Deliverable 28: Specification of low risk products REBECA ...

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diseases is difficult to capture in this section. Effects described above focus on nontarget mortality - an approach not suited to describe the dynamics of a microbial community. Therefore, in the absence of more detailed knowledge, the likelihood and magnitude values in this category are set to three for antagonistic micro-organisms. As in the previous category, the risk score results from the multiplication of likelihood and magnitude of the effect. Direct Effects. Whereas the host/target range describes the spectrum of organisms affected by the pest control product, the direct and indirect effects characterise the impact on the most sensitive non-target organism or group. This portion of the risk indicator is calculated by multiplication of the likelihood of an adverse effect (mortality) with its magnitude. The likelihood of non target mortality can, for instance, be deduced from dose/response data or an ‘impact assessment system’ such as the NAESI approach presented above (compare Mineau et al., 2008). Somewhat more challenging is the assessment of the non-target effects for antagonistic organisms used for disease suppression. These organisms do not kill their targets, but rather suppress the growth of disease-causing micro-organisms by establishing in their ecological niche. Capturing the suppression of non target microorganisms by an antagonist in the proposed indicator will only be considered if a substantial long-term suppression and/or consequential indirect effects are expected. For instance, suppression of a saprotrophic basidiomycete fungus in the soil after application of an antagonist to wild blueberry would be considered as a non-target effect, whereas transient changes in the soil or phylloshpere microbiota would not. The scoring regime for direct effects, described in Table 4, allows for an assessment based on likelihood and magnitude of the effect (derived from ERBIC system), or alternatively on the basis of the highest risk quotient as determined from a deterministic risk assessment approach as described by PMRA (Pest Management Regulatory Agency, 2007). Table 4. Risk of direct effects. The overall score is either the product of scores assigned for likelihood and magnitude, or the square of the score assigned for the highest risk quotient as described by the PMRA. Direct Effects Score Likelihood Magnitude Score Highest Quotient 1 Very unlikely (< < 5 % mortality 1 %) 1 2 ( = 1) < 0.1 2 Unlikely (1 %-10 %) < 50 % mortality 2 2 ( = 4) < 1 3 Possible (10 %- > 50 % mortality or > 10 % 3 2 ( = 9) 50 %) short term suppression < 10 4 Likely (50 %-80 %) > 50 % mortality ore > 10 % 4 2 (= 16) permanent suppression < 100 > 10 % long term 5 Very likely (> 80 %) suppression or local 5 2 (= 25) > 100 extinction Risk 23
Indirect Effects. Indirect effects in this context are defined as changes in the ecosystem that are a consequence of a direct effect caused by the use of a pesticide. For instance, the reduction of pollinators will reduce the reproduction of plants that rely on these pollinators. Likewise, pesticide effects on earthworms, aquatic plants, or microbial activity will temporarily or permanently alter the ecosystem the product is applied to. Because of their indirect nature, the level of uncertainty in assessing these effects is greater than for the other components of the risk indicator system, and the assessment must mainly rely on expert judgement. However, the estimation of how severe the occurrence of a non-target effect is on an ecosystem level is considered significant for the appropriate assessment of pesticide risk to the ecosystem. Table 5. Score for indirect effects on the ecosystem. Assignments are generally based on expert judgement as indicated by the ecosystematic position of organisms affected by direct effects, and the severity of anticipated effects. Indirect Effects Score Likelihood Magnitude 1 Very unlikely no significant impact on whole ecosystem 2 Unlikely minor and short-term impact on parts of ecosystem 3 Possible significant short-term impact on parts of 4 Likely ecosystem significant long-term impact on parts of ecosystem 5 Very likely significant long-term impact on whole ecosystem Table 5 describes the scoring mechanism for indirect effects. As a general guidance, substances that score high in the host range and direct effects sections will in most cases have a higher likelihood for indirect effects. Vertebrate toxicity. We propose to apply a weighting factor to direct effects (E D ) to increase the value for non-target losses if vertebrates are affected. The weighting scheme is described in Table 6. Table 6 Factors assigned whether or not direct effects concern vertebrates. Vertebrate toxicity Factor Magnitude 1 No vertebrates are affected 1.5 Poikilothermic vertebrates are affected by non-target effects 2 Homeothermic vertebrates are affected 24
Page 1 and 2: Deliverable 28: Specification of lo
Page 3 and 4: Table of contents Introduction.....
Page 5 and 6: Further more the substances which a
Page 7 and 8: Regulator’s experiences in defini
Page 9 and 10: Bacteria directly consumed by human
Page 11 and 12: Annex I. List of taxonomic units pr
Page 13 and 14: Annex 2 Developing a risk indicator
Page 15 and 16: cannot afford the high costs for a
Page 17 and 18: esulting from microbial pest contro
Page 19 and 20: ERBIC Risk Indicator To our knowled
Page 21 and 22: The multiplication of non-target ri
Page 23: For a given chemical pesticide, the
Page 27 and 28: Table 7 Risk scores and calculated
Page 29 and 30: These results demonstrate that the
Page 31 and 32: Jaronski ST, Goettel MS & Lomer CJ
Page 33 and 34: Pest Management Regulatory Agency (

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