Rangia.

Bottom: likelihood of exceeding Microcystin concentrations at various levels of CHLa.

0%

25%

50%

75%

100%

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80CHLa (µg L-1)

Pro

babi

lity

of e

xcee

denc

e

0

10

20

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Obs

erva

tions

N Obs

> 0.4 µg L-1

> 0.8

> 1.6

> 3.2

Page 9: Science Advisory Panel Data Analysis Workgroup Paul Bukaveckas July 23 2014

Assessing MC Thresholds

Approach #2: effects on fish health via dietary ingestion.

(Right) effects of MC ingestion on liver and gonadal function in threadfin shad (Acuna et al. 2012).

These results were used to assess risk to health of pelagic fishes based on mass-specific content of MC in the James (i.e., MC:TSS).

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Microcystin & CHLa

Likelihood of exceeding mass-specific MC concentrations shown to have adverse effects on fish health as a function of CHLa.

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CHLa Criteria

All 5 metrics show relationships with CHLa and therefore support the view that CHLa criteria can be used to assess attainment of designated uses. •Are current standards protective of designated uses?

•What is the expected level of impairment if current CHLa criteria are attained?

•As the standard is based on a mean value, answering this question requires combining two probability distributions:

1. probability of exceedence as a function of CHLa.

2. probability of exceeding a given CHLa as a function of the mean CHLa.

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CHLa Distribution

Proportional distribution of CHLa observations based on weekly monitoring during July-September in the tidal-fresh James.

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Assessing Risk

Current CHLa standard for tidal fresh = 23 µg/L (Jul-Sep mean)