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

TL;DR

This paper introduces a hierarchical Bayesian model for species sensitivity distributions that incorporates uncertainty and variability, providing a comprehensive assessment of community responses to contaminants, demonstrated on herbicide effects on diatoms.

Contribution

It develops a novel hierarchical Bayesian framework for SSD that accounts for all sources of uncertainty and enables assessment of global community responses.

Findings

The model successfully integrates concentration-response data with SSD distribution laws.

Application to herbicides on diatoms revealed detailed community sensitivity insights.

The approach quantifies uncertainty in ecological risk assessments.

Abstract

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.