WEBFRAM 5: A risk assessment module for soil invertebrates

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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

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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

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Testing

Standard higher-tier

test ?

Earthworms

Collembola

Enchytraeidae

routine

optional

optional

yes

no

no

Soil invertebrates pesticide risk assessment

( 91 / 414 / EEC )

4

WEBFRAM 5 : Background

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Deterministic risk assessment scheme

Risk: based ontoxicity

exposure× safety factor

Lower tier : acute

Lower tier : chronic

Higher tier : field

Risk measure Safety factor

TER

TER

effects none

10

5

Earthworms example

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 ontoxicity

exposure× safety factor


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:

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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)

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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

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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 riskassessment with

supporting data andworked examples

output

WEBFRAM 5 : Objectives

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WEBFRAM 5 : Database summary

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Data sources

Research publications & reports

Regulatory data in public domain

Contract testing laboratory owned

82%

17%

1%

100%

0%

0%

Systematic search (literature, institutions, colleagues)

> 1000 relevant publications screened

> 400 selected for data extraction

Data quality classes assigned after data extraction

Lower tier Higher tier

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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%)

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CarbendazimCopper

BenomylDimethoate

PentachlorophenolParathion

CarbofuranDiazinonLindaneAtrazine

ChloroacetamideLambda-cyhalothrin

ImidaclopridChlorpyrifos

CarbarylHalofenozide

DNOCBendiocarb

MalathionThiophanate-methyl

PhorateNumber of data sets

0 50 100 150 200 250 300 350

Lower tier

Higher tier

Soil invertebrate effects data : pesticides with > 20 data sets

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Number of data sets

Diflubenzuron

Cypermethrin

Methylacetophos

e

Dicresyl

Propxur

4-nitrophenol

Parathion-methyl

Chlordane

Isofenphos

Disulfoton

DDT

Phenmedipham

Imazalil

Flusilazole

Cyfluthrin

Chlorthal

Boric acid

Amidosulfuron0 2 4 6 8 10 12 14 16 18

Lower tier

Higher tier

Soil invertebrate effects data : pesticides with 9 - 20 data sets

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Lumbricidae

Collembola

Enchytraeidae

Acari

Coleoptera

Nematoda

Isopoda

Formicidae

Diptera

Araneae

0 200 400 600 800 1000 1200 1400

Distribution of pesticide effects data among soil invertebrate groups

Number of data sets

Lower tier

Higher tier

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Collembola species data : lower tier

Number of data sets

0 10 20 30 40 50

Folsomia candidaFolsomia fimetariaOnychiurus folsomiIsotoma viridisOnychiurus armatusProisotoma minutaOrchesella cinctaSinella communisCollembolans groupedIsotomidaeLepidocyrtus sp.Onychiurus apuanicusSinella caeca

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0 5 10 15 20 25 30 35

Enchytraeidae species data : lower tier

Number of data sets

Enchytraeus sp. indet.

Enchytraeus coronatus

Enchytraeus albidus

Cognettia sphagnetorum

Friderica ratzeli

Enchytraeus crypticus

Enchytraeus buchholzi

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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

0 100 200 300 400 500

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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 %

114 9

586 45

241 19

351 27

54 %

46 %

1292 100Total

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EC50

LC50

0.2

0.4

0.6

0.8

1.0

10 100 1000 10000

EC50 and LC50 (mg/kg Cu)

Po

ten

tia

lly A

ffe

cte

d F

ract

ion

Reliable without restriction

Reliable with restrictions

Not reliableNot assignable

0.0

Cumulative sensitivity distributions for Cu based on data of varying quality

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WEBFRAM 5 : Risk assessment approach

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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

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Exposure model

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

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Fate model Ploughing No ploughing

Step 1 No loss 8.3 8.3

Step 2 Loss due to transformation and ploughing only, 5 oC

0.6 0.9

Step 3 PEARL calculations for a realistic worst-case scenario

0.4 0.5

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

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Tier 1 Laboratory

deterministic

- a reasonable worst case estimate (present situation)

Tier 2 Laboratory

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

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Effects model (top 5 cm soil) – earthworms example

Tier 1 LC50 acuteNOEC chronic

OECD 207 guidance &ISO 11268-2(present situation)

Tier 2 HC5 From lower-tier species sensitivity distributions to incorporate inter-species variation

Tier 3 NOEC field From higher-tier semi-field or field experiments

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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)


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earthworms

OECD 207

Assumptions:


(b) top 5cm soil


(d) no loss

-3



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




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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 < 10RISK

indicated

Assumptions:


(b) top 5cm soil


(d) no loss

-3



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earthworms

OECD 207

Requirement for chronic (reproduction) test if:

EU Terrestrial Guidance Document

SANCO / 10329 / 2002

• More than 6 applications (not fulfilled here)

• DT90 field > 90 days (probably not fulfilled)

• TER acute < 10 (fulfilled)


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Tier 1 (deterministic, chronic)

earthworms

OECD 207


PEC chronic:

Cumulative concentration

In top 5cm over 20 years,

assuming no loss

Lower limit TER chronic trigger

(safety factor) = 5

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earthworms

OECD 207


PEC chronic:



assuming no loss


(safety factor) = 5

Lowest NOEC chronic = 0.6 mg a.i. / kg

(van Gestel 1992)

PEC chronic = 8.36 mg a.i. / kg

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earthworms

OECD 207


PEC chronic:



assuming no loss


(safety factor) = 5

Lowest NOEC chronic = 0.6 mg a.i. / kg

(van Gestel 1992)

PEC chronic = 8.36 mg a.i. / kg

TER < 5RISK

indicated

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earthworms &enchytraeids


Tier 2 (probabilistic)

An effect estimate based on the

median HC5, in this example

derived from an array of

individual toxicity (NOEC) data

for earthworms and enchytraeids


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HC5 (50%)

Fre

qu

en

cy

Soil concentrations (log)

NOECs forvariousspecies &experiments

5 species

(1 – 14 NOEC valuesper species)

HC5 (50%) =

0.53 mg / kg

(95% CL 0.059 – 1.30)





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5 species


HC5 (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

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Lowest PEC from step 2 of exposure model = 0.6 mg / kg





5 species


HC5 (50%) =

0.53 mg / kg

(95% CL 0.059 – 1.30)

TER refined = 0.53 / 0.6 = 0.88

TER < 5RISK

indicated

Safety factor ? Assume = 5 (conservative, from Tier 1)

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multiplespecies


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


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

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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

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The effect estimate (NOEC field) is determined from

TME and field experiments that simulate or represent

realistic agroecological conditions

Lumbricidae

1

2

3

0.1 1 10 100

Carbendazim concentration (mg/kg)

Eff

ect

Cla

ss

1

2

3

Effects class

multiplespecies




61 data entries for

Lumbricidae

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Lumbricidae

1

2

3

0.1 1 10 100


Eff

ect

Cla

ss

1

2

3

Effects class

multiplespecies




NOEC field = 1.0 mg / kg

61 data entries for

Lumbricidae

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Lumbricidae

1

2

3

0.1 1 10 100


Eff

ect

Cla

ss

1

2

3

Effects class

multiplespecies




NOEC field = 1.0 mg / kgStep 2 PECs

61 data entries for

Lumbricidae

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Lumbricidae

1

2

3

0.1 1 10 100


Eff

ect

Cla

ss

1

2

3

Effects class

multiplespecies




NOEC field = 1.0 mg / kg

Step 3 PECs

Step 2 PECs

NOEC > PEC

NO RISK

61 data entries for

Lumbricidae

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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

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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

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Conclusions

Opportunities to explicitly incorporate uncertainty in the risk assessment are limited, even for standard testspecies, due to a lack of appropriate empirical data

However, the feasibility of incorporating uncertainty can beillustrated for components of the risk assessment schemewhere data shortage is least problematic

Further development of the database is imperative, to enableadvances in these research areas

Data from the independent literature is biased stronglytowards standard test species, meaning that few data areavailable to support extrapolation to non-standard species

Documents

WEBFRAM 5: A risk assessment module for soil invertebrates