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Models for Pesticide Selection Jennifer Grant NYS IPM Program Cornell University

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Presentation on theme: "Models for Pesticide Selection Jennifer Grant NYS IPM Program Cornell University"— Presentation transcript:

1 Models for Pesticide Selection Jennifer Grant NYS IPM Program Cornell University

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

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

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 LD 50 rabbits Dermal LD 50 rats 1 = > 2000 mg/kg 3 = mg/kg 5 = mg/kg

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

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

24 Plant half life Soil half life Exposure Persistence

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

26 Ecological component 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) = [(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 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 Thiodan Guthion Cygon Omite Sevin Kelthane Total field EIQ 501

37 IPM Strategy, Red Delicious Apples Material EIQ ai Apps Dosage Total Nova Captan Dipel Sevin Guthion Total field EIQ 62.1

38 IPM Strategy, Liberty Apples Material EIQ ai Apps Dosage Total Imidan Total field EIQ 36.2

39 Organic Strategy, Red Delicious Apples Material EIQ ai Apps Dosage Total Sulfur Rot/pyr Ryania Total field EIQ 1045

40 SUMMARY Strategy Field EIQ 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


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