Mixed phylogenetic signal in fish toxicity data across chemical classes

Andrew Hylton, Ylenia Chiari, Isabella Capellini, Mace G. Barron, Scott Glaberman*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Chemical use in society is growing rapidly and is one of the five major pressures on biodiversity worldwide. Since empirical toxicity studies of pollutants generally focus on a handful of model organisms, reliable approaches are needed to assess sensitivity to chemicals across the wide variety of species in the environment. Phylogenetic comparative methods (PCM) offer a promising approach for toxicity extrapolation incorporating known evolutionary relationships among species. If phylogenetic signal in toxicity data is high, i.e., closely related species are more similarly sensitive as compared to distantly related species, PCM could ultimately help predict species sensitivity when toxicity data are lacking. Here, we present the largest ever test of phylogenetic signal in toxicity data by combining phylogenetic data from fish with acute mortality data for 42 chemicals spanning 10 different chemical classes. Phylogenetic signal is high for some chemicals, particularly organophosphate pesticides, but not necessarily for many chemicals in other classes (e.g., metals, organochlorines). These results demonstrate that PCM may be useful for toxicity extrapolation in untested species for those chemicals with clear phylogenetic signal. This study provides a framework for using PCM to understand the patterns and causes of variation in species sensitivity to pollutants.

Original languageEnglish
Pages (from-to)605-611
Number of pages7
JournalEcological Applications
Issue number3
Publication statusPublished - 20 Apr 2018
Externally publishedYes


  • ecological risk assessment
  • ecotoxicology
  • evolutionary toxicology
  • fish
  • organochlorine
  • organophosphate
  • phylogenetic comparative methods
  • phylogeny

ASJC Scopus subject areas

  • Ecology


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