Regionalización de los elementos de la flora en los límites de los campos sensibles a la hibridación con la colza genéticamente modificada

Background, aim, and scope Gene flow via pollen dispersal to neighbouring non-genetically modified (GM) and organic fields or to biotopes containing the same crop species and/or their wild relatives are among the most debated potential environmental risks of GM crops. These crosses permit ingression of GM traits and may produce viable progeny. Current GM crop monitoring plans and concepts have not considered this a critical issue. In the present study, we develop a methodology for the regionalisation of the hybridisation risk of GM oilseed rape (OSR) (Brassica napus L.) with respect to related hybridisation partners (both OSR and related species) as well as neighbouring arable fields and biotopes. This methodology should constitute an important component of future spatial GM crop monitoring designs.Materials and methods A vegetation database containing occurrence frequencies of OSR crossing partners in Brandenburg state was analysed, and literature surveys were performed on OSR outcrossing proofs with regard to different wild species, the viability of progeny and the potential establishment of crosses. We aggregated detailed biotope maps for the entire Brandenburg state in order to differentiate the nine main biotope groups relevant as habitats for OSR and hybridising Brassicaceae. We determined the types and areas of biotopes neighbouring all arable fields with an outside buffer of 50 m, and then ascertained whether the biotope composition outside the buffers was significantly different from that of the buffers. We then overlayed our buffering results with an ecoregion map of Brandenburg to upscale our results to larger regions.Results Brassica rapa presented the highest potential for hybridisation, reproduction and persistence in this environment, but Raphanus raphanistrum, Brassica oleracea, Hirschfeldia incana, Sinapis arvensis and Diplotaxis muralis are also significant potential crossing partners for OSR. The highest average frequency of species occurring in biotopes applies to arable lands, settlements and industrial areas, disturbed areas, road verges and gardens, which together cover 84.2 % of the total area and 74.6 % of the neighbouring biotopes. Related species occurring most often in Brandenburg are Descurainia sophia, feral OSR, Sinapis arvensis, Diplotaxis tenuifolia and Diplotaxis muralis. All biotopes relevant to OSR-related species are present in all Brandenburg ecoregions, but there are differences in the proportion of each biotope, especially hedgerows, arable land, gardens and road verges. The Uckermark and Oder valley can be considered slightly more critical.Discussion Hybridisation and persistence of GM OSR depends on (a) the related species’ potential to hybridise and produce viable progeny, (b) the frequency of hybridisation partners at different biotope types, and (c) the frequency of directly neighbouring arable fields with sensitive biotopes. Integration of these factors gives the following rank order of hybridisation risks for different biotopes in the agro-environment: disturbed areas > arable land > road verges > settlements and industrial areas > gardens. Extrapolation of local relevée and biotope results to larger areas such as the Brandenburg state was shown to be feasible, and may also be done nationwide and EU-wide with suitable biotope datasets.Conclusions Cultivation of GM OSR in Brandenburg carries a considerable potential of hybridisation with related species and feral OSR in biotopes neighbouring arable fields. The methodology presented here is suitable to link spatially limited but highly detailed datasets on the occurrence of potential hybridisation partners for GM OSR with regional datasets and to extrapolate hybridisation risks, and therefore could serve as a monitoring instrument.Recommendations and perspectives We suggest that populations of related species and the potential spread of GM traits should be monitored using a targeted approach. While further standardisation will be required, this methodology should be included as a regular component of GM crop monitoring.