Arpaia S.

Bartsch D.

Devos Y.

Gathmann A.

Hails R. S.

Kiss J.

Lheureux K.

Manachini B.

Mestdagh S.

Neemann G.

Ortego F.

Perry J. N.

Schiemann J.

Sweet J. B.

English

ENEA-IRIS Open Archive

Proc. R. Soc. B (2011) 278, 982–984 Downloaded from https://royalsocietypublishing.org/ on 17 May 2021 doi:10.1098/rspb.2010.2667Published online 5 January 2011Invited replyThe acc10.1098ReceivedAcceptedThe usefulness of a mathematical model ofexposure for environmental risk assessmentWe respond to the Comment of Lang et al. [1] regarding MON810 than the former, a further example of Perryour mathematical model [2] of exposure of non-targetLepidoptera to Bt-maize pollen expressing Cry1Abwithin Europe. Lang et al. remark on the degree towhich the model was subject to uncertainty. Perry et al.[2] did indeed emphasize precaution: they made four sep-arate decisions to model worst-case scenarios; identifiedsix distinct sources of variability to which their resultsmight be sensitive; and emphasized six different basesfor the uncertainty of predictions. Lang et al. rightlyemphasize the importance of identifying to which par-ameters the results of a model are most sensitive; Perryet al. should perhaps have emphasized more that theparameter to which their estimates of mortality weremost sensitive was undoubtedly the variable measuringthe rate of change of mortality with concentration/doseof the Cry1Ab protein (i.e. the slope of the probit/logitregression line; see below).Regarding the relationship between the toxicity ofMON810 and Bt176 pollen, Lang et al. imply that therelationship between mortality and dose may be nonlinear.Regressions from bioassay should always be checked fornonlinearity, but there was no evidence of this in any ofthe extensive number of regressions of Saeglitz et al. [3,4]upon which our slope estimate was based. Of course, thestandard transformation of mortality to probits (or logits)and the logarithmic transformation of concentration [5,6]are designed to achieve a linear regression; bothpapers cited by Lang et al. use this method. Data fromone of these papers [7] were tested for nonlinearity;none was found, and no disproportionally highermortality at low Cry1Ab concentrations could be verified(figure 1).Lang et al. are correct that Perry et al. used the range ofpublished [8,9] values (12.2–78.9) to derive an average ofthe ratio of the concentration of the Cry1Ab proteinexpressed in pollen of maize Bt176 relative to that inmaize MON810 for which a 31.05-fold difference wasassumed. This is already likely to be a worst-case under-estimate because, as Sears et al. [8] noted, the value ofexpression for MON810 was near the current level ofdetection by immunoassay. We do not agree with Langet al.’s interpretation of the data from Nguyen [10]: theycompared the smallest Bt176 value from 2002 to thelargest MON810 value from 2003. The within-yearratio of Bt176 : MON810 was 64.8 in 2002 and 30.5 in2003. The latter value, very close to that adopted byPerry et al., leads to larger mortality estimates forompanying comment can be viewed at http://dx.doi.org//rspb.2010.2085.10 December 201013 December 2010 982et al.’s use of worst-case scenarios. Figure 2 shows theimportance of the distinction between the intercept andslope of the probit/logit line in this issue. The conclusionsof the model for risk management depend on the degreeof estimated mortality. The conclusions are clearlyhighly sensitive to assumptions concerning the slope.They are sensitive, but much less so, to the intercept; itis the intercept that is governed by the Bt176 :MON810 ratio. Figure 2 demonstrates the effect ofchoosing an alternative worst-case value of the ratio(12.2) at the end of the range.Regarding the assumption of equal susceptibility forthe butterflies Inachis io and Vanessa atalanta, we apolo-gize for the incorrect citation given by Perry et al. Weacknowledge that data to compare the sensitivities ofI. io and V. atalanta are very limited. We are aware of noevidence that the sensitivities differ; unpublished datafrom a single field experiment appear to suggest thatthey may not. Both Perry et al. and Lang et al. remarkedon the need for further data on European Lepidopteraof conservation concern.Lang et al. argue that the experimental methodologyof Felke et al. [11] was likely to give results that under-estimated true mortality. However, in many experimentswith MON810, larvae have been exposed to longer timeperiods than those of Felke et al. [11]: 10 days [12]; 14–22 days [13]; 7 days [14]; 10–14 days [15]. These andother experiments with MON810 pollen have shown nonegative effects when lepidopteran larvae were exposedto MON810 pollen alone. Furthermore, susceptibilityto Bt toxin declines with age in older instars (e.g.[16]), so any potential for negative impacts ofBt pollen is reduced as the larvae develop. Lang et al.claim that fig. 1 of [7] demonstrates long-term effects(longer than 7 days) following a short acute dose ofBt. However, comparison of treatment and control inthat figure appears to contradict rather than supporttheir claim. In the period between 7 and 27 days, themortality for a dose of 2.5 mg of Bt is only marginally(approx. 2%) greater than that of the control, whilethe mortalities for all other doses (1, 5, 7.5, 10, 20,30 mg) are at least 5 per cent less than that of thecontrol.We fully agree with Lang et al. that sublethal effectsshould encompass fecundity and other parameters. How-ever, many studies neglect to test parameters other thanlarval or pupal weight (e.g. [7]). Perry et al. emphasizedthat ‘our methods are subject to considerable uncer-tainty’, a caveat repeated in the final sentence of theDiscussion.This journal is q 2011 The Royal Society20–20.8 1.2log10 (dose)1.6logit (mortality)Figure 1. Logit-transformed observed percentage mortalityfrom fig. 1 of [7] plotted against logarithmically trans-formed (base 10) dose (Bt-maize pollen consumed) fromtable 1 of [7], with fitted linear regression for 2 days(filled circles, solid line), 7 days (open circles, dashedline) and 14 days (stars, dotted line). All three regressionsare highly significant (p , 0.001) with no indication ofnonlinearity. The addition of a nonlinear term for curva-ture to the linear regressions was not significant for anyof the three periods (F1,3 ¼ 0.20, F1,4 ¼ 1.83, F1,4 ¼ 1.20,respectively).0.050.010.0010.00010.510–710–12400 58001500ABconcentration(pollen grains cm–2)estimated mortality rate Figure 2. The probit regression line (thick solid line withbutton ends) for the LC50 of larvae of Inachis io assumed byPerry et al. [2] according to the slope value 1.095 estimatedby Saeglitz et al. [3,4]. The assumed concentration of theCry1Ab protein in pollen of maize MON810 is 31.05-foldless than that in maize Bt176. Shown for comparison are thelines expected if instead the different slope values of 2.25 (aver-age of estimates of Farinós et al. [18]; thick long-dashed linewith button ends) or 5.79 (estimated by Felke et al. [11];thick short-dashed line with button ends) had been assumed.All three lines go through point A, the assumed LC50 of5800 maize MON810 pollen grains cm22, for which themortality rate is 0.5. Within the crop, typical pollen concen-trations are 10-fold less than this, and at the crop edge 30-fold less, and less still at distances into the margin, furtherfrom the edge. Also shown for comparison are three corre-sponding lines (thinner lines without button ends) with thesame slope but different intercepts to the first three, represent-ing the lines expected if the assumed concentration of theCry1Ab protein in pollen of maize MON810 was only 12.2-fold less than that in maize Bt176. All three lines of thissecond set go through point B, for which the mortality rate is0.5 and the assumed LC50 of 2283 grains cm22. Estimatedmortality is more sensitive to the differences in slopes than tothe difference in intercepts.Invited reply. Usefulness of exposure model J. N. Perry et al. 983 Downloaded from https://royalsocietypublishing.org/ on 17 May 2021 Lang et al. stated that ‘all publications cited in Perryet al. in support of a possible reduction in exposurethrough behaviour of the larvae refer to Danaus plexippus’,but have perhaps overlooked Perry et al.’s text: ‘Bothspecies [V. atalanta and I. io] are somewhat protectedunder field conditions from pollen deposition; theformer species creates “leaf bags”, the latter builds webs(e.g. [17])’. We agree that the extent to which exposureis reduced through such behaviour is variable but it issurely not contentious to state that there is evidence forthis for neonate larvae within Europe (see e.g. http://tris-tram.squarespace.com/home/2009/6/9/peacock-butterfly-caterpillars.html).Regarding sensitivity analysis, it is important to allowfor the fact that depositions of pollen in the field occurat far lesser concentrations than the LC50s for the threespecies considered by Perry et al. In consequence, asshown in figure 2, differing assumptions for the slope ofthe assumed probit (or logit) line will have little effecton the results for concentrations close to the LC50, butresult in very large differences at concentrations aroundthose expected within the crop or in the margin. Withinthe crop, the estimated mortality using the slope esti-mated by Felke et al. [11] is vanishingly small and sucha value would be impossible to measure in field con-ditions. Even a doubling of the Saeglitz et al. [3,4] slopeof close to 1.1 to the moderately small average 2.25 esti-mated by Farinós et al. [18] would result in roughly10-fold decrease in estimated mortality. It is for thesereasons that we consider that the consequence of this sen-sitivity completely outweighs any of the several effectsclaimed by Lang et al. to engender uncertainty andaffect mortality estimates. We regard them as minor com-pared with the ‘safety margin’ factor of 8 3 1027 bywhich Perry et al. inflated the estimated mortality throughdeliberate choice of a small value of the logit slope,designed to give worst-case mortality.Proc. R. Soc. B (2011)The value of the Perry et al. model is that it provides atransparent, structured and simple approach to exposureanalysis that may be followed for other species and taxain other settings, if sufficient data become available.Further, in its derivation of an integrated mortality–distance relationship, it offers the opportunity forrelatively accurate laboratory-based estimation ofmortality–dose relationships to supplement relativelyinaccurate determinations of mortality in the field. Weagree with Lang et al. that species’ sensitivity to particularGM events that express different forms of Cry1 proteins isan important determinant of mortality; also that furtherdata would be welcome on the mortality–dose relation-ships (particularly regarding the slopes) for a range ofspecies, especially those of conservation concern. How-ever, we disagree that we have been incautious984 J. N. Perry et al. Invited reply. Usefulness of exposure model Downloaded from https://royalsocietypublishing.org/ on 17 May 2021 regarding the implications of our results for conclusionsregarding regulatory policy. We therefore reaffirm therobustness of our conclusion from our model that, afteraccounting for large-scale exposure effects, the ‘estimatedenvironmental impact of MON810 pollen on non-targetLepidoptera is low’.We thank the European Food Safety Authority for paying forEXiS Open Choice.J. N. Perry1,*, Y. Devos2, S. Arpaia3, D. Bartsch4,A. Gathmann4, R. S. Hails5, J. Kiss6, K. Lheureux2,B. Manachini7, S. Mestdagh2, G. Neemann8, F. Ortego9,J. Schiemann10 and J. B. Sweet111Oaklands Barn, Lug’s Lane, Broome, NorfolkNR35 2HT, UK2European Food Safety Authority (EFSA), GMO Unit,Largo Natale Palli 5/A, 43121 Parma, Italy3National Agency for New Technologies, Energy andSustainable Economic Development, Research Centre Trisaia,75026 Rotondella, Italy4Bundesamt für Verbraucherschutz und Lebensmittelsicherheit(BVL), Federal Office of Consumer Protection and FoodSafety, Mauerstrasse 39-42, 10117 Berlin, Germany5Centre for Ecology and Hydrology, Maclean Building,Benson Lane, Wallingford OX10 8BB, UK6Plant Protection Institute, Szent István University, Pater K. 1,2100 Gödölló́, Hungary7Animal Biology Department, University of Palermo, ViaArchirafi, 18, 90123 Palermo, Italy8Büro für Landschaftsökologie und Umweltstudien, Muehlenweg60, 29358 Eicklingen, Germany9Centro de Investigaciones Biológicas (CSIC), Departamento deBiologı́a de Plantas, Laboratorio Interacción Planta-Insecto,C/ Ramiro de Maeztu 9, 28040 Madrid, Spain10Julius Kühn Institute, Federal Research Centre for CultivatedPlants (JKI), Institute for Biosafety of Genetically ModifiedPlants, Erwin-Baur-Strasse 27, 06484 Quedlinburg, Germany11Sweet Environmental Consultants, 6 The Green, Willingham,Cambridge CB24 5JA, UK*Author for correspondence (joe.perry@bbsrc.ac.uk).REFERENCES1 Lang, A., Brunzel, S., Dolek, M., Otto, M. & Theißen, B.2011 Modelling in the light of uncertaintyof key parameters:a call to exercise caution in field predictions of Bt-maizeeffects. 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The usefulness of a mathematical model of exposure for environmental risk assessment

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The usefulness of a mathematical model of exposure for environmental risk assessment

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