Under CopyrightHommen, U.U.Hommen2022-03-0907.01.20042003https://publica.fraunhofer.de/handle/publica/34373210.24406/publica-fhg-343732Why population level risk assessment? - We want to protect (local) populations in the field, effects on individuals can often be accepted. Why modelling? - Lower tier studies usually focus on individual level endpoints; - the most sensitive life history trait must not be the most important one for the population; - direct measurement of effects on populations can rarely be done at lower tiers, and even in higher tiers not for all taxa; - Higher tier studies can usually be conducted only for one or a few scenarios (e.g. application pattern, environmental conditions...). Summary: Added value of population modelling - Additional line of evidence for conclusions based on lab or field experiments or monitoring studies (Extrapolation from effects on life cycle traits on population growth rate; Application of model ecosystem data to other environmental conditions; Prediction of response over longer time periods); - Identify data gaps (e. g. data for important life stages); - Screening tool (e.g. identify critical species based on their ecology).Introduction Endpoints in population level risk assessment Logistic growth Dealing with parameter uncertainty Individual based models Daphnia: Simulating demographic stochasticity Example 1: HARAP insecticide case study Spatial explicit models: ALMaSS "Mapping" of model examples Selection of the type of modelen570610620660presentation