Presentation de Christopher John Topping  Aarhus university à un colloque de l'EFSA intitulée : Science, Food, Society 18-21 Septembre 2018

Current guidance in ERA has its focus on toxicology, but it is becoming increasing clear that ecological aspects cannot be ignored. Landscape, its structure and function, have a very important role to play in determining the outcome of the assessment on populations of non-target organisms, as has been acknowledged in recent EFSA scientific opinions. The incorporation of landscape-scale risk assessment is also part of the EFSA strategy for 2020.
Naturally, when dealing with what amounts to a paradigm shift in ERA, there are both opportunities to grasp and challenges to overcome. The opportunities are primarily related to being better able to predict risk, related to the context the animals find themselves in, and to the interactions between stressors and animal populations in space and time. This has the knock-on benefit of being able to use the same tools to evaluate mitigation options. Challenges are both technical and conceptual. The technical challenges related to the need for accurate simulation of landscape structure and function, as well as the development and testing of models and obtaining the volume of data required to support these activities. The conceptual issues relate primarily to definition of specific protection goals at this scale, and decisions on choice of representative species and scenarios.
Several steps towards development of models suitable for supporting landscape-scale ERA have been taken already. EFSA is developing ApisRAM, an individual-based honey bee model that will utilise landscape structure and dynamics to predict impacts of pesticides and other stressors on bees. Other models of mammals, birds and terrestrial arthropods already exist and are being adapted for use.
Currently EFSA is working towards implementation of landscape-scale ERA for pesticides using a systems approach (EFSA Scientific Committee 2016). This endeavour will use those building blocks currently available and adapt them to provide a systems model that includes relevant local (Member State & regional) context. These building blocks include current models of non-target animals and environmental fate models. Landscape simulation will use existing EU datasets e.g. held by JRC, to generate regulatory scenarios, and existing landscape simulation and landscape capture methods provided by the ALMaSS framework (Topping, Dalby et al. 2016). This process has been initiated for a restricted set of species of terrestrial mammals, birds and insects but the aim is to expand to other systems, including aquatic systems in later developmental steps.