%0 Journal Article
%T Population level risk assessment: practical considerations for evaluation of population models from a risk assessor's perspective
%A Magnus Wang
%A Robert Luttik
%J Environmental Sciences Europe
%D 2012
%I BioMed Central
%R 10.1186/2190-4715-24-3
%X During the last decade, several attempts were made to introduce population modelling in pesticide risk assessment by either the academia or the industry [1-6]. The main advantage of using population models in risk assessments is seen in reaching a higher realism and ecological relevance. Most recently, the European Union [EU]-funded project CREAM [7] was initiated, aiming at the application of population models in chemical risk assessment. This project includes a variety of subprojects ranging from aquatic organisms to polar bears. Despite these attempts to use or establish population models in pesticide risk assessment, the acceptance of such models is still limited in Europe. This is due to two main issues: the complexity of the models and a lack of trust in the models or scenarios. Population models are necessarily complex because they must include all aspects which are relevant for the development of populations, i.e. reproduction, survival and further factors. Even if the simulation of each of these factors may be easy to understand (e.g. the simulation of survival, which may be as simple as throwing a dice), the combination of various factors makes the models more complex. However, in reality, it's not the model which is complex, but it's the biology and ecology which are complex, and the model has to reproduce this complexity. Still, due to this complexity, it is extremely important to explain how a model works and what it represents. This does not only imply a detailed technical description of how the model works mechanistically (model type or description of processes in the model) and how it was parameterized, but also covers important assumptions used for the model, a description of what the model actually reflects (representativeness) and an evaluation of the realism of the model (validation) and applied scenarios.While the advantages of using models and how to develop and describe them have been addressed in several previous studies [2,8,9], several aspe
%K population models
%K risk assessment
%K pesticides
%K recovery
%K uncertainty
%U http://www.enveurope.com/content/24/1/3