(Question N EFSA-Q ) adopted on 14 December 2005

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1 Opinion of the Scientific Panel on Plant health, Plant protection products and their Residues on a request from EFSA related to the assessment of the acute and chronic risk to aquatic organisms with regard to the possibility of lowering the uncertainty factor if additional species were tested. (Question N EFSA-Q ) adopted on 14 December 2005 SUMMARY OF OPINION The Scientific Panel on Plant Health, Plant Protection Products and their Residues (PPR Panel) was asked by EFSA for an opinion on the possibility of refining the acute and chronic aquatic risk assessment of pesticides by lowering the assessment factor if additional species were tested. In particular, the PPR Panel was asked how these values could be reduced when additional singlespecies studies are available whilst still maintaining the same level of protection as foreseen in the Directive 91/414/EEC. The current approach for acute and chronic risk assessment to protect the ecosystem against adverse effects of pesticides uses the lowest available toxicity value from laboratory standard toxicity tests, i.e. the most sensitive tested species, and divides this value by a fixed assessment factor. This results in an increase of conservatism when more species are tested and does not reflect the increased certainty that more data provide. To answer this question the PPR Panel reviewed existing literature, guidance documents, and data. Statistical calculations based on species sensitivity distributions were used to develop a range of options for adjusting the risk assessment when more species are tested. The PPR Panel assessed the current level of protection and found that it is not equal for different taxonomic groups and for different substances. On average, the level of protection provided by the current approach is, for example, markedly higher for fish than for crustaceans and insects. The PPR Panel identified a range of possible methods either to maintain at least the current unspecified level of protection, or to achieve any specified level of protection. For taxonomic groups where the legislation requires only one species (e.g. crustaceans), this effectively sets the level of protection in the effects assessment. When additional species are tested, the same average level of protection can be maintained by taking the geometric mean (rather than the lowest value) and dividing by the current assessment factor. For fish, where the legislation requires that at least two species are tested, this implies a higher level of protection in the effects assessment. In this case, a different procedure is required when additional species are tested. The minimum is then replaced by the second or third lowest toxicity value depending on the sample size available, and divided by the current assessment factor. The Panel described three further approaches that allow a particular level of protection to be achieved, provided such a level is specified. These methods involve using a modified assessment factor that incorporates an estimate of the variation between species, which can either be specific to the substance under consideration or derived from existing information on related substances. These three methods relate only to uncertainty due to variation between 1 of 45

2 species. Any other uncertainties that are relevant to the assessment would need to be accounted for separately. Key words: plant protection products, pesticides, aquatic risk assessment, safety factors, assessment factors, level of protection, species sensitivity distribution (SSD), extrapolation, standard toxicity tests. 2 of 45

3 TABLE OF CONTENTS SUMMARY OF OPINION... 1 TABLE OF CONTENTS... 3 BACKGROUND... 4 TERMS OF REFERENCE... 5 ASSESSMENT Introduction History Review of historical sources Conclusions from the review of historical sources Basic concepts Toxicity-exposure ratio Assessment factors Species sensitivity distributions Effect of the assessment factor Quantifying the level of protection Correcting for differences in the SSD standard deviation Choice of test species causes variation in level of protection Conceptual description of method for calculating MFE Controlling the level of protection when more species are tested Factors affecting the level of protection Size of assessment factor (controllable) Choice of toxicity statistic (controllable) Magnitude of variation between species (not controllable) Differences between taxonomic groups Differences between substances Number of species tested (controllable) Choice of species tested (controllable) Shape of SSD Options for risk calculations Methods to achieve at least the current average level of protection For taxa where legislation requires only one species (e.g. Daphnia) = Method For taxa where legislation requires two species (e.g. fish) = Method Methods requiring specification of mean fraction exceeding endpoint (MFE) Standard deviation varies between substances Substance-specific standard deviation with no relevant historical data - Method Substance specific standard deviation and large historical database - Method Standard deviation does not vary between substances - Method Using assessment shifts in risk assessment Overview of alternative approaches Assumptions and limitations common to all methods Comparison of alternative approaches Options for longer term development Investigation of biased species Incorporation of information about biased species in risk calculations Methods for risk calculation using small to medium databases (e.g. chronic data) Alternative measures for quantifying the level of protection α 0 and λ 0 estimates for particular groups of substances The larger risk calculation Conclusions and Recommendations...38 DOCUMENTATION PROVIDED TO EFSA PPR PANEL...40 REFERENCES of 45

4 SCIENTIFIC PANEL MEMBERS...43 ACKNOWLEDGEMENT...43 LIST OF ACRONYMS...44 APPENDIX..45 BACKGROUND 1 In the risk assessment for plant protection products under Directive 91/414/EEC 2, acute toxicity data are required for rainbow trout and a warm water fish species to address the acute toxicity to fish, and acute toxicity data are required for Daphnia magna to address the acute toxicity to aquatic invertebrates. According to Annex VI 3 of Directive 91/414/EEC, C , an uncertainty factor of 100 is required on the LC50/EC50 of the most sensitive of the tested species (Guidance Document on Aquatic Ecotoxicology, Sanco/3268/2001 rev.3). Although the Uniform Principles given in Annex VI apply to national authorisations, the same criteria are being used also in the EU assessment of active substances due to the lack of such document. If, as a result of the first tier aquatic risk assessment, the acute TER for fish or invertebrates is breached, the Guidance Document on Aquatic Ecotoxicology foresees the possibility to refine the assessment by using additional toxicity tests with different species. The Guidance Document on Aquatic Ecotoxicology states the following in this regard: The testing of more species reduces the uncertainty of the risk assessment attributable to interspecies differences in sensitivity (see also section 5.6). It therefore permits a reduction of the uncertainty factor that is applied to the lower tier data. If a considerable number of additional species was tested in valid studies, then it is possible that the uncertainty factors that are applied to the lowest toxicity value could be lowered by up to an order of magnitude. However, the full order of magnitude reduction is likely only to apply to acute risk assessments, e.g., Annex VI TER trigger for acute risk to fish and aquatic invertebrates. In the SETAC Guidance document on higher tier risk assessment for pesticides ( HARAP-Report ; SETAC, 1999) it is stated that in general a dataset of acute single species tests on eight organisms could be used to describe the distribution of sensitivities of aquatic organisms. In the same document it is stated that probably five fish species are sufficient to describe the range of toxicities of fish. In this document no guidance is given with regard to the number of additional single-species studies necessary in case of a chronic risk assessment. On this background, notifiers tend to propose an uncertainty factor of 10 on the lowest LC50/EC50 value for the acute aquatic risk assessment when at least 8 aquatic invertebrate species or at least 5 fish species have been tested. Considering the situation, the PPR Panel is asked for their opinion whether a lowering of the factor from 100 to 10 (i.e. the full order of magnitude as mentioned in the Aquatic Guidance Document, Sanco/3268/2001) for the acute aquatic risk assessment could be seen as a standard when at least eight aquatic invertebrate species or at least five fish species have been tested to ensure the same level of protection as foreseen in the Directive 91/414/EEC. Or should the degree of lowering be defined individually, based on the number of species tested in order to ensure the same level of protection as foreseen in the Directive 91/414/EEC. 1 Submitted by EFSA s PRAPeR sector (coordination of the pesticide risk assessment peer review of active substances). 2 OJ N L230, , p1. 3 OJ N L265, , p of 45

5 Furthermore the opinion of the Panel concerning the possibility of lowering the uncertainty factor for chronic risk to aquatic organisms would be welcomed. And if this lowering is regarded as possible, an opinion on the probable order of magnitude for which situation (e.g. number of species tested) to ensure the same level of protection as foreseen in the Directive 91/414/EEC for the chronic risk to aquatic organisms is sought. TERMS OF REFERENCE The Scientific Panel on Plant Health, Plant Protection Products and their Residues (PPR Panel) of EFSA is asked for an opinion on: The possibility to refine the acute and chronic aquatic risk assessment by lowering the uncertainty factor if additional species were tested. In particular, the opinion of the Panel on how these trigger values could be reduced when additional single-species studies are available whilst still maintaining the same level of protection as foreseen in the Directive 91/414/EEC would be appreciated. ASSESSMENT 1 Introduction In order to protect the ecosystem against adverse effects of pesticides and other substances, specific risk assessment procedures have been developed. These involve the calculation of environmental levels of concern on the basis of laboratory toxicity data and the application of assessment factors, uncertainty factors or safety factors. These factors are meant to account for the extrapolation and uncertainties that occur when limited laboratory data are used to assess risk to the species-rich and variable environment of the field. In the guidance documents on pesticide risk assessment these factors are often called trigger values, because they are used to decide if higher tier risk assessment is required. In this opinion the term assessment factor is used, unless directly quoting another reference source, because this is a general term which can cover factors for both, extrapolation and uncertainty 4. They are important parameters in risk assessment and have a marked impact on the quality of regulations and the level of environmental protection. In Directive 91/414/EEC, Annex VI provides such fixed values as part of the decision-making criteria for plant protection products. A primary goal of risk assessment for a pesticide is to determine whether the predicted environmental concentration will have any unacceptable effects on species in nature. The calculations in the assessments are typically based on results from laboratory standard toxicity tests with a few species, e.g. one crustacean (Daphnia), two fish, one planktonic alga, one earthworm, one bird and one mammal. Each test species is assumed to represent a species assemblage in nature such as freshwater invertebrates, freshwater fish etc.. The assessment is straightforward if the test species can be assumed to be the most sensitive within the group it represents - or one of the most sensitive - towards all pesticides, and if toxicity under environmental conditions in the field is the same as measured under laboratory conditions. Then 4 Extrapolation occurs when measurements for one set of species or conditions are used to represent or estimate values for other species or conditions. Uncertainty results from limitations in knowledge, for example if the measurements are subject to experimental error or if the extrapolation is approximate. 5 of 45

6 all or most other species would be protected if the environmental concentration is below the no observed effect concentration (NOEC) of the test species. However, the assumption of the standard test species being the most sensitive ones is certainly not true for many substances. Also, as will be shown in section 3, data on more species will cause the risk assessment to become increasingly conservative if the same fixed assessment factors are applied to the most sensitive species toxicity value. To account for these issues, the use of variable assessment factors has been proposed on various occasions in the literature (Kooijman 1987, Van Straalen and Denneman 1989, Wagner and Løkke 1991, Aldenberg and Slob 1993, Jagoe and Newman 1997, Luttik and Aldenberg 1997, Aldenberg and Jaworska 2000, and Aldenberg and Luttik 2002). The general approach is to start with a description of the distribution of the toxicity data, i.e., a description of the variation in sensitivity across species. This distribution is then used to calculate a concentration at which, for example, 95% of the species are expected not to exceed their toxicity endpoints. Subsequently, a correction is calculated which takes into account how many measurements have been used for estimating the parameters of the distribution. If few data are available, this results in a large assessment factor. If more data are available, the assessment factor becomes smaller. Approaches of this type involve several types of risk management judgement about what constitutes an appropriate level of protection. First, they involve deciding what percentage of species should be permitted to exceed their toxicity endpoints; frequently a figure of 5% is suggested, but other figures could be considered. Second, they often involve deciding how much scientific certainty is required that this percentage will not be exceeded; frequently the assessment factors are based on 95% confidence intervals, but again other choices could be considered. These two factors can be treated separately or they can be combined, as they are in this opinion, by considering the mean fraction of species whose endpoint would be exceeded. Risk management judgements are outside the remit of the PPR Panel, so the Panel presents results for several alternative options for risk managers to consider. Further options are possible, and could be explored if required. Among several sources of uncertainty involved (as listed in section 2), the question put to the PPR Panel deals solely with the uncertainty related to the extrapolation between different species. All other sources of uncertainty are outside of the scope of this question and will not be evaluated in this opinion. Whichever of the options presented in this opinion will be taken for the species to species uncertainty, this would only replace part of an existing assessment factor but not all of it. The question also requires that any options for refining (changing) the current factors should maintain the same level of protection as foreseen in the Directive 91/414/EEC. However, this current level of protection in nowhere defined. Furthermore, the PPR Panel shows in section 4 that the level of protection is not the same for each group of organisms: it is higher for fish than aquatic invertebrates, and higher still for birds and mammals. The Panel also shows in section 4 that the level of protection can increase by over an order of magnitude when the number of species tested increases from 1 to 10. The PPR Panel has therefore developed methods that either maintain the current level of protection without specification or that can be applied to achieve any specified level of protection. In section 2 the PPR Panel reviews the history of assessment factors in ecotoxicology. In section 3 the Panel describes the basic concepts that will be used in this opinion. Section 4 gives an overview on the factors affecting the level of protection. In section 5 options will be provided that either maintain the current level of protection without specification or that can be applied to achieve any specified level of protection. Section 6 is an overview of the alternative approaches 6 of 45

7 and their limitations. In section 7 options for further research will be presented and section 8 gives conclusions and recommendations. 2 History 2.1 Review of historical sources In the literature (e.g. EC, 2003, a Technical Guidance Document on Risk Assessment) a number of uncertainties are identified which must be addressed to extrapolate from single-species laboratory data to a multi-species ecosystem. These areas may be summarised under the following headings: Intra- and inter-laboratory variation of toxicity data; Intra- and inter-species variation (biological variance); Short-term to long-term toxicity extrapolation; Laboratory data to field impact extrapolation (additive, synergistic and antagonistic effects from the presence of other substances may also play a role here). One of the first sources that mentions assessment factors is the report of the OECD Workshop on the extrapolation of laboratory aquatic toxicity data to the real environment (OECD 1992). This workshop addressed (and used data for) both pesticides and industrial substances, without differentiating between them. One of the Working Groups (i.e. Preliminary aquatic effects assessment - Procedures for extrapolating from small data sets) recommended the following assessment factors: 1000 applied to the lowest acute LC50, EC50 value or QSAR estimate within a data set on one or two aquatic species; 100 applied to the lowest acute LC50, EC50 or QSAR estimate within a data set comprising at a minimum algae, crustaceans and fish; and 10 applied to the lowest chronic NOEC value or QSAR estimate within a data set comprising at a minimum algae, crustaceans and fish. In OECD (1992, p ) these conclusions are also presented in a different wording: Chronic to field toxicity ratio To extrapolate from the lowest chronic NOEC to the field situation, it was agreed that available data support the use of a factor of 10. Acute to chronic toxicity ratio A factor of 10 was felt to be supported by most data (especially neutral organics) with some exceptions (e.g. anilines) where larger factors may be appropriate. Extrapolation from a single LC50 or EC50 to a set comprising fish, daphnia and algae If a LC50 or EC50 for a single species is available, the group proposed that a factor of 10 be used to extrapolate effects to the three taxa. In the relevant EU plant protection product regulation 5 it is less clear what the assessment factors are meant to be for, as no explanation is given. It is only stated that where there is a possibility of aquatic organisms being exposed, no authorisation shall be granted if: 5 Annex VI of Directive 91/414/EEC. It provides the decision-making criteria for plant protection products. 7 of 45

8 the toxicity/exposure ratio for fish and Daphnia is less than 100 for acute exposure and less than 10 for long-term exposure, or the algal growth inhibition/exposure ratio is less than 10. On the other hand, for industrial substances, the more recent Technical Guidance Document on Risk Assessment (EC, 2003) goes more into the purpose of assessment factors and addresses the different types of uncertainty in more detail (see also Table 1). In EC (2003, p. 99) it is stated that: For most substances, the pool of data from which to predict ecosystem effects is very limited, as in general, only short-term toxicity data are available. In these circumstances, it is recognized that, while not having a strong scientific validity, empirically derived assessment factors must be used. Assessment factors have also been proposed by the US EPA and OECD (1992). In applying such factors, the intention is to predict a concentration below which an unacceptable effect will most likely not occur. It is not intended to be a level below which the substance is considered safe. However, again, it is likely that an unacceptable effect will not occur. Table 1. Assessment factors to derive PNEC 6 aquatic for industrial substances (EC, 2003, p. 101) applied to the most sensitive species available. Available data Assessment factor At least one short-term L(E)C50 from each of three trophic levels of the base-set (fish, Daphnia and algae) 1000 One long-term NOEC (either fish or Daphnia) 100 Two long-term NOECs from species representing two trophic levels (fish and/or Daphnia and/or algae) 50 Long-term NOECs from at least three species (normally fish, Daphnia and algae) representing three trophic levels 10 Species sensitivity distribution (SSD) method 5-1 (to be fully justified case by case) Field data or model ecosystems Reviewed on a case by case basis The most recent official EU document, the Guidance Document on Aquatic Ecotoxicology (EC, 2002) for the evaluation of plant protection products, discusses uncertainty assessment factors in several places: On page 13 it is stated that in the preliminary risk assessment, the uncertainty factors (taken from Annex VI) of 100 and 10 are applied to acute and chronic endpoints respectively to account for potential inter-species differences in invertebrate sensitivity and other sources of uncertainty. It is also stated that for groups of organisms not specifically mentioned in Annex VI, the appropriate TER trigger values for related groups should be used for acute and chronic risk assessments. For example, assessments using data on insects (e.g., Chironomus sp.) should use the uncertainty factors specified for Daphnia (acute or long-term, whichever is more appropriate). Currently, the uncertainty factor specified for algae growth inhibition is also applied to higher aquatic plants and bacteria. 6 Predicted No Effect Concentration. A concentration below which unacceptable effects on organisms will most likely not occur This term is normally not used in the context of the evaluation of plant protection products but for chemicals assessment. 8 of 45

9 It says that testing of more species reduces the uncertainty of the risk assessment attributable to inter-species differences in sensitivity. It therefore permits a reduction of the uncertainty factor from Annex VI that is applied to the lower tier data. If a considerable number of additional species was tested in valid studies, then it is deemed possible that the uncertainty factors that are applied to the lowest toxicity value could be lowered by up to an order of magnitude. However, the full order of magnitude reduction is expected to apply only to acute risk assessments, e.g., the Annex VI uncertainty factors for acute risk to fish and aquatic invertebrates. Further, the document states that the number and type of additional species that should be tested depends on what is known about the mode of action or selectivity of the pesticide. In general, for substances which do not appear to be selective to aquatic organisms (i.e., all standard test organisms respond at similar - within an order of magnitude - concentrations), it is suggested that eight species could be used as a minimum to describe the distribution of sensitivities of aquatic organisms. Lower numbers may be appropriate for groups of organisms like fish which show a lower variability than for example algae. However, in cases where it is known that a specific group of organisms is particularly sensitive, then the species selected for further testing should be chosen from the relevant group. 2.2 Conclusions from the review of historical sources All approaches assume that in principle the ecosystem can be protected by knowing the effects of the substance for three species representing three different trophic levels in the aquatic ecosystem (i.e. fish, Daphnia and algae), although, it is possible to include other species from different groups of organisms. Annex VI of Directive 91/414/EEC and the OECD (1992) assume that a factor of 10 covers the difference between an assessment based on acute data and an assessment based on long-term data. The EC (2003) assumes that this difference requires a factor of 100 when data for three trophic groups are available. No explanation could be found for this divergence. The OECD (1992) and the EC (2003) assume that for extrapolating from long-term laboratory toxicity values to the ecosystem, a factor of 10 is appropriate. The OECD (1992) has no factor for the uncertainty between species, either within a group (e.g. fish) or for the uncertainty within a species. The EC (2003) does mention a number of uncertainties, but their magnitude is not quantified. Also, Annex VI of Directive 91/414/EEC and the pesticides guidance documents do not quantify the magnitude of uncertainties. In contrast to the other documents, the EC (2002) mentions that testing of more species reduces the uncertainty of the acute risk assessment attributable to inter-species differences in sensitivity. It states that a reduction of the uncertainty by an order of magnitude could be achievable (i.e. a factor of 10). Annex VI of Directive 91/414/EEC requires that there should be no unacceptable impact on the viability of exposed species, but does not define the type or magnitude of impact that is acceptable. The EC (2002) includes (pp.5-6) a discussion on aspects to be considered (such as species richness and densities, key species, ecosystems functions) but equally does not provide operational criteria for risk assessments beyond the tier I (e.g., percentage of species to be protected, degree of density reductions to be prevented, which key species to be protected, etc.). 9 of 45

10 The above overview indicates that assessment factors have been used inconsistently among different ecological risk assessment protocols. Overall there is a lack of clarity in the sources of uncertainty for which the various factors are intended to account, and there are sources of uncertainty that are not explicitly accounted for by the application of assessment factors. 3 Basic concepts 3.1 Toxicity-exposure ratio The standard risk assessment procedure for aquatic organisms requires the calculation of the toxicity-exposure ratio (TER): Toxicity Statistic TER = PEC where PEC is the predicted environmental concentration and Toxicity Statistic is a relevant toxicity endpoint (e.g. LC50 or NOEC for a specified type of adverse effect). Current practice is that the Toxicity Statistic is either the test result for a single species or is the minimum of the results for two or more species. 3.2 Assessment factors The TER is compared with values specified in Annex VI of Directive 91/414/EEC, e.g. 100 for acute risk to fish. These values can be regarded as assessment factors (AF) that allow for various uncertainties affecting the TER. If the TER is lower than the relevant assessment factor, then authorisation may not be granted unless an appropriate (higher tier) risk assessment demonstrates that the risk is acceptable. Part of the assessment factor is considered to allow for uncertainty due to variation in toxicity between species, i.e. to allow for the likelihood that some species in the field will be more sensitive than the species tested in the laboratory. As more species are tested, (a) more information is provided about the degree of variation between species, and (b) the minimum of the test results is likely to decrease. Therefore it would be reasonable to reduce the assessment factor when more species are tested. However, part of the assessment factor is intended to allow for other sources of uncertainty, although this is not clearly defined (see section 2). Therefore, when more species are tested, a reduction should be made only in the part of the assessment factor that relates to variation between species. It is commonly assumed (see section 2) that factors allowing for different uncertainties should be multiplied to obtain an overall assessment factor 7. In this case: AF = AF overall spec AF other where AFspec is the assessment factor to allow for uncertainty due to variation in toxicity between species. The EC (2002) states that the uncertainty factor for acute assessments could be reduced by up to a factor of 10 when sufficient additional species are tested, which implies that AFspec = 10 for acute toxicity. This Guidance Document also implies that AFspec for chronic toxicity is less than 10, but does not indicate a specific figure. 7 Other ways of combining assessment factors could be explored, see section of 45

11 It is beyond the scope of this opinion to analyse the various other uncertainties that might be covered by AFother. The opinion is therefore restricted to considering how AFspec might be altered when more than the minimum number of species is tested. 3.3 Species sensitivity distributions To answer the question posed to the PPR Panel it is necessary to quantify variation in toxicity between species. The natural tool for this purpose is the species sensitivity distribution or SSD. A detailed account of SSD theory and practice is provided by Posthuma et al. (2002). One way of depicting an SSD is as a probability density function, as shown by the curve in Figure 1. Each point represents acute toxicity for a different species, all tested with the same substance. 0.5 p robability densit y Log10 log10 log10 LC50, (mg/l) per L Figure 1. Example of Species Sensitivity Distribution for log10 acute fish toxicity (LC50) for substance A. The circles represent LC50 for 47 different fish species, and the curve shows a normal distribution fitted to the data. SSDs are more often presented in the form of cumulative distributions. An example is shown in Figure 2, using the same data as Figure 1. The number of species tested for the substance shown in Figure 1 is unusually large. Normally, there are fewer than ten tested species, especially because the SSD is limited to either fish, invertebrates or plants. The PPR Panel assumes a normal distribution on the log scale regardless of the number of species tested, because of the evidence for its general applicability. However, increasing the number of species tested implies increased certainty in estimating the mean and variance of the SSD, and this is reflected in methods 3, 4, and 5 described later in the opinion of 45

12 1 0.8 Fraction f raction exceeded exceede (FE) d Log10 log10 LC LC50, 50 (mg/l) (mg/l) per L Figure 2. Example of Species Sensitivity Distribution (SSD) for log10 acute fish toxicity (LC50) for substance A, with 47 different fish species. Note that in Figures 1 and 2, toxicity is plotted on a logarithmic scale. The curve in each Figure shows a normal distribution fitted to the logarithms of the data. Previous studies have found that, provided separate SSDs are made for fish, plants and invertebrates, normal distributions on the log scale give a reasonable fit (not rejected at the P<0.05 level) for a large proportion of substances (see section 4.6). On the basis of this evidence, the PPR Panel assumes that normal SSDs on the log scale generally provide an adequate description of variation between species for aquatic organisms and pesticides. 3.4 Effect of the assessment factor As explained in section 3.2, the PPR Panel considers only the part of the assessment factor that is intended to allow for uncertainty due to variation between species (AFspec). In effect, AFspec performs an extrapolation from a tested species to a more sensitive one, thereby taking account of more sensitive species in the risk assessment. This extrapolation is illustrated for a single substance by the curved arrow in Figure 3. The PPR Panel uses the term Adjusted Toxicity Statistic (ATS) to refer to the value obtained after applying the assessment factor AFspec, that is: Toxicity Statistic Adjusted Toxicity Statistic (ATS) = AF spec where the Toxicity Statistic is the measure of toxicity for the tested species (currently, the endpoint for the most sensitive tested species). The Adjusted Toxicity Statistic can therefore be interpreted as representing the endpoint for a more sensitive species of 45

13 1.0 Fraction Exceeded Fraction exceeded (FE) FE = 84% (level of protection) EF AF spec = = FE = 16% LC50 = Log 10 LC50 (mg/l) Log 10 LC 50 (mg/l) Figure 3. Hypothetical example of the effect of the assessment factor, applied to a single substance. The thick curve represents the species sensitivity distribution (SSD) for the substance. The filled circle on the horizontal axis represents the LC50 for a hypothetical tested species. Dividing this by an assessment factor AFspec of 10 (curved arrow) gives the adjusted toxicity statistic (ATS, open circle), which can be interpreted as representing the LC50 for a more sensitive species. One measure of the level of protection provided by AFspec is the fraction of species that are less sensitive than (i.e. protected by) the ATS. This is equal to 1 minus the fraction of species whose endpoint (e.g. LC50) would be exceeded if exposed to a concentration equal to the ATS, which can be seen from the dotted arrow. In this example, 1-FE is 0.84 (or 84%). 3.5 Quantifying the level of protection The PPR Panel was asked whether the trigger values (uncertainty or assessment factors) used in risk assessment can be reduced when more than the minimum number of species is tested, while still maintaining the same level of protection as foreseen in Directive 91/414/EEC. In order to answer this question, it is necessary to define a way of quantifying the level of protection. There are various ways in which the level of protection could be quantified. The PPR Panel has chosen in this opinion to quantify it by calculating the fraction of species that would be less sensitive than (i.e. protected by) the adjusted toxicity statistic (ATS). This can readily be obtained from the SSD by first calculating the fraction of species whose endpoint will be exceeded (FE) at a test concentration equal to the ATS, and then subtracting from 1. Therefore, the level of protection can be defined as 1 minus the fraction of species whose endpoint (e.g. LC50) would be exceeded at a concentration equal to the ATS. The derivation of this measure of the level of protection is illustrated graphically by the dashed arrow in Figure 3. Reading from the ATS on the horizontal axis up to the SSD and left to the vertical axis gives the fraction exceeded (FE) at that concentration (0.16 or 16% in the example); 13 of 45

14 subtracting from 1 gives the measure of the level of protection (0.84 or 84% in this case). Using a larger assessment factor AFspec would give a lower ATS, a lower fraction exceeded (FE), and a higher level of protection (1-FE). 3.6 Correcting for differences in the SSD standard deviation Different substances have different species sensitivity distributions. The mean of the SSD is lower for more toxic substances than for less toxic ones. In addition, analyses in section 4 suggest that the standard deviation of the SSD differs between substances, i.e. some substances show more between-species variation in sensitivity than others. It is important to consider how this might affect the level of protection provided by the assessment factor AFspec. In fact, it turns out that the level of protection (1-FE) is unaffected by differences in the mean of the SSD. This is illustrated in Figure 4 (SSDs 1 and 2). Changing the mean of the SSD moves it sideways without changing its slope, and leads to the same fraction exceeded (FE). However, increasing the standard deviation decreases the slope of the SSD. In this case, applying the same AFspec to both SSDs will lead to different values of FE, i.e. differing levels of protection, as illustrated in Figure 4 (SSDs 2 and 3). The same level of protection can be achieved for substances with different SSD standard deviations, if the assessment factor AFspec is adjusted accordingly. This is also illustrated in Figure 4. Increasing AFspec counteracts the effect of the higher standard deviation and results in the same FE. Two of the methods presented later in the opinion (methods 3 and 4) use this approach to take account of differing standard deviations. 1.0 SSD 1 SSD 2 SSD 3 Fraction Exceeded Fraction exceeded (FE) EF=10 AF=10 EF=10 AF=10 EF=10 AF=10 Increased EF AF to achieve same FE Log 10 LC 50 (mg/l) Log 10 LC50 (mg/l) Figure 4. Effect of varying SSD mean and standard deviation on the level of protection. Changing only the mean (SSDs 1 and 2) does not change the fraction exceeded (FE), but changing the standard deviation (SSDs 3) does change FE. The same FE can be achieved for different substances if the assessment factor is adjusted to account for any difference in standard deviation. Key: solid circle = LC50 for tested species, open circle = adjusted toxicity statistic (ATS), after applying AFspec of 45

15 3.7 Choice of test species causes variation in level of protection In Figure 4, the tested species (solid circle) is shown at the same point on each SSD. In practice, the tested species may come from different points on the SSD. This will cause variation in FE and consequently in the level of protection, even if the mean and standard deviation of the SSD are fixed. This is illustrated in Figure 5. The effect of the choice of test species has two important consequences. First, the actual level of protection achieved by applying a particular AFspec may be either higher or lower than expected, depending on where the tested species falls on the SSD. The expected (or mean) value of FE for a substance is determined by AFspec and the SSD standard deviation, but the actual value may be higher or lower, depending on the choice of test species. Second, if the procedure is applied to a large number of substances, the actual level of protection will vary between substances because the position of the tested species on the SSD will vary. However, the average or mean FE across substances will be equal to the expected FE. This has important implications for the choice and interpretation of a measure for the level of protection. The PPR Panel chose in this opinion to use the mean fraction exceeded (MFE), i.e. the expected value for a single substance or the mean (average) value over many substances. This choice was made primarily for practical convenience, because it makes it possible to derive general assessment factors that can be applied to different pesticides without the user needing to make complex calculations. It is important to remember that, for individual substances, the actual FE will vary above and below the expected value MFE, as is illustrated in Figure 5. Alternative measures for the level of protection could be devised to take account of this variation, e.g. the proportion of substances exceeding a stated level of FE. 1.0 EF=10 AF=10 S3 Fraction Exceeded Fraction exceeded (FE) EF=10 AF=10 EF=10 AF=10 S1 S Log 10 LC 50 (mg/l) Log 10 LC50 (mg/l) Figure 5. Choice of test species influences the level of protection. Applying the same assessment factor AFspec to three species (S1, S2, S3) from different points on the SSD leads to differing levels of protection (FE). Key: solid circle = LC50 for tested species, open circle = adjusted toxicity statistic (ATS), after applying AFspec of 45

16 Choosing which measure should be used for the level of protection implies risk management judgements (e.g. whether concern should be focussed on the average impact or on the frequency of impacts exceeding a particular level), which are outside the remit of the PPR Panel. Calculations shown in this opinion using the MFE could be carried out for other measures, if required by risk managers, and might give different answers. 3.8 Conceptual description of method for calculating MFE This section aims to provide a conceptual understanding of the procedure used for calculating MFE. The mathematical details are set out formally in the Appendix. The approach used by the PPR Panel was originally developed by van Straalen (1990, 2002) for a type of risk characterisation, combining species sensitivity distributions with distributions of exposure concentrations and calculating an average measure of risk. The approach was subsequently extended by Aldenberg et al. (2002). The approach is illustrated conceptually in Figure 6, which adapts the graphical representation originally developed by van Straalen (1990). The Figure represents the calculation of the MFE for a single hypothetical substance, given a particular choice of assessment factor AFspec. The SSD for the substance is shown as a cumulative curve. If a single species is selected at random for testing, and the resulting LC50 is divided by the assessment factor, then a single value for the adjusted toxicity statistic (ATS) will be obtained. However, this single species could come from any point on the SSD. If the process were repeated a large number of times, each time selecting a different species, they would come from different points on the SSD and generate different values for the ATS. The result would be a distribution for the ATS, as shown in Figure 6. For any given concentration on the horizontal axis of Figure 6, the SSD shows a possible value for the fraction of species whose endpoint would be exceeded (FE), and the ATS distribution shows the frequency with which that FE would occur if a large number of test species were selected at random. The mean FE (MFE) over all these instances can be found by multiplying each value of FE (from the SSD) by the frequency with which it occurs (from the ATS distribution), and then summing the results. This operation is illustrated by the third curve in Figure 6. Each point on the third curve is the product of the corresponding values from the SSD and ATS distributions, and the total area under the curve gives the mean FE (MFE) of 45

17 Probability density for the ATS Fraction exceeded (FE) Log 10 LC 50 (mg/l) Figure 6. Graphical representation of the method used for calculating the mean fraction of species whose endpoint would be exceeded (MFE), illustrated for a single hypothetical substance and an assessment factor (AFspec) of 10. The dashed cumulative curve represents the species sensitivity distribution (SSD), which has a standard deviation of 1. The dotted curve shows the distribution of the adjusted toxicity statistic (ATS), showing how it varies when different test species are selected at random from the SSD. The solid curve shows the product of values from the other two distributions, and the area under this curve gives the mean fraction of species whose endpoint would be exceeded (MFE). For the hypothetical substance in Figure 6, the standard deviation of the SSD is 1 and the assessment factor AFspec is 10, resulting in MFE = 24%. The MFE depends on both the AFspec and the standard deviation (as shown in Figure 4). If the standard deviation is the same for all substances (as is assumed for method 3 later in the opinion), then AFspec can be adjusted so as to achieve the level of protection (1-MFE) required by the risk manager. If the standard deviation varies between substances (as is assumed for methods 4 and 5), then a different AFspec is used for each substance, to adjust for their differing standard deviations and achieve the same MFE for each (this was illustrated in a simplified way in Figure 4). Because the MFE for each substance is the same, this will also be the MFE across a large number of substances. 3.9 Controlling the level of protection when more species are tested The PPR Panel was asked, in particular, for an opinion on how the uncertainty factors/trigger values for the acute and chronic aquatic risk assessment could be reduced when additional species are tested, whilst still maintaining the same level of protection as foreseen in the Directive 91/414/EEC of 45

18 The PPR Panel examined several different methods that could be used to refine the risk assessment when additional species are tested. Some of the methods (methods 1 and 2) do not change the current assessment factors. Instead, they involve changing the toxicity statistic that is used, so as to maintain at least the level of protection (as measured by 1-MFE) that is implied by the minimum requirements of Directive 91/414/EEC. The other methods considered by the PPR Panel (methods 3, 4, and 5) do involve changing assessment factors, but they require specification of particular values for the level of protection. In particular, they require specification of what level of MFE is tolerable. Specifying this involves a risk management judgement (what level of impact is tolerable) and is therefore outside the remit of the PPR Panel. Therefore the opinion includes tables that enable assessment factors to be calculated for several different values of MFE (10%, 5% and 1%). Calculations could be carried out for other values, if required by risk managers. Finally, it is important to emphasise that the measure of level of protection discussed in this opinion only relates to the effect of the assessment factor that is used to take account of uncertainty in extrapolating toxicity between species (AFspec). The overall level of protection will depend partly on this, but also on other parts of the risk assessment including any conservative assumptions (e.g. regarding exposure) and assessment factors for other uncertainties (AFother). 4 Factors affecting the level of protection The choice of assessment factors clearly affects the level of protection. Moreover, for any particular value of the assessment factor, the MFE (or other measure of risk) depends on a number of other factors, some of which are under human control of the decision-maker and some of which are simply features of the SSD. Figure 7 shows how the mean fraction of species whose endpoint would be exceeded is affected by various factors. A detailed description of each panel is given in the appropriate sub-section below. One factor which does not affect the MFE is the mean of the SSD. In the hypothetical example, changing the mean only changes the numbers on the horizontal and left-vertical axes in Figure 6, the rest of the Figure is unchanged of 45

19 Probability density for the ATS MFE (shaded area) is 8 % Fraction Exceeded (FE) Probability density for the ATS MFE (shaded area) is 18 % Fraction Exceeded (FE) Log 10 LC50 (mg/l) Log 10 LC50 (mg/l) a) assessment factor=100 b) toxicity statistic is geometric mean of data for 5 species Probability density for the ATS MFE (shaded area) is 3 % Fraction Exceeded (FE) Probability density for the ATS MFE (shaded area) is 8 % Fraction Exceeded (FE) Log 10 LC50 (mg/l) Log 10 LC50 (mg/l) c) toxicity statistic is minimum of data for 5 species σ = 1 d) standard deviation of SSD 2 Figure 7. Effects on the mean fraction of species whose endpoint would be exceeded (MFE) of changing parameters from those in Figure 6. a) assessment factor is 100 instead of 10; b) the toxicity statistic is the geometric mean of endpoints for 5 species instead of 1; c) the toxicity statistic is the minimum of the data from 5 species ; d) the standard deviation of the SSD, σ, is ½ instead of Size of assessment factor (controllable) Changing the assessment factor changes the level of protection. A larger assessment factor corresponds to a larger shift to the left and increases the level of protection. Figure 7a shows what happens in the hypothetical example from Figure 6 if the assessment factor is increased from 10 to 100. The distribution of the adjusted toxicity statistic shifts left by one unit from its position in Figure 6. Consequently, the distribution of FE concentrates at lower values and so the MFE reduces to 8%. Figure 7b will be discussed in section Choice of toxicity statistic (controllable) In Figure 6, the acceptable exposure concentration was determined by applying an assessment factor to the toxicity endpoint for a single species. When more species endpoints are measured, an assessment factor might be applied to any one of a number of different measures such as the minimum, geometric mean or median (or even another order statistic) of 45