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Assessing variability in chemical acute toxicity of unionid mussels: Influence of intra- and inter-laboratory testing, life stage, and species
Citation:
Raimondo, Sandy, C. Lilavois, L. Lee, T. Augspurger, N. Wang, C. Ingersoll, C. Bauer, E. Hammer, AND M. Barron. Assessing variability in chemical acute toxicity of unionid mussels: Influence of intra- and inter-laboratory testing, life stage, and species. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, 35(3):750-758, (2016).
Impact/Purpose:
Identify the sources of variability in toxicity data for freshwater mussels to improve the protection of endangered species within the family Unionidae
Description:
The authors developed a toxicity database for unionid mussels to examine the extent of intra- and interlaboratory variability in acute toxicity tests with mussel larvae (glochidia) and juveniles; the extent of differential sensitivity of the 2 life stages; and the variation in sensitivity among commonly tested mussels (Lampsilis siliquoidea, Utterbackia imbecillis, and Villosa iris), commonly tested cladocerans (Daphnia magna and Ceriodaphnia dubia), and fish (Oncorhynchus mykiss, Pimephales promelas, and Lepomis macrochirus). The results of these analyses indicate that intralaboratory variability for median effect concentrations (EC50) averaged about 2-fold for both life stages, whereas interlaboratory variability averaged 3.6-fold for juvenile mussels and 6.3-fold for glochidia. The EC50s for juveniles and glochidia were within a factor of 2 of each other for 50% of paired records across chemicals, with juveniles more sensitive than glochidia by more than 2-fold for 33% of the comparisons made between life stages. There was a high concurrence of sensitivity of commonly tested L. siliquoidea, U. imbecillis, and V. iris to that of other mussels. However, this concurrence decreased as the taxonomic distance of the commonly tested cladocerans and fish to mussels increased. The compiled mussel database and determination of data variability will advance risk assessments by including more robust species sensitivity distributions, interspecies correlation estimates, and availability of taxon-specific empirically derived application factors for risk assessment.
