  The Species Sensitivity Distribution (SSD) is a key tool to assess the
ecotoxicological threat of contaminant to biodiversity. It predicts safe
concentrations for a contaminant in a community. Widely used, this approach
suffers from several drawbacks: i)summarizing the sensitivity of each species
by a single value entails a loss of valuable information about the other
parameters characterizing the concentration-effect curves; ii)it does not
propagate the uncertainty on the critical effect concentration into the SSD;
iii)the hazardous concentration estimated with SSD only indicates the threat to
biodiversity, without any insight about a global response of the community
related to the measured endpoint. We revisited the current SSD approach to
account for all the sources of variability and uncertainty into the prediction
and to assess a global response for the community. For this purpose, we built a
global hierarchical model including the concentration-response model together
with the distribution law for the SSD. Working within a Bayesian framework, we
were able to compute an SSD taking into account all the uncertainty from the
original raw data. From model simulations, it is also possible to extract a
quantitative indicator of a global response of the community to the
contaminant. We applied this methodology to study the toxicity of 6 herbicides
to benthic diatoms from Lake Geneva, measured from biomass reduction.
