Models for Pesticide Selection

1. Models for Pesticide Selection Jennifer Grant NYS IPM Program Cornell University http://www.nysipm.cornell.edu/

2. Pesticide selection criteria:the 3 E’s • Efficacy • Economics • Environmental & health impact

3. Data Sources • MSDS Sheet • Label • Cornell Pesticide Management and Education Program, PIMS site • EPA pesticide fact sheets • EXTOXNET pesticide summaries • Pesticide Action Network (PAN) database • Turf Pesticides and Cancer Risk Database

4. Water impact models for Agriculture • Chemical and physical properties of pesticides that affect environmental fate (e.g. solubility, soil adsorption) • Agricultural crops (row crops with some bare soil) • Physical properties of soils Based on:

5. Water impact models for Agriculture • WinPST (USDA National Resource Conservation Service’s Windows Pesticide Screening Tool) • GLEAMS (Groundwater Loading Effects of Agricultural Management) • NAPRA (National Pesticide Risk Analysis) • GUS (Groundwater Ubiquity Source) • SPISP (Soil Pesticide Interaction Screening Procedure)

6. Water impact models for Turfgrass • TurfPQ (model for runoff from turfgrass, Haith, 2001) • estimates pesticide in runoff events from turf • Accounts for thatch • Uses Carbon content, OM and bulk density specific to turf • Useful for water quality studies and environmental assessments

7. Model Complexity • Ecological impacts (e.g. toxicity to fish, other non-targets) • Human health impacts • Site specificity (e.g. soil type, slope) • Management influences

8. NRCS Three-Tiered Pesticide Environmental Risk Screening • Tier 1 - SPISP • Tier 2 = NAPRA • Utilizes GLEAMS • environmental benefits of management alternatives • Regional climatic conditions • Results consider both the off-site movement of pesticide and its toxicity to non-target species • Tier 3 - NAPRA • Site specific • Generic inputs are replaced by individual producers' filing records and field measured soils data

10. Integrated models for selection Decision Tool for Integrated Pesticide Selection and Management (IATP) • Minnesota corn & soybeans • Water contamination focus (WinPST) • Human exposure (drinking water) • Fish as non-target organism

11. Integrated models for selection Environmental EIL • Assigns an “environmental cost” to pest management, based on opinion surveys (contingent valuation) • Largely theoretical, but assigns values (Higley & Wintersteen, 1992)

12. Risk/Category and Environmental Cost, Environmental EIL

13. Integrated models for selection Environmental Yardstick(Netherlands) • Values risk as environmental impact points • Based on • Acute risk to water organisms • Risk of groundwater contamination • Acute and chronic risks to soil organisms • Provides numerical value for a pesticide applied at a specific rate • Expressed as environmental impact points (EIP) (www.agralin.nl/milieumeetlat; Reus and Pak, 1993; Reus and Leendertse, 2000)

14. Integrated models for selection Environmental Yardstick(cont’d) Currently used in the Netherlands • Farm & Greenhouse decision support tool • Environmental performance incentive • Standards for eco-labels • Policy tool (www.agralin.nl/milieumeetlat; Reus and Pak, 1993; Reus and Leendertse, 2000)

15. Integrated models for selection Environmental Impact Quotient (EIQ) • Original model published in 1992 (Kovach et al.) for food crops • Three components: worker, consumer, ecological • Provides numerical value for a pesticide, applied at a specific rate • Can use to select pesticides or compare systems

16. EIQ = {C x [DT x 5 + (DT x P)] + [(C x ((S + P)/2) x SY) + L] + [(F x R) + (D x ((S + P)/2) x 3) + (Z x P x 3) + (B x P x 5)]} ÷ 3

17. EIQ • Farm worker: Acute and chronic toxicity to humans. • Consumer: Food residues, chronic toxicity to humans, leachability to groundwater. • Ecological: Aquatic and terrestrial non-target toxicity (fish, bees), leachability, persistence.

18. EIQ • Risk = toxicity x potential for exposure • E.g. effect on fish depends on toxicity to fish, and likelihood of fish encountering pesticide. • Persistence • Surface loss potential

19. Farm worker Component Applicator+ Picker (C * DT * 5)+ (C * DT * P) Dermal Toxicity Chronic Toxicity Plant surface residue half-life

20. Chronic Toxicity • Average of Reproductive, Teratogenic, Mutagenic, & Oncogenic effects • Low value if no evidence of carcinogenicity • High value if probable human carcinogen

21. Dermal Toxicity • Dermal LD50 rabbits • Dermal LD50 rats 1 = > 2000 mg/kg 3 = 200 - 2000 mg/kg 5 = 0 - 200 mg/kg

22. Plant Surface Residue 1 = < 2 weeks 3 = 2-4 weeks 5 = > 4 weeks Herbicides Pre-emergent = 1 Post-emergent = 3

23. Consumer Component Food residue+ Groundwater (C * ((S + P)/2) * SY)+ (L) Soil half-life Plant half-life Mode of Action: Systemic or non Leaching potential Chronic Toxicity

24. Exposure Persistence • Plant half life • Soil half life

25. Ecological Component Fish + Bird + Bee + Beneficials Each organism X potential for exposure

26. Fish toxicity (F) Surface Loss Potential (R) Bird Toxicity (D) Soil half life (S) Plant surface half life (P) Bee Toxicity (Z) Beneficial Arthropod toxicity (B) Ecological component = [(F x R) + (D x ((S + P)/2) x 3) + (Z x P x 3) + (B x P x 5)]

27. Beneficial arthropod impact • SELCTV database on 600 chemicals, 400 natural enemies (Oregon State Univ., Theiling and Croft, 1988) • Data generated more recently --standardized on 5 natural enemies (insects) and 3 microbials • (Cornell, Petzoldt & Kovach, 2002)

28. EIQ = {C x [DT x 5 + (DT x P)] + [(C x ((S + P)/2) x SY) + L] + [(F x R) + (D x ((S + P)/2) x 3) + (Z x P x 3) + (B x P x 5)]} ÷ 3

29. The poison is in the dose!

30. The poison is in the dose! An EIQ value must be multiplied by the rate it is applied. This yields a “field EIQ” that can be compared.

31. EIQ as a Pesticide Selection Tool

32. Insecticide Example

33. Fungicide example

34. Additional Considerations • Resistance management • Ease of application • Weather conditions • Availability of product • Availability of equipment

35. EIQ for Comparing Management Strategies

36. Conventional Red Delicious Material EIQ ai Apps Dosage Total Nova Captan Lorsban Lorsban Thiodan Guthion Cygon Omite Sevin Kelthane 65.3 16.2 35.0 35.0 34.0 26.3 49.6 27.5 21.7 26.1 .4 .5 .4 .5 .5 .35 .43 .68 .5 .35 4 6 1 2 1 2 3 2 1 1 0.3 3.0 1.5 3.0 3.0 1.5 2.0 2.0 1.0 4.5 31 24 21 105 51 14 128 75 11 41 Total field EIQ 501

37. IPM Strategy, Red Delicious Apples Material EIQ ai Apps Dosage Total 13.6 10.5 1.4 19.1 17.5 Nova Captan Dipel Sevin Guthion 65.3 16.2 10.6 21.7 26.3 .4 .5 .06 .8 .35 4 1 3 1 2 .13 1.3 .73 1.1 .95 Total field EIQ 62.1

38. IPM Strategy, Liberty Apples Material EIQ ai Apps Dosage Total Imidan 16.1 .5 3 1.5 36.2 Total field EIQ 36.2

39. Organic Strategy, Red Delicious Apples Material EIQ ai Apps Dosage Total 997 47 1 Sulfur Rot/pyr Ryania 26.4 16.3 10.6 .9 .04 .001 7 6 1 6 12 58 Total field EIQ 1045

40. SUMMARY Strategy Field EIQ 1045 501 62 36 Organic Conventional IPM IPM on Liberty

41. Is the EIQ useful for Turf? • Toxicity and environmental fate characteristics of the pesticides are the same for ag. and turf • The arrangement of these data in the formula are similar to what would be appropriate for turfgrass • the EIQ and other quantitative models are the best we can do until there is a model specifically designed for turf

42. Environmental Impact of Pesticide Applications, Bethpage Project, 2004, expressed as Field EIQ (Grant & Rossi 2006)

43. EIQ Challenges • Standardization of data & data gaps • Weighting may not meet criteria of user • Not site specific

44. Turfgrass EIQ • Adjust formula to better reflect turfgrass system • replace bee toxicity with earthworm toxicity • “User” for consumer (e.g. golfer) • Weight factors appropriately for turfgrass • Incorporate TurfPQ? • Include site specific information such as soil type and water proximity

45. Pesticide selection criteria:the 3 E’s • Efficacy • Economics • Environmental & health impact