Do interspecies correlation estimations increase the reliability of toxicity estimates for wildlife?

Abstract

For warm-blooded species, the hazardous dose of a chemical (HD50) is an upcoming and important characteristic in the assessment of toxic chemicals. Generally, experimental information is available for a limited number of warm-blooded species only, which causes statistical uncertainty. Furthermore, when small datasets contain an unrepresentative sample of species, they can cause systematic uncertainty in chemicals' hazardous doses. The number of species can be enlarged with interspecies correlation estimation (ICE) models, but these are uncertain themselves. The goal of this study is to quantify the possible gain in reliability of the HD50 values for warm-blooded wildlife species after enlargement of the sample size with ICE predictions. For 1137 chemicals, we compared systematic uncertainty and statistical uncertainty between HD50 values based on experimental data (HD50Ex) and on datasets combining experimental data and ICE predictions (HD50Co). HD50Ex values ranged between 1.0×10−1 and 9.5×103mgkgwwt−1, and HD50Co values between 1.1×100 and 6.1×103mgkgwwt−1. For over 97 percent of the chemicals, HD50Ex values exceeded HD50Co values, with a systematic uncertainty (i.e. the ratio of HD50Ex/HD50Co) of typically 3.5. The limited availability of experimental toxicity data, predominantly for mammals, resulted in a systematic underestimation of the wildlife toxicity of a chemical. Statistical uncertainty factors (i.e. the ratio of the 95th/5th percentile) quantified the statistical uncertainty in the HD50 values. The statistical uncertainty factors ranged between 1.0×100 and 2.5×1022 for the experimental dataset, and between 4.8×100 and 1.1×102 for the combined dataset. For all sample sizes, median statistical uncertainty factors were the largest for combined datasets. However, combining experimental toxicity data with ICE predictions makes it possible to reduce the upper limit of the range for statistical uncertainty factors. We conclude that, by combining experimental data with ICE model predictions, the validity of the HD50 value can be improved and high statistical uncertainty can be reduced, particularly in cases of limited toxicity data, i.e. data for mammals only or a sample size of n≤4.