2015/01/21 by Guillaume Kon Kam King, King, Guillaume Kon Kam, Floriane Larras +5
Environmental Science · #Applications (stat.AP) #Environmental Toxicology and Ecotoxicology #FOS: Computer and information sciences #Pesticide and Herbicide Environmental Studies #Pharmaceutical and Antibiotic Environmental Impacts
paper · pdf · doi:10.48550/arxiv.1501.05230
openalex publication_date 2015/01/21 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
The Species Sensitivity Distribution (SSD) is a key tool to assess the\necotoxicological threat of contaminant to biodiversity. It predicts safe\nconcentrations for a contaminant in a community. Widely used, this approach\nsuffers from several drawbacks: i)summarizing the sensitivity of each species\nby a single value entails a loss of valuable information about the other\nparameters characterizing the concentration-effect curves; ii)it does not\npropagate the uncertainty on the critical effect concentration into the SSD;\niii)the hazardous concentration estimated with SSD only indicates the threat to\nbiodiversity, without any insight about a global response of the community\nrelated to the measured endpoint. We revisited the current SSD approach to\naccount for all the sources of variability and uncertainty into the prediction\nand to assess a global response for the community. For this purpose, we built a\nglobal hierarchical model including the concentration-response model together\nwith the distribution law for the SSD. Working within a Bayesian framework, we\nwere able to compute an SSD taking into account all the uncertainty from the\noriginal raw data. From model simulations, it is also possible to extract a\nquantitative indicator of a global response of the community to the\ncontaminant. We applied this methodology to study the toxicity of 6 herbicides\nto benthic diatoms from Lake Geneva, measured from biomass reduction.\n