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The Species Sensitivity Distribution (SSD) is a key tool to assess theecotoxicological threat of contaminant to biodiversity. It predicts safeconcentrations for a contaminant in a community. Widely used, this approachsuffers from several drawbacks: i)summarizing the sensitivity of each speciesby a single value entails a loss of valuable information about the otherparameters characterizing the concentration-effect curves; ii)it does notpropagate the uncertainty on the critical effect concentration into the SSD;iii)the hazardous concentration estimated with SSD only indicates the threat tobiodiversity, without any insight about a global response of the communityrelated to the measured endpoint. We revisited the current SSD approach toaccount for all the sources of variability and uncertainty into the predictionand to assess a global response for the community. For this purpose, we built aglobal hierarchical model including the concentration-response model togetherwith the distribution law for the SSD. Working within a Bayesian framework, wewere able to compute an SSD taking into account all the uncertainty from theoriginal raw data. From model simulations, it is also possible to extract aquantitative indicator of a global response of the community to thecontaminant. We applied this methodology to study the toxicity of 6 herbicidesto benthic diatoms from Lake Geneva, measured from biomass reduction.

Hierarchical modelling of species sensitivity distribution: development and application to the case of diatoms exposed to several herbicides