Navigating Pesticide Risk Assessment for Informed Decisions

1. Finding Common Ground in the Pesticide Risk Assessment Process Bruce K. Hope, Ph.D. CropLife America & RISE2014 Spring ConferenceArlington, VA

2. National Research Council (NRC) • Committee on Ecological Risk Assessment Under FIFRA and ESA • Report: April 2013 • CropLife Science Forum • May 2013 • Agency efforts • “Interim Approaches for National-Level Endangered Species…Assessments”

3. Risk • Uncertainty (as a probability) about an outcome (with specified consequences) being realized in the future due to a decision made today • This probability is the “risk estimate” • Uncertainty about the risk estimate itself • Sources • Natural / stochastic variability • Incertitude (lack of knowledge, ignorance) • Measurement and model error • Can be expressed qualitatively and/or qualitatively • Essentially our “confidence” in the risk estimate

4. Components of a Risk Assessment Exposure Scenario Exposure Risk Characterization Probability of a Specified Adverse Effect Exposure-Response

5. Risk Characterization EXPOSURE (EEC) EXPOSURE-RESPONSE PROBABILITY Risk Estimate Probability of eliciting a specified response in an individual CONCENTRATION

6. Interim Memo: Exposure • Step 1 • Modeled estimates • Step 2 • Modeled estimates w/ refinements • Step 3 • Not specified • Role for both prediction and measurements (empirical data) for model corroboration)

7. Interim Memo: Exposure-Response • Step 1 (No Effect / May Affect; Action Area) • Animals: EEC  LD0.000001 (individual mortality) • 5th percentile species from SSD or most sensitive species tested • Plants: Lowest NOAEC or EC05 • Step 2 (NLAA / LAA) • Animals: EEC  EC10 (10% decrease in individuals) • 5th percentile species from SSD or most sensitive species tested • Plants: Lowest LOAEC or EC25 • Step 3 (Jeopardy) • Population model(s) - Same SSD, D/R slopes as in Steps 1 & 2

8. Interim Memo: It’s a Start, but… • Point of departure for exposure is not defined • What will the EEC represent? Median, mean, 95%? • Point to point comparisons (EEC to LD0.000001, etc.) are not “risk” estimates • They are hazard or threshold assessments • Step 1 & 2 hazard assessments produce “risk quotients” that are not easily transferable to Step 3 stochastic population models • A common basis in probability (risk) is missing

9. Why Not Quotients? • A hazard (threshold) assessment gives decision makers no idea of the chance of an outcome • But being just over the threshold is often perceived of as a 100% certainty of a detrimental outcome • Benefits can be foregone to avert a “certainty” that is highly unlikely to ever happen • This may lead to decisions that limit pesticide use to a greater extent than is intended by policy

10. Informing Decisions with Risk • If I plan to make decision X (to register a pesticide)… • What is the probability (p(Y)) that detrimental outcome Y will occur in the future? [p(Y) is the risk estimate] • What is my confidence in that estimate of p(Y)? • Where confidence is affected by variability and incertitude • Acceptability of p(Y)’s value is strictly a policy choice • But knowledge of it’s size (large or very small) is an important component of informed decision making

11. Tools for quantitative risk analysis • Monte Carlo • First-order (variability + incertitude) • Widely used approach, particularly for data-rich situations • Second-order (variability, incertitude) • Useful for value of information determinations • Probability Bounds Analysis • Bayesian Methods • Can work across a hierarchy of data levels • Dempster-Shafer Theory (multiple lines of evidence)

12. Risk as Common Ground EXPOSURE (EEC) EXPOSURE-RESPONSE (SSD) EPA: Steps 1 & 2 PROBABILITY Risk estimate (%) Exposure Scenario Exposure CONCENTRATION Risk Characterization Exposure-Response Population Model(s) Probability of Effect on Population Services: Step 3