Answer to comments made by J. Smith on "Is non-human species radiosensitivity in the lab a good indicator of that in the field? Making the comparison more robust" by Beaugelin-Seiller et al. (2018)
Karine Beaugelin-Seiller*
karine.beaugelin@irsn.fr
Institut de Radioprotection et de Sûreté Nucléaire, PSE-ENV/SRTE/LECO, St Paul les Durance, 13115, France
*Corresponding author.
Jacqueline Garnier-Laplace
Institut de Radioprotection et de Sûreté Nucléaire, PSE-ENV Fontenay-aux-roses, 92260, France Dear Editor,
We appreciate J. Smith's interest to our publication “Is non-human species radiosensitivity in the lab a good indicator of that in the field? Making the comparison more robust", even more to a companion- publication released five years ago by Garnier-Laplace et al. (2013). We agree with J. Smith about the necessary caution to observe when dealing with effects of ionizing radiation on wildlife, especially regarding the comparison that could be made with human radiation protection issue. We also share his reservations about the validity of some conclusions drawn in papers dealing with radiocontaminated field studies previously published, especially with regard to the assessment of exposure levels at which effects have been reported. This remains the main message of our past and present publications where weaknesses in field dose assessments were identified as one of the major biases for a proper interpretation of ecological data from radiocontaminated field studies, either related to the Chernobyl or the Fukushima accident. We think that the key question is even more complex than only “to know at what dose and dose rate does significant damage to wildlife populations occur" as J. Smith says, since the answer to such question is highly dependent of exposure circumstances (e.g, duration and period of exposure, pathways, radionuclides, other non-radiological stressors, species and life stage, genetic diversity, ecosystem types). This question was clearly pinpointed in our previous publications (e.g, “It is the accurate quantification of absorbed dose that is the greatest challenge in the correct use of effects data from Chernobyl", Garnier-Laplace et al. (2008)). Ecological data are rarely accessible for researchers who are not directly involved in the implementation of the field strategy. More specifically data related to wildlife exposure to ionizing radiation in the real world are even rarer and were dominantly produced by one group of researchers under the leadership of A.P. M0ller and T. Mousseau. In this context, it is difficult to ignore such unique data, despite their potential weaknesses. At the opposite we believe it is essential to re-examine them in light of the latest advances in our scientific fields and critically analyze the outcome using the best available methods regarding data treatment, either for dose reconstruction or for statistical analyses. In this continuous process for improvement to reduce remaining uncertainties and enhance the robustness of conclusion, sharing data from ecological observations including associated information such as potential confounding factors is a key approach to build upon the state of the art. This is the reasons why since ca. five years we have tried to work together with producers of field data in order to access their raw data sets and any related information they could have acquired without necessarily publishing or making them publicly available. Our aim was to produce an analysis of such data as sound, robust and transparent as possible, notably to make it reproducible. Additionally, the rational application of a common approach to re-analyze different data sets would give associated results a certain consistency. For example, our previous publication dealing with the birds community in the Fukushima impacted territories (Garnier-Laplace et al., 2015; Beaugelin-Seiller et al., 2018) demonstrated that a proper dose reconstruction made consistent the ecological findings with the state of the art about effects of ionizing radiation on birds as published in ICRP Publication 108 (ICRP Environmental Protection, 2008).
The objective of the commented paper was not “to evaluate the hypothesis that animals in the natural environment are much more radiosensitive than those in laboratory settings" as understood by J. Smith.
Instead, we discussed in the paper how data from the field may challenge or not effects benchmarks that are generally derived from data acquired in the lab or controlled field for several reasons detailed in our paper and in Real and Garnier-Laplace (2018). Similar was the objective of the paper published from Garnier-Laplace et al. (2008) by comparing critical chronic radiotoxicity data sets (i.e. EDR10) estimated from studies in the Chernobyl Exclusion Zone vs. those estimated from controlled experiments (field or lab). The data used were extracted from the FREDERICA database quality-checked by the FASSET and ERICA consortia according to several criteria (see Copplestone et al, 2008).
About “Remarkable claims" as discussed by J. Smith
The total dose which would have led to a 50% reduction of birds number in the Fukushima area mentioned in our paper was established by Garnier-Laplace et al. (2015), who estimated that birds may have received total dose rates between from less than 1 up to ca 100 pGy h-1 in 2011, the higher bound decreasing to about 60 pGy h-1 three years after the accident. Part of these values exceed indeed the ICRP DCRL
value for birds (4-42 gGy h-1; ICRP 2008) and were estimated by the authors for 90% of the studied species within the range of dose rates the ICRP considered as impairing the reproductive success of such animais (42-420 gGy h-1). This convergence contributes to build a weight of evidence in favor of a link between the number of birds and their exposure to ionizing radiation, at the level of dose rates calculated by Garnier- Laplace et al. (2015). However this link is really complex and depends on various circumstances because the quantification made of dose-effects relationship is done on the used dataset and the global GLMM we implemented. This limitation mentioned by Garnier-Laplace et al. (2015), was omitted by J. Smith in his judgement. For example, the interpretation from J. Smith “Few people would want to live in an area in which birds are, apparently, dying or failing to reproduce as a direct or indirect effect of radiation,..." omits birds movement to other areas accordingly to species-related behavior and sensitivity to various factors, including non- radiological ones. This is largely discussed in Garnier-Laplace et al. (2015).
We also strongly disagree with J. Smith claiming the ICRP occupational effective dose limit (fixed at 20 mSv per year to protect workers from stochastic effects) is comparable to the transitional PNEDR of 2 gGy h-1 proposed for reproduction, mortality and morbidity of non-human vertebrates by Garnier-Laplace et al. (2010). Those two dose criteria have nothing in common to allow such direct comparison. The first one deals with preventing stochastic effects in a unique species (adult human), at work, and is suitable for use as a regulatory dose limit under planned exposure situations. The other deals with deterministic effects of ionizing radiation (which may have impact on population demography) in a wide range of non-human vertebrate species whatever the life stages. It is not a dose limit (note that the principle of dose limitation is not applicable for non-human species) but a benchmark value to be used for the purpose of risk characterization at an initial stage of screening. For us, the comment “Though it would be a mistake to assume that the current ICRP recommendations for human radiation protection are infallible, the contradiction illustrates how remarkable are the claims being made by some studies of wildlife at Chernobyl and Fukushima." is not justified by such inappropriate comparison.
About “Weak and misleading evidence" found by J. Smith
The point made by J. Smith relates mainly to (i) the critical issue of effects data selection for any type of meta-analysis (e.g, statistical distributions such as Species Sensitivity Distribution-SSD), (ii) the issue of taking into account confounding factors in ecological data sets (habitat changes, additional stress like predator pressure,.).
The first item has been extensively discussed in the field of ecotoxicology in the last 20 years. Regarding benchmark derivation for the purpose of ecological risk assessment associated to radiological exposure situations, a review publication discussed in details approaches that were adapted from ecotoxicological guidance with the suite of FASSET-ERICA-PROTECT EC-funded projects (Real and Garnier-Laplace, 2018). The advantages and limitations are discussed there and there is no added value to repeat this.
Regarding the second item dealing with field ecological data restricted to those outcoming from the Chernobyl Exclusion Zone (to serve the lab-to-field comparison), a number of original papers did not pay enough attention to this issue which was considered in data selection by Garnier-Laplace et al. (2008). In this past work, “data sets were rejected if obvious confounding variables were apparent and uncorrected (e.g, seasonal effects in species abundances)". Data sets were also rejected in case primary information did not allow the reconstruction of dose rate-effect relationship in order to obtain consistent critical radiotoxicity values (i.e., EDR10) that are comparable for a proper use of statistical meta-analysis. The first quality-control of the data used was established by the FASSET and ERICA consortia (see Copplestone et al., 2008), which additionally published the multi-step data treatment process and associated criteria for data selection (Garnier-Laplace et al., 2006, 2010, for ERICA and PROTECT respectively). One may consider “this is in no way sufficient" as judged by J. Smith, but FREDERICA is today considered as the reference database gathering validated inputs by a suite of consortia (FASSET, ERICA, PROTECT and more recently EMRAS-II).
In Garnier-Laplace et al. (2008), the multiple criteria adopted to select data resulted in a “CEZ chronic effets data set" quite small but documented enough for assisting the comparison of radiosensitivity variation among species and endpoints in the laboratory and in the field. For example, excluding data because they may reflect the initial high dose rates shortly after the accident as concluded by Jackson et al. (2005) could apply to all data from chronically exposed species or assemblage of species present in the CEZ. We alerted in our paper that “the major limitation of the method relies on the impossibility to incorporate knowledge when the experiments failed to evidence any significant effect". However it is underlined that this is also a strength to have the same robustness with EDR10, which is not the case with NOEDR strongly dependent upon design and dose rate spacing. It is also said that “eventually, although it was impossible to incorporate this knowledge quantitatively into our meta-analysis, the implications of such results are discussed in this paper and used to modulate our conclusion" (Garnier-Laplace et al., 2008).
One key reasoning to accept or reject data from Moller and Mousseau studies was the consistency of the outcome from the dose reconstruction and the state of the art in terms of dose-effect relationship (i.e.
dose reconstruction giving dose rate estimates close or below the natural background leads to data rejection, this was only the case of invertebrates data from Moller and Mousseau (2009) logically excluded from our comparison as outliers).
Finally, for all the other EDR10 estimates, this was the internal consistency of the data set as a whole that led however Garnier-Laplace et al. (2008) to include them in their study. Such a consistency seems in fact
significant considering that the data issued from different authors on different organisms under different exposure conditions. In addition to scientific considérations discussed in their paper, this empirical considération added to the conviction of Garnier-Laplace et al. (2008) that the Moller and Mousseau study on invertebrates has to be rejected.
J. Smith noted as a huge contradiction the apparition of effects at population level at lower dose rates than for individuals. He based this comment on two studies from Moller and Mousseau, one of them being rejected by Garnier-Laplace et al. (2008). The second one, related to birds, referred to dose rates from 1 to 100 gGy h-1 which are in agreement with the elements presented above concerning the occurrence of effects in birds exposed to ionizing radiation. There is no contradiction. Additionally, it is acknowledged that it is difficult to anticipate population response from individual data. This is the field of investigation for population modelling that, if promising, still lacks very often validation. Answering any point made by J. Smith based on personal communications from some researchers and on his personal belief seems to us out of scope for our answer restricted to scientific justifications. We just want to insist on the fact that the majority of Moller and Mousseau's ecological data sets are unique and, as demonstrated by our re-analysis of data describing the birds communities in Fukushima, dose reconstruction may reconcile the findings with the knowledge on radiobiology of non-human species (Garnier-Laplace et al., 2015; Beaugelin-Seiller et al., 2018).
About “Laboratory studies are likely to be more sensitive than field studies"
We share this point of view that has been largely discussed in our present paper if “sensitive" means more powerful to evidence causality between exposure levels and observed effects. Field and laboratory studies have always been seen as complementary approach.
About “Problem with the methodological approach"
The points made by J. Smith have all been mentioned and discussed in the Garnier-Laplace et al. studies (2006, 2008, 2010, 2013, 2015). The limitations of the results are well known and we do not think constructive to epilog about it here. We just would like to add some precisions regarding the non-use of no effect values; even it was also already largely discussed in Garnier-Laplace et al. (2008). This is a well-known issue in the derivation of benchmarks in ecotoxicology. The use of the NOEC concept (and even LOEC) in this aim was widely criticized and has had many objections during the last four decades (Kooijman, 1981;
Kooijman, 1996; Chapman et al., 1996; Murrell et al., 1998; Pires et al., 2002; Warne and Van Dam, 2008; Fox et al., 2012; Murado and Prieto, 2013). Ignoring NOEDR in SSDs aiming finally to derive benchmarks appears consistent with the current practice in the field of ecotoxicology, as illustrated for example by the outcomes of an OECD sponsored Workshop to review and compare data analysis options for ecotoxicity testing, including the NOEC and ECx (OECD, 1998). A consensus was reached for the need of an NOEC replacement by an ECx measurement, to be progressively included in OECD test guidelines. Some years later US EPA recommended also a similar shift, with the use of BMC (Benchmark concentration corresponding to the Effect Concentration ECx) instead NOEC (Reed et al., 2004). The issue of dose-response curves has been extensively explained in Garnier-Laplace et al. (2010), describing the process to select the best fitted relationship among four parameters log-logistic models or hormetic models (Brain-Cousens or Cedergreen-Ritz-Streibig). The dose-response curves built from selected chronic effects data sets acquired in the CEZ have been represented for the EDR10 commented by J. Smith in a new figure (Fig. 1) where any reader will be able to judge visually the data sets and model fit quality. This answers and dismisses J. Smith's criticism on the subject.
Fig. 1 Dose-response relationships used to support the détermination of the EDR10 commented by J. Smith, localized on the sensitivity distribution of species observed in the Chernobyl Exclusion Zone.
alt-text: Fig. 1
1 Conclusions
For different reasons (ethic, time elapsed, funding ...), former ecological data sets cannot be revised or completed. They are precious as irreplaceable. We must make the most of this knowledge that captures a more or less biased picture of the real world, trying not to over interpret them. This is more the ignorance of ecological data from contaminated fields whatever they are that could make psychologically ""Real damage to people's health and wellbeing". Sharing data among scientists is the only way to cross-validate (or not) interpretation from observational science such as eco-epidemiology. Dose reconstruction, and statistics are potentially powerful tools, but their use supposes inevitably assumptions leading to uncertainties in the results. It is only by working transparently on these data that we can really identify their limits and the errors potentially made in their acquisition, manipulation and interpretation. Lessons learned from this type of meta-analyses would allow avoiding to reproduce the same mistakes in the future, and thus continue to progress in the understanding of actual effects of exposure of wildlife to ionizing radiation.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/jjenvrad.2019.02.016.
References
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Appendix A. Supplementary data
The following is the Supplementary data to this article:
Multimedia Component 1 Data Profile
alt-text: Data Profile
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