1. 1 WEBFRAM 5: A risk assessment module for soil invertebrates Geoff Frampton University of Southampton (UK) Joerg Roembke ECT Oekotoxikologie (DE) Paul van den Brink Alterra Green World Research (NL) Janeck Scott-Fordsmand NERI (DK) Funded by

2. 2 WEBFRAM-5 : Principal aim To investigate whether the pesticide risk assessment for below-ground invertebrates could be improved by explicitly incorporating variability and uncertainty into estimates of risk

3. 3 Testing Standard higher-tier test ? Earthworms Collembola Enchytraeidae routine optional yes no Soil invertebrates pesticide risk assessment ( 91 / 414 / EEC )

4. 4 WEBFRAM 5 : Background

5. 5 Deterministic risk assessment scheme Risk: based on toxicity exposure × safety factor Lower tier : acute Lower tier : chronic Higher tier : field Risk measureSafety factor TER effectsnone 10 5 Earthworms example

6. 6 Appropriate as a worst-case screening tool Simple to apply Harmonised calculations and interpretation Applicable to small data sets Safety factor represents uncertainty Risk: based on toxicity exposure × safety factor Deterministic risk assessment scheme

7. 7 Ecological relevance unclear Does not use all the available information Based on untested assumptions Risk estimates lack transparency Does not indicate: - likelihood of risk - degree of risk - certainty of the risk estimate Principal criticisms:

8. 8 Potential benefits of incorporating uncertainty in the risk assessment Clarify how conservative the risk estimate is Make better use of available information Improve realism (i.e. ecological relevance) Indicate certainty, likelihood, degree of risk Improve transparency of risk estimation Validate or refine assumptions Improve efficiency (reduce unnecessary testing)

9. 9 Requires more data than deterministic approach Statistical approaches more complex Could introduce more assumptions May not clarify risk if not communicated well Potential criticisms of incorporating uncertainty in the risk assessment

10. 10 1. Acquire data (key step!) 2. Identify variables with adequately-supported distributions 3. Use data distributions to describe variability 4. Incorporate descriptions of variability in alternative version(s) of the risk assessment Risk assessment version(s) that include uncertainty where appropriate Deterministic risk assessment with supporting data and worked examples output WEBFRAM 5 : Objectives

11. 11 WEBFRAM 5 : Database summary

12. 12 Data sources Research publications & reports Regulatory data in public domain Contract testing laboratory owned 82% 17% 1% 100% 0% Systematic search (literature, institutions, colleagues) > 1000 relevant publications screened > 400 selected for data extraction Data quality classes assigned after data extraction Lower tierHigher tier

13. 13 Below-ground invertebrates database Active substances (a. s.) Species / groups Effects data sets Lower tier (laboratory) Higher tier (TME / field) 257 70 1282 75 72 1029 a. s. with data for both tiers a. s. with only one data set 45 (16%) 108 (38%)

14. 14 Carbendazim Copper Benomyl Dimethoate Pentachlorophenol Parathion Carbofuran Diazinon Lindane Atrazine Chloroacetamide Lambda-cyhalothrin Imidacloprid Chlorpyrifos Carbaryl Halofenozide DNOC Bendiocarb Malathion Thiophanate-methyl Phorate Number of data sets 050100150200250300350 Lower tier Higher tier Soil invertebrate effects data : pesticides with > 20 data sets

15. 15 Number of data sets Diflubenzuron Cypermethrin Methylacetophose Dicresyl Propxur 4-nitrophenol Parathion-methyl Chlordane Isofenphos Disulfoton DDT Phenmedipham Imazalil Flusilazole Cyfluthrin Chlorthal Boric acid Amidosulfuron 024681012141618 Lower tier Higher tier Soil invertebrate effects data : pesticides with 9 - 20 data sets

16. 16 Lumbricidae Collembola Enchytraeidae Acari Coleoptera Nematoda Isopoda Formicidae Diptera Araneae 0200400600800100012001400 Distribution of pesticide effects data among soil invertebrate groups Number of data sets Lower tier Higher tier

17. 17 Collembola species data : lower tier Number of data sets Folsomia candida Folsomia fimetaria Onychiurus folsomi Isotoma viridis Onychiurus armatus Proisotoma minuta Orchesella cincta Sinella communis Collembolans grouped Isotomidae Lepidocyrtus sp. Onychiurus apuanicus Sinella caeca

18. 18 Enchytraeidae species data : lower tier Number of data sets Enchytraeus sp. indet. Enchytraeus coronatus Enchytraeus albidus Cognettia sphagnetorum Friderica ratzeli Enchytraeus crypticus Enchytraeus buchholzi

19. 19 Lumbricidae species data : lower tier Number of data sets Eisenia fetida Earthworms grouped Eisenia andrei Lumbricus terrestris Aporrectodea caliginosa Lumbricus rubellus Aporrectodea tuberculata Allobophora chlorotica Dendrobaena rubida Apporectodea longa Aporrectodea rosea Octolasium lacteum Eisenia veneta 0100200300400500

20. 20 Data reliability checks Following Klimisch et al. (1997) in Regulatory Toxicology & Pharmacology (1) Reliable without restriction (2) Reliable with restrictions (4) Not assignable (3) Not reliable Number% 1149 58645 24119 35127 54 % 46 % 1292100 Total

21. 21

22. 22 WEBFRAM 5 : Risk assessment approach

23. 23 Tiered risk assessment approach Earlier steps are more strict / conservative than later steps Later steps are more realistic than earlier steps Earlier steps usually require less effort than later steps The same type of concentration applies to all steps Jumping to later steps is usually acceptable

24. 24 Tiered risk assessment approach Exposure model

25. 25 Tiered risk assessment approach (Boesten, J.J.T.I.)

26. 26 Fate modelPloughingNo ploughing Step 1No loss 8.3 Step 2Loss due to transformation and ploughing only, 5 o C 0.60.9 Step 3PEARL calculations for a realistic worst-case scenario 0.40.5 Maximum carbendazim content in top 5cm soil (mg a.i. / kg) 20 year period Annual carbendazim application 250 g.a.i. / ha on 15 May Annual ploughing to 15cm on 1 November

27. 27 Tiered risk assessment approach Tier 1Laboratory deterministic - a reasonable worst case estimate (present situation) Tier 2Laboratory probabilistic - a point estimate based on a distribution that indicates probability of the sensitivity Tier 3(Semi-)Field- a safe concentration based on (semi-)field experiments Effects model

28. 28 Tiered risk assessment approach Effects model (top 5 cm soil) – earthworms example Tier 1LC50 acute NOEC chronic OECD 207 guidance & ISO 11268-2 (present situation) Tier 2HC5From lower-tier species sensitivity distributions to incorporate inter-species variation Tier 3NOEC fieldFrom higher-tier semi-field or field experiments

29. 29 earthworms OECD 207 Assumptions: (a)even distribution (b)top 5cm soil (c)bulk density 1200 kg m (d)no loss -3 Lower limit TER acute trigger (safety factor) = 10 Example: carbendazim Tier 1 (deterministic, acute) Tiered risk assessment approach

30. 30 earthworms OECD 207 Assumptions: (a)even distribution (b)top 5cm soil (c)bulk density 1200 kg m (d)no loss -3 Lower limit TER acute trigger (safety factor) = 10 Lowest LC50 acute = 3.9 mg a.i. / kg (EU SEEM project 2002) Typical application rate = 250 g a.i. / ha, equivalent to 0.418 mg a.i. / kg Example: carbendazim Tier 1 (deterministic, acute) Tiered risk assessment approach

31. 31 Example: carbendazim Tier 1 (deterministic, acute) Tiered risk assessment approach earthworms OECD 207 Lowest LC50 acute = 3.9 mg a.i. / kg (EU SEEM project 2002) Typical application rate = 250 g a.i. / ha, equivalent to 0.418 mg a.i. / kg TER < 10 RISK indicated Assumptions: (a)even distribution (b)top 5cm soil (c)bulk density 1200 kg m (d)no loss -3 Lower limit TER acute trigger (safety factor) = 10

32. 32 earthworms OECD 207 Requirement for chronic (reproduction) test if: EU Terrestrial Guidance Document SANCO / 10329 / 2002 More than 6 applications (not fulfilled here) DT 90 field > 90 days (probably not fulfilled) TER acute < 10 (fulfilled) Tiered risk assessment approach

33. 33 Example: carbendazim Tier 1 (deterministic, chronic) earthworms OECD 207 Tiered risk assessment approach PEC chronic: Cumulative concentration In top 5cm over 20 years, assuming no loss Lower limit TER chronic trigger (safety factor) = 5

34. 34 Example: carbendazim Tier 1 (deterministic, chronic) earthworms OECD 207 Tiered risk assessment approach PEC chronic: Cumulative concentration In top 5cm over 20 years, assuming no loss Lower limit TER chronic trigger (safety factor) = 5 Lowest NOEC chronic = 0.6 mg a.i. / kg (van Gestel 1992) PEC chronic = 8.36 mg a.i. / kg

35. 35 Example: carbendazim Tier 1 (deterministic, chronic) earthworms OECD 207 Tiered risk assessment approach PEC chronic: Cumulative concentration In top 5cm over 20 years, assuming no loss Lower limit TER chronic trigger (safety factor) = 5 Lowest NOEC chronic = 0.6 mg a.i. / kg (van Gestel 1992) PEC chronic = 8.36 mg a.i. / kg TER < 5 RISK indicated

36. 36 earthworms & enchytraeids Example: carbendazim Tier 2 (probabilistic) An effect estimate based on the median HC 5, in this example derived from an array of individual toxicity (NOEC) data for earthworms and enchytraeids Tiered risk assessment approach

37. 37 5 species (1 – 14 NOEC values per species) HC 5 (50%) = 0.53 mg / kg (95% CL 0.059 – 1.30) earthworms & enchytraeids Example: carbendazim Tier 2 (probabilistic) Tiered risk assessment approach

38. 38 earthworms & enchytraeids Example: carbendazim Tier 2 (probabilistic) Tiered risk assessment approach 5 species (1 – 14 NOEC values per species) HC 5 (50%) = 0.53 mg / kg (95% CL 0.059 – 1.30) Lowest PEC from step 2 of exposure model = 0.6 mg / kg TER refined = 0.53 / 0.6 = 0.88

39. 39 Lowest PEC from step 2 of exposure model = 0.6 mg / kg earthworms & enchytraeids Example: carbendazim Tier 2 (probabilistic) Tiered risk assessment approach 5 species (1 – 14 NOEC values per species) HC 5 (50%) = 0.53 mg / kg (95% CL 0.059 – 1.30) TER refined = 0.53 / 0.6 = 0.88 TER < 5 RISK indicated Safety factor ? Assume = 5 (conservative, from Tier 1)

40. 40 multiple species Example: carbendazim Tier 3 (semi-field / field) Instead, the effect estimate (NOEC field) may be determined from TME and field experiments that simulate or represent realistic agroecological conditions Tiered risk assessment approach Higher-tier studies did not yield data suitable for constructing distributions of sensitivities An HC5 type approach therefore could not be applied to the higher-tier data to estimate risk

41. 41 Higher-tier effects classes (based on Brock et al. (2000) Alterra Report 88) Class 1 Class 2 Class 3 No effect demonstrable Slight effect, transient Slight effect, long term; Pronounced effect, transient or long term

42. 42 The effect estimate (NOEC field) is determined from TME and field experiments that simulate or represent realistic agroecological conditions 1 2 3 Effects class multiple species Example: carbendazim Tier 3 (semi-field / field) Tiered risk assessment approach 61 data entries for Lumbricidae

43. 43 The effect estimate (NOEC field) is determined from TME and field experiments that simulate or represent realistic agroecological conditions 1 2 3 Effects class multiple species Example: carbendazim Tier 3 (semi-field / field) Tiered risk assessment approach NOEC field = 1.0 mg / kg 61 data entries for Lumbricidae

44. 44 The effect estimate (NOEC field) is determined from TME and field experiments that simulate or represent realistic agroecological conditions 1 2 3 Effects class multiple species Example: carbendazim Tier 3 (semi-field / field) Tiered risk assessment approach NOEC field = 1.0 mg / kg Step 2 PECs 61 data entries for Lumbricidae

45. 45 The effect estimate (NOEC field) is determined from TME and field experiments that simulate or represent realistic agroecological conditions 1 2 3 Effects class multiple species Example: carbendazim Tier 3 (semi-field / field) Tiered risk assessment approach NOEC field = 1.0 mg / kg Step 3 PECs Step 2 PECs NOEC > PEC NO RISK 61 data entries for Lumbricidae

46. 46 Project outputs An internet-based risk assessment tool that would enable stakeholders to input their own data or use default examples to explore the impact on risk estimates of incorporating uncertainty, using: a species sensitivity distribution model to calculate HC5 (or HCx) values for lower-tier data a tiered exposure model an interface to enable exposure and effects estimates to be combined and plotted (where appropriate) to indicate probability and certainty of risk estimates online guidance and links to other relevant risk assessment resources

47. 47 Purpose of the internet resource Optimise opportunities for interested parties to explore alternative ways of estimating risk Assist decision making at each risk assessment tier Raise awareness of data availability issues and limitations Provide feedback Could be used as an educational and training resource

48. 48 Conclusions Opportunities to explicitly incorporate uncertainty in the risk assessment are limited, even for standard test species, due to a lack of appropriate empirical data However, the feasibility of incorporating uncertainty can be illustrated for components of the risk assessment scheme where data shortage is least problematic Further development of the database is imperative, to enable advances in these research areas Data from the independent literature is biased strongly towards standard test species, meaning that few data are available to support extrapolation to non-standard species