CropLife America & RISE 2014 Spring Conference Arlington, VA Finding Common Ground in the Pesticide Risk Assessment Process Bruce K. Hope, Ph.D.

2  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” National Research Council (NRC)

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 3

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

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

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) 6

Interim Memo: Exposure-Response  Step 1 (No Effect / May Affect; Action Area) –Animals: EEC  LD (individual mortality) 5 th 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) 5 th 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 7

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 LD , 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 8

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 9

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 10

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) 11

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