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Species Sensitivity to Toxic Substances: Evolution, Ecology and Applications
Summary
This review explores why different species vary in their sensitivity to toxic substances, examining the evolutionary and ecological factors that drive these differences. Researchers analyzed how traits like metabolic capacity, body size, and life history influence how organisms respond to chemical exposure. The study provides a framework for improving ecotoxicological predictions by better understanding the biological basis of species sensitivity.
Because it is only possible to test chemicals for effects on a restricted range of species and exposure scenarios, ecotoxicologists are faced with a significant challenge of how to translate the measurements in model species into predictions of impacts for the wider range of species in ecosystems. Because of this challenge, within ecotoxicology there is no more fundamental aspect than to understand the nature of the traits that determine sensitivity. To account for the uncertainties of species extrapolations in risk assessment, “safety factors” or species sensitivity distributions are commonly used. While valuable as pragmatic tools, these approaches have no mechanistic grounding. Here we highlight how mechanistic information that is increasingly available for a range of traits can be used to understand and potentially predict species sensitivity to chemicals. We review current knowledge on how toxicokinetic, toxicodynamic, physiological, and ecological traits contribute to differences in sensitivity. We go on to discuss how this information is being used to make predictions of sensitivity using correlative and trait-based approaches, including comparisons of target receptor orthologs. Finally, we discuss how the emerging knowledge and associated tools can be used to enhance theoretical and applied ecotoxicological research through improvements in mechanistic modeling, predictive ecotoxicology, species sensitivity distribution development, mixture toxicity assessment, chemical design, biotechnology application and mechanistically informed monitoring.
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