The objective of the report is to provide a science-based reference to support any future design and implementation of co-existence measures within the EU. The case studies covered crop and seed production of maize, sugar-beet and cotton. The report also examined the feasibility of producing conventional seeds in Europe under different thresholds for the presence of GM seeds.
On the basis of the model simulations and expert opinions gathered in this report, for the case studies covered (maize, sugar-beet, cotton), co-existence in seed production is technically feasible for a threshold of 0.5 percent, with few or no changes in current practices. For maize, this holds true for co-existence between non-GM and GM seed production. However, co-existence of non-GM maize seed production with GM maize crops would need changes in current practices, namely introduction of larger isolation distances (from the current 100 to 200 metres distances to 400 to 600 metres).
If GM presence in seeds does not exceed 0.5 percent, co-existence in crop production is technically feasible for the target threshold of 0.9 percent. For maize, additional measures are needed for some specific situations defined by climatic, landscape and agronomic parameters. The report evaluates measures found to be technically simple and effective. These measures, targeting GM maize growers, have variable farm-level economic consequences that will affect the farmer's decision whether or not to grow GM maize varieties.
The report illustrates the power of novel gene flow models that actually take into account the spatial patterns of landscapes and agricultural practices. It is now possible to estimate levels of adventitious GM presence in non-GM production resulting from multiple fields and sources, over extended time periods, propose numerous co-existence measures and quickly test their feasibility and consequences at regional level. The information obtained from model simulations, such as the decision tables presented in this report, is valuable for helping decision-makers set up co-existence strategies. Models simulations are not a substitute for field experiments, but a way of overcoming the limitations (time scale, spatial coverage, costs) inherent to field work.