BIODIVERSITY SECTOR ECOLOGICAL IMPLICATIONS OF GMOS Robust methodologies for ecological risk assessment Best practice and current practice in ecological risk assessment for Genetically Modified Organisms

i Executive summary This report compares current practice in ecological risk assessment for genetically modified (GM) plants and microorganisms, as evidenced by eight transnational and national frameworks, with what might reasonably be considered best practice. Best practice is defined for the scientific principles, hazard identification, risk calculation, social appraisal and monitoring stages of an ideal ecological risk assessment, and summarised in the following ten points: 1. Carefully define measurement and assessment endpoints for environmental values for each stage of a genetically modified organism (GMO) release; 2. Construct good qualitative models of all hazard scenarios using structured deductive and inductive hazard assessment techniques; 3. Consider the influence of cognitive bias, framing effects, anchoring and sample size on qualitative decisions; 4. Consider the full spectrum of ecological models from simple (screening) to detailed ecosystem models; 5. Recognise that even simple models can incorporate uncertainty and be useful in ecological risk assessment; 6. It is essential to include a transparent analysis of uncertainty; 7. When information is sparse use probability bounding analysis to express uncertainty; 8. Examine opportunities to promote appropriate and ongoing stake-holder participation in the risk assessment; 9. Adopt a precautionary approach to high consequence, but highly uncertain, hazards; and, 10. Consider statistical power, effect size and model based sensitivity analysis and other remedies to hidden conventional pitfalls in monitoring. Most of the frameworks reviewed here provide evidence of best practice in the scientific principles and frameworks of ecological risk assessment. All of them, however, rely on simple checklists in the hazard identification stage, and only one discusses inductive techniques. Hazard identification as currently practiced is therefore largely restricted to prescriptive deductive techniques. Analysts will identify a larger range of potential hazards, and gain a better understanding of the event chains associated with these hazards, if they used inductive hazard identifications techniques. Well-corroborated quantitative techniques exist for some of the potential hazards associated with GMO field release. However, despite the rich scientific literature on quantitative techniques and models, only one framework bridges the divide between science and regulation by identifying specific experimental techniques and models in the regulatory process. Some of the regulatory frameworks recognise that quantitative approaches are possible in certain circumstances, but neither the circumstances (i.e. which hazards) nor available techniques are identified. For the main part it is not clear when and how quantitative techniques are expected of the applicant. ii Regulators can assist quantitative risk assessment by …