Estimating acute mortality of Lepidoptera caused by the cultivation of insect-resistant Bt maize – The LepiX model
Introduction
Genetically modified (GM) crops are cultivated worldwide, and most of these crops are resistant to herbicides, insects or both (Parisi et al., 2016). The commercial use and release of GM crops in the environment is regulated and only granted after the risks for human health and the environment have been assessed (EC, 2001).
Insect resistance is most commonly implemented by transferring genes originating from the soil bacterium Bacillus thuringiensis into the crop which will express insecticidal Cry or Vip proteins in the plant tissues (Glare and O'Callaghan, 2000). A number of Bt maize plants target Lepidoptera, such as the European corn borer (Lepidoptera: Crambidae, Ostrinia nubilalis) and the Mediterranean corn borer (Lepidoptera: Noctuidae, Sesamia nonagrioides). However, as Bt proteins do not act species specific (van Frankenhuyzen, 2009, van Frankenhuyzen, 2013), effects of Bt crops on non-target organisms, e.g. non-target butterfly larvae, have to be considered in the risk assessment (Andow and Hilbeck, 2004; Andow and Zwahlen, 2006; Hilbeck et al., 2011; Lang and Otto, 2010; Marvier, 2001; O'Callaghan et al., 2005; Romeis et al., 2008; Wolfenbarger and Phifer, 2000).
In most Bt maize, the Bt proteins are expressed in all plant tissues, including pollen. As maize is wind pollinated and produces large amounts of pollen (Eastham and Sweet, 2002), habitats adjacent to Bt maize cultivation fields will be exposed to pollen containing Bt proteins (Hofmann et al., 2010), and off-field effects have to be considered in the risk assessment. Maize flowering and the larval phenology of many butterfly species overlap; therefore, non-target butterflies in Europe are likely at risk (Lang et al., 2015; Musche et al., 2009; Schmitz et al., 2003; Traxler and Gaugg, 2005). This risk will depend on a variety of factors, such as the degree of temporal overlap in phenologies, amount of pollen to be expected on host plants, toxin concentration in pollen and sensitivity of the non-target species.
Risk assessment prior to GMO authorization requires substantial data and analytical tools. In 2009, the European Food Safety Authority (EFSA) deployed a first mathematical simulation model to predict the consequences of cultivation of Bt maize on non-target Lepidoptera (EFSA, 2009; Perry et al., 2010). This model has been developed further to take new aspects and data for the assessment into account (EFSA, 2011a, EFSA, 2011b, EFSA, 2012, EFSA, 2015). In addition, Holst et al., 2013a, Holst et al., 2013b estimated the mortality of the Peacock butterfly Inachis io caused by Bt maize in a simulation model of the butterfly’s annual life cycle over-laid with the phenology of maize pollen deposition on the leaves of the food plant Urtica dioica. However, the model has not been used in the context of regulatory purposes and did not include spatial aspects, such as the distance of larvae and host plants to the maize field.
Here, we present a new simulation model (LepiX 1.0) to estimate off-field effects of Bt maize cultivation on non-target butterfly species. Our model is designed to simulate the temporal overlap of maize flowering and larval phenology, pollen deposition on host plants depending on the distance to the maize field, and the effect of Bt pollen exposure on the mortality of butterfly larvae. Because we can obtain information on both individual larvae and populations LepiX is especially suited to analyse effects on rare, endangered and/or protected Lepidoptera as these may be protected on the level of the individuum and/or population. The exposure module of our model uses the so far most comprehensive set of field data from research projects dealing with maize pollen deposition, which were initiated by the German Federal Agency for Nature Conservation in collaboration with German federal states to improve the assessment of Bt maize exposure on non-target organisms (Hofmann et al., 2009, Hofmann et al., 2011, Hofmann et al., 2013, Hofmann et al., 2014, Hofmann et al., 2016).
Section snippets
The LepiX model
At first, we specify the purpose of the model (Section 2.1) and give a general overview of its structure (Section 2.2.1) before all submodels are described in detail (Section 2.2.2).
Case example: calibration and settings
The LepiX model can, in principle, be used for any butterfly species, geographical region and Bt maize event. We calibrated the model for Bt maize event MON810, which produces the lepidopteran-active Bt protein Cry1Ab. MON810 maize is the only Bt maize currently approved for cultivation in the EU. The lepidopteran species I. io used in our case example (Bryant et al., 2000, Bryant et al., 2002; Ebert and Rennwald, 1991) is common in agricultural areas of Europe and is protected in some EU
Results
According to the calibration of the model for I. io and the two geographical regions, we performed various simulations to validate the model, estimate rates of mortality and analyse the sensitivity of the model results according to the input parameters.
The output of the individual module simulating the phenology of I. io was in good agreement with field data (Ebert and Rennwald, 1991) for larval and adult phenology in the regions where univoltine (e.g. Bad Hersfeld) or bivoltine (e.g.
General remarks
The LepiX model presented here is an individual-based model designed to estimate the risk of mortality of non-target butterfly larvae caused by exposure to Bt toxins expressed in pollen of insect-resistant Bt maize. LepiX can be easily applied to other Bt maize events (both single and stacked events) and to other species of Lepidoptera. The specific data needed should, in principle, be available from the scientific literature and from market applications of the respective Bt maize. The
Conclusions
We present LepiX as a versatile tool to assist the risk assessment and risk management of Bt maize effects on non-target Lepidoptera. The model balances the need for detailed biological data while offering a high degree of stochasticity to account for the natural variabilities for all three model components: i) pollen deposition and exposure, ii) larval phenology and iii) larval mortality. LepiX allows modelling the effect of larval phenology on the likelihood of exposure to maize pollen and
Acknowledgements
We thank Frieder Hofmann for helpful discussions and Karen A. Brune for language revision. The valuable comments provided by two reviewers are appreciated. This work has been financially supported by funds of the Federal Agency for Nature Conservation (BfN), Germany.
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