Accuracy assessment of time-concentration-effect models in predicting chronic lethality from acute toxicity data.

Acute-to-chronic (ACE) models (accelerated life testing, ALT; linear regression analysis, LRA) are used to estimate chemical concentrations resulting in low levels of chronic mortality from acute toxicity data, thereby greatly increasing the inferential value of acute data. We applied the ACE models to test data from 72 chemicals and 14 aquatic species (131 acute and 97 chronic tests) and then compared the results with reported chronic no observed effect concentrations (NOEC) and lowest observed effect concentrations (LOEC), as determined by traditional analysis of variance techniques. Acute-to-chronic models produced highly accurate chronic lethality estimates compared with reported chronic NOEC and LOEC values. Lethality estimates fell within two times reported NOEC-LOEC values 71% of the time and within five times 98% of the time. Therefore, ACE models are very appropriate for estimating chronic lethality from acute toxicity data when chronic data are absent and have high applicability in probability-based hazard and risk assessments.

Interspecies correlation estimates predict protective environmental concentrations.

Environmental risk assessments often use multiple single species toxicity test results and species sensitivity distributions (SSDs) to derive a predicted no-effect concentration in the environment, typically the 5th percentile of the SSD, termed the HC5. The shape and location of the distribution are best known when populated with numerous toxicity values. To help overcome the cost of multiple toxicity tests, we explored the potential of the U.S. EPA's Interspecies Correlation Estimation (ICE) program to predict single species toxicity values from a single known toxicity value. ICE uses the initial toxicity estimate for one species to produce correlation toxicity values for multiple species, which can be used to develop SSD and HC5. To test this approach to deriving HC5, we generated toxicity values based on measured toxicity values for three surrogate species Pimephales promelas (Fathead minnow), Onchorynchus mykiss (Rainbow trout), and Daphnia magna (water flea). Algal taxa were not used due to the paucity of high quality algal-aquatic invertebrate and algal-fish correlations. The compounds used (dodecyl linear alkylbenzenesulfonate (LAS), nonylphenol, fenvalerate, atrazine, and copper) have multiple measured toxicity values and diverse modes of action and toxicities. Distribution parameters and HC5 values from the measured toxicity values were compared with ICE predicted distributions and HC5 values. While distributional parameters (scale and intercept) differed between measured and predicted distributions, in general, the ICE-based SSDs had HC5 values that were within an order of magnitude of the measured HC5 values. Examination of species placements within the SSDs indicated that the most sensitive species were coldwater species (e.g., salmonids and Gammarus pseudolimnaeus). These results raise the potential of using quantitative structure activity models to estimate HC5s.

Acute toxicity value extrapolation with fish and aquatic invertebrates.

Assessment of risk posed by an environmental contaminant to an aquatic community requires estimation of both its magnitude of occurrence (exposure) and its ability to cause harm (effects). Our ability to estimate effects is often hindered by limited toxicological information. As a result, resource managers and environmental regulators are often faced with the need to extrapolate across taxonomic groups in order to protect the more sensitive members of the aquatic community. The goals of this effort were to 1) compile and organize an extensive body of acute toxicity data, 2) characterize the distribution of toxicant sensitivity across taxa and species, and 3) evaluate the utility of toxicity extrapolation methods based upon sensitivity relations among species and chemicals. Although the analysis encompassed a wide range of toxicants and species, pesticides and freshwater fish and invertebrates were emphasized as a reflection of available data. Although it is obviously desirable to have high-quality acute toxicity values for as many species as possible, the results of this effort allow for better use of available information for predicting the sensitivity of untested species to environmental contaminants. A software program entitled "Ecological Risk Analysis" (ERA) was developed that predicts toxicity values for sensitive members of the aquatic community using species sensitivity distributions. Of several methods evaluated, the ERA program used with minimum data sets comprising acute toxicity values for rainbow trout, bluegill, daphnia, and mysids provided the most satisfactory predictions with the least amount of data. However, if predictions must be made using data for a single species, the most satisfactory results were obtained with extrapolation factors developed for rainbow trout (0.412), bluegill (0.331), or scud (0.041). Although many specific exceptions occur, our results also support the conventional wisdom that invertebrates are generally more sensitive to contaminants than fish are.