Cross-species extrapolation of chemical sensitivity

作者：Sanne van den Berg, Lorraine Maltby, Tom Sinclair, Ruoyu Liang, Paul J. Van den Brink · 发表于：The Science of The Total Environment · 年份：2020 · DOI：10.1016/j.scitotenv.2020.141800 · 被引用次数：52 · 研究领域：Species Distribution and Climate Change、Environmental Toxicology and Ecotoxicology、Animal testing and alternatives

Ecosystems are usually populated by many species. Each of these species carries the potential to show a different sensitivity towards all of the numerous chemical compounds that can be present in their environment. Since experimentally testing all possible species-chemical combinations is impossible, the ecological risk assessment of chemicals largely depends on cross-species extrapolation approaches. This review overviews currently existing cross-species extrapolation methodologies, and discusses i) how species sensitivity could be described, ii) which predictors might be useful for explaining differences in species sensitivity, and iii) which statistical considerations are important. We argue that risk assessment can benefit most from modelling approaches when sensitivity is described based on ecologically relevant and robust effects. Additionally, specific attention should be paid to heterogeneity of the training data (e.g. exposure duration, pH, temperature), since this strongly influences the reliability of the resulting models. Regarding which predictors are useful for explaining differences in species sensitivity, we review interspecies-correlation, relatedness-based, traits-based, and genomic-based extrapolation methods, describing the amount of mechanistic information the predictors contain, the amount of input data the models require, and the extent to which the different methods provide protection for ecological entities. We develop a conceptual framework, incorpor...