Use of the Joint Probability Distribution Analysis for ... - ACS Publications

Chapter 12

Downloaded by CORNELL UNIV on November 8, 2012 | http://pubs.acs.org Publication Date (Web): November 6, 2012 | doi: 10.1021/bk-2012-1111.ch012

Use of the Joint Probability Distribution Analysis for Assessment of the Potential Risks of Dimethoate to Aquatic Endangered Species Qingli Ma,*,1 Richard Reiss,1 Clifford Habig,2 and Paul Whatling3 1Exponent,

Inc., 1150 Connecticut Avenue, NW, Suite 1100, Washington, DC 20036 2Compliance Services International, 7501 Bridgeport Way West, Lakewood, WA 98499 3Cheminova, Inc., 1600 Wilson Blvd., Suite 700, Arlington, VA 22209 *E-mail: [email protected]

The joint probability distribution analysis (JPDA) utilizes the full exposure distribution and the dose-response curve to determine the probability of an adverse effect occurring and the magnitude of the effect. It accounts for uncertainty from variations in exposure concentrations and species sensitivities and can better address the probability of risks of pesticides than the standard, Environmental Protection Agency regulatory risk quotient (RQ) method. In this application, the concern is for effects of dimethoate on salmonid prey which have differing sensitivities. Thus, accounting for variability in response is important. While use of the RQ method indicated potential risks to aquatic invertebrates, results of JPDA showed minimal risks, despite using an exposure model that likely significantly overestimates water concentrations. This paper demonstrates the application of the JPDA methodology to refine an ecological risk assessment and develop more accurate risk estimates.

© 2012 American Chemical Society In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Introduction As part of its mandate to assess the potential effects of pesticides on endangered species, the U.S. Environmental Protection Agency (EPA) and the National Marine Fisheries Service (NMFS) are engaged in a consultation regarding potential effects to salmonids in 26 Evolutionary Significant Units (ESUs) in the Pacific Northwest (http://www.epa.gov/oppfead1/endanger/ litstatus/final-batch-3-opin.pdf). In analyzing the risks of pesticides to endangered species, EPA and NMFS have routinely applied conservative assumptions and based risk characterizations on single point estimates (risk quotients [RQs]). The analysis provides limited information about the probability of an unacceptable risk or the magnitude of risk, nor does it scientifically consider many of the uncertainties in individual sensitivity and species sensitivity. In commenting on EPA’s current procedures for risk assessments, the FIFRA Science Advisory Panel (SAP) recommended that EPA develop methodologies to conduct probabilistic assessments of risks. The SAP specifically emphasized that “while these current procedures can serve as a screen to identify possible environmental damage, they often provide less information on the likelihood of the damage and the uncertainty in such estimates as is desirable in balancing risks and benefits as required under FIFRA” (1). Addressing issues of probability of risk requires incorporation of the full exposure distribution and the concentration-effect relationship. A more refined, higher tier risk assessment is therefore warranted, such as the joint probability distribution analysis (JPDA) that was recommended in the ecological risk assessment process (http://www.epa.gov/oppefed1/ecorisk/aquareport.pdf). In this approach, both the exposure and the effect are treated as probabilistic distributions instead of point values, and the two probabilistic distributions are then integrated to create a joint probability distribution, which describes the probability that an effect (response) exceeding any given magnitude will occur under the range of exposure scenarios used to generate the exposure distribution. Thus, the joint probability distribution provides information on the relationship between the magnitude of effect and the probability of that effect occurring. Contrary to the EPA RQ method in which only one point on the exposure concentration distribution is used in risk characterization, the JPDA utilizes the full exposure concentration distribution, which alleviates the uncertainty due to variation in ranges of exposure concentration. Since the concentration-effect relationship can be derived from any effect endpoints for developing the joint probability distribution, the JPDA can also address the probability of risks of a pesticide to various species, with the probability of an effect being predicted across the range of sensitivities of the species in question. Depending on the number of species included in the analysis, the resulting joint probability distribution can better characterize potential pesticide impact on communities and ecosystems than an assessment based on an individual test species. Therefore, the joint probability distribution is especially useful for an endangered species risk analysis, such as the Pacific Northwest salmonid risk analysis. Because the joint probability distribution reflects the uncertainties in the risk characterizations for 172 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

both exposure and effects, it provides a better description of the risks of pesticides to ecosystems for decision making than a simple quotient, as EPA currently uses. The objectives of this study were to evaluate the potential risk of dimethoate (O,O-dimethyl S-[2-(methylamino)-2-oxoethyl] dithiophosphate) to federally-listed Pacific Northwest salmonids using the JPDA and to compare the results of such an analysis to those of EPA in their risk assessments.

Material and Methods


Risk Assessment Using the Joint Probability Distribution Analysis With the JPDA, the exposure and toxicity are both estimated probabilistically. The exposure assessment is undertaken by using the concentrations predicted by the linked PRZM/EXAMS model (PE 5.0, http://www.epa.gov/oppefed1/models/ water/) with EPA standard scenarios (http://www.epa.gov/oppefed1/models/ water/przmenvironmentdisclaim.htm) for higher-tier ecological risk assessment. All these scenarios were developed assuming a 10-ha treated field draining into an adjacent, 1 ha by 2 meter deep, stagnant pond, with no outlet. Each scenario represents a unique combination of climatic conditions, crop-specific management practices, soil-specific properties, site-specific hydrology, and pesticide-specific application and dissipation processes. The scenarios are supposed to represent a high-end exposure for the crop of interest. The modeling scenario is also expected to produce runoff greater than would be expected at 90% of the sites where the crop of interest is grown. The exposure is modeled for 30 years to provide a meaningful distribution of the predicted concentrations for probabilistic exposure characterization. Contributions from spray drift to exposure are included in PRZM/EXAMS and are dependent on the method of pesticide application (e.g., ground equipment, aerial, airblast). The model generates probability distributions of pesticide concentrations in the water column for various durations of exposure. For acute exposure assessment, the probability distribution of the daily peak concentrations over a period of 30 years is used to construct the joint probability curve. Chemical specific PRZM/EXAMS model input parameters are presented in Table I. For toxicity, the concentration-effect relationship is derived from two effect endpoints. One effect endpoint is the percent of species affected by dimethoate, expressed as the species sensitivity distribution (SSD). In this case, we would use toxicity levels for invertebrate species that salmonids may consume. The 48-hour, acute toxicities of dimethoate (LC50/EC50) to 9 freshwater and marine invertebrates determined in 11 studies (Table II) were used to construct the SSD using the EPA Species Sensitivity Distribution Generator (SSD_Generator_V1. xlt). This generator produces an SSD by fitting the most commonly applied distribution, the linearized log-normal distribution, to laboratory toxicity data, such as LC50/EC50 or other toxicity endpoints. The fitted distribution for the central tendency was then used to construct the JPD curve. When multiple test data are available for the same species, the geometric mean of the measured toxicities for the species is used. The acute toxicities for freshwater and saltwater species were combined because only two saltwater species toxicity data are available, which makes it impossible 173 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

to construct the SSD for saltwater species alone. Furthermore, salmon can reside in either habitat depending on life stage. Therefore, it can feed on both saltwater and freshwater invertebrates.


Table I. PRZM/EXAMS input parameters for dimethoate1 Parameters

Dimethoate

Water solubility (mg/L)

3,200

Henry’s Law Constant (atm-m3/mole)

8.0e-11

Linear adsorption coefficient (L/kg)

0.3 (Kd)

Photolysis half-life (days)

353.0

Aerobic aquatic metabolism half-life (days)

16.4

Anaerobic aquatic metabolism half-life (days)

40.9

Aerobic soil metabolism half-life (days)

6.2

Neutral hydrolysis half-life (days)

6.8

Foliar decay half-life (days)

2.9

Application method

Aerial

Application rate

(kg/ha)2

0.28

Number of application

3

Application efficiency

0.95

Spray drift fraction

0.05

1

These parameter values were obtained from the EPA effects determination (http:// www.epa.gov/espp/litstatus/effects/redleg-frog/dimethoate/analysis.pdf) for the California red-legged frog. 2 This use rate was for the California lettuce scenario. Application rates for other scenarios were obtained from the same EPA effects determination.

The second effect endpoint is the dose-response relationship derived from the acute mortality data for daphnids. The dose-response data measured by Song et al. (6) at 20–21°C, Hertl et al. (9), and Anderson et al. (10) are combined and used. The measured concentration-mortality data for dimethoate were fitted to a logarithm function to derive the concentration-effect relationship. The exposure distribution is then integrated with the concentration-effect relationship to develop a joint probability curve for analysis. The risk is then characterized according to the magnitude of the risk product (RP), which is calculated as the product of the exceedance probability and magnitude of effect. This risk product can also be interpreted numerically as the area under the 174 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

exceedance curve (13). Four categories of RPs have been used, following Giesy et al. (14) and Giddings et al. (15), to characterize the effects of dimethoate on aquatic animals. For comparison and consistency with the EPA RQ method, all categorizations are based on the 90th percentile RP.

• •


• •

If the calculated 90th percentile RP is less than 0.25%, then the risk is characterized as minimal; If the calculated 90th percentile RP is greater than 0.25% but less than 2%, then the risk is characterized as low; If the calculated 90th percentile RP is greater than 2% but less than 10%, then the risk is characterized as intermediate; and If the calculated 90th percentile RP is greater than 10%, then the risk is characterized as high.

Table II. Acute (48-h) toxicity of dimethoate to various aquatic salmon prey species for construction of species sensitivity distribution (SSD) Species

LC50 or EC50 (mg/L)

Sources

Stonefly (Pteronarcys california)

0.14

(2)

Snowbug (Asellus aquaticus)

2.96

(3)

Scud (Gammarus lacustris)

0.2

(4)

Midge (Chironomus tentans)

0.249

(5)

5.0, 6.4

(6)

Saltwater mysid (Mysidopsis bahia)

22.0

(7)

Brine shrimp (Artemia; Crustacea)

15.73

(6)

Marsh mosquito (Aedes taeniorhynchus)

0.031

(6)

Daphnid (Daphnia magna)

6.4

(8)


2.0

(9)


1.1

(10)


1.5, 1.8, 1.7, 2.0

(11)


3.32, 3.12

(6)


6.4

(12)

Yellow fever mosquito (Aedes aegypti)

175 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Risk Assessment Using the EPA Risk Quotient Method The same exposure concentration distribution generated by PRZM/EXAMS model as in the JPDA is used for exposure assessment using the deterministic RQ method. However, unlike the JPDA in which the entire concentration probability distribution is used, the EPA RQ method only uses the 90th percentile concentration of the daily peak concentration distribution to calculate the RQ for acute risk characterizations. Practically, the RQ is calculated by dividing the exposure concentration at the 90th percentile by an appropriate measurement endpoint (e.g., LC50/EC50) obtained from the standard toxicity tests. Usually the lowest toxicity endpoint (e.g., LC50/EC50) is used for the RQ calculation. The RQ is compared to a set of risk criteria to determine whether there is a potential regulatory concern. Three categories of regulatory concern above minimal risk to non-target aquatic animals have been established for acute risks—acute high risk, acute restricted use, and acute endangered species. Each category comes with a prescribed level of concern (LOC) defined by EPA for risk characterizations. For aquatic animals, the LOCs are 0.5, 0.1 and 0.05 for acute high risk, acute restricted use, and acute endangered species, respectively. If the risk criteria (LOCs) are not exceeded, it is concluded that there will be minimal ecological concern from the proposed use of the product and the aquatic risk assessment process is judged complete. If the risk criteria are exceeded, the risk assessment process advances to a higher tier analysis, but only for those taxa and application scenarios that continue to be of concern. Note that although an entire dose-response curve can normally be derived from the standard toxicity test, only one point on this curve, the concentration corresponding to 50% mortality (LC50/EC50), would be used in toxicity assessment and risk characterizations with the EPA deterministic RQ method. Ignoring the rest of the curve in risk characterizations may result in uncertainty due to variation in ranges of exposure concentrations. This is an apparent limitation of the RQ method compared to the JPDA method in which the entire dose-response curve is utilized for risk characterizations.

Results and Discussion Risk Characterizations Using the Joint Probability Distribution Analysis Figure 1 shows the SSD of dimethoate constructed based on data in Table II using the EPA Species Sensitivity Distribution Generator. The measured 48hour acute toxicities (LC50/EC50) of dimethoate to nine invertebrate species are included. The sensitivities of the nine species to dimethoate vary significantly (Figure 1), with the marsh mosquito (Aedes taeniorhynchus) being the most sensitive and saltwater mysid (Mysidopsis bahia) being the least sensitive to dimethoate. The 90th percentile dimethoate peak concentrations in the ecological pond predicted by PRZM/EXAMS for seven sites are also included in Figure 1 for comparisons. These sites cover the major use patterns of dimethoate in the U.S. and some were used by EPA in endangered species effects determinations 176 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


(http://www.epa.gov/espp/litstatus/effects/redleg-frog/ dimethoate/analysis.pdf). These predicted concentrations (the vertical lines on the tail side of the SSD curve in Figure 1) incorporate site-specific field and environmental information and can serve as the upper bound concentrations expected under the specified conditions, especially when the site-specific information (e.g., the site-specific monitoring results and the results from mesocosm studies) is not available. Putting together these predicted concentrations with the SSD in one graph has the advantage of helping visually determine the potential impacts on the examined species from different use sites. This is important because one of the primary goals of aquatic ecological risk assessment, whether it is at the screening-level or at higher levels, is to prioritize the potential risks at different locations and to eliminate from further considerations those species and locations that are unlikely to be at risk (13). It can be seen from Figure 1 that for all invertebrate species, dimethoate uses on Oregon pear and wheat, and California alfalfa, citrus, corn, cotton, and lettuce have minimal impacts on the invertebrates. Of the seven scenarios modeled, the California lettuce scenario predicted the highest peak daily concentration (Figure 1), which is 2-3 times higher than those of the two Oregon scenarios, and even it does not exceed the LC50 of the most sensitive invertebrate (marsh mosquito), indicating that uses of dimethoate would not impose significant impacts on salmon prey invertebrates.

Figure 1. Acute species sensitivity distribution (SSD) to dimethoate, with site-specific 90th percentile peak daily concentrations for representative crop uses predicted by PRZM/EXAMS.

177 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


The SSD is then combined with the probability distribution of exposure concentrations predicted by PRZM/EXAMS for the California-lettuce use scenario to create the joint probability curve for dimethoate risk (Figure 2). This use scenario generates the highest dimethoate peak daily concentrations in the hypothetical EPA (Environmental Fate and Effects Division) farm pond (Figure 1) and the JPDA based on this use scenario is more protective of invertebrate species. The joint probability curve (Figure 2) clearly indicates that there is no predicted adverse effect on a wide variety of salmon-feed invertebrate species from the dimethoate use on California lettuce. The calculated RPs for the same exposure concentration range are also included in Figure 2 (the secondary Y-axis). The 90th percentile RP is 0.118% and the maximum RP is 0.144%, which is significantly less than 0.25%, indicating that uses of dimethoate pose minimal risk to salmon-feed invertebrate species according to the risk categories described previously. In its recent Biological Opinions (BiOps) (http://www.epa.gov/ oppfead1/ endanger/litstatus/final-batch-3-opin.pdf), NMFS reported that dimethoate use might adversely affect salmonid prey communities in some areas and jeopardize the Pacific Northwest salmon-feed species based on the AgDrift model estimates and the EPA screening-level GENEEC model estimates. EPA also reported that dimethoate use “May Affect” steelhead and salmon in the Pacific Northwest in its risk analysis for these listed species (http://www.epa.gov/oppfead1/endanger/ litstatus/effects/dimethoate/dimethoate_analysis.pdf) based partly on GENEEC and PRZM/EXAMS models. The higher level JPDA for dimethoate including its use in the Pacific Northwest clearly indicates that those jeopardy determinations were overstated.

Figure 2. Joint probability curve derived from the acute species sensitivity distribution (SSD) and exposure distribution predicted by PRZM/EXAMS for dimethoate use on California lettuce (CA-Lettuce). 178 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


A joint probability curve was also constructed for daphnids alone by integrating the same probability distribution of exposure concentrations as above with the concentration-effect relationship between Daphnia magna and dimethoate. The latter was obtained by fitting the measured concentration-mortality data for Daphnia magna (Table II) to a logarithm function. The resulting joint probability curve is shown in Figure 3, along with the RPs for the same exposure concentration range (the secondary Y-axis in Figure 3). Like the joint probability curve constructed based on the SSD, this joint probability curve shows that there is a very low probability for dimethoate to impact Daphnia magna at the maximum label rate on California lettuce. Since the peak daily concentration for dimethoate use on California lettuce is the highest among the seven scenarios modeled, it is expected that uses of dimethoate would have minimal impact on Daphnia magna. The calculated RPs (

Use of the Joint Probability Distribution Analysis for ... - ACS Publications

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