Estimation of Chemical Toxicity to Wildlife Species Using Interspecies Correlation Models

Ecological risks to wildlife are typically assessed using
toxicity data for relatively few species and with limited
understanding of differences in species sensitivity to
contaminants. Empirical interspecies correlation models
were derived from LD50 values for 49 wildlife species and
951 chemicals. The standard wildlife test species Japanese
quail (Coturnix japonica) and mallard (Anas platyrhynchos)
were determined to be good surrogates for many species
within the database. Cross-validation of all models
predicted toxicity values within 5-fold and 10-fold of the
actual values with 85 and 95% certainty, respectively. Model
robustness was not consistently improved by developing
correlation models within modes of action (MOA); however,
improved models for neurotoxicants, carbamates, and
direct acting organophosphorous acetylcholenesterase
inhibiting compounds indicate that toxicity estimates may
improve if MOA-specific models are built with robust
datasets. There was a strong relationship between taxonomic
distance and cross-validation prediction success (χ2 =
297, df = 12, p < 0.0001), with uncertainty increasing with
larger taxonomic distance between the surrogate and
predicted species. Interspecies toxicity correlations provide
a tool for estimating contaminant sensitivity with known
levels of uncertainty for a diversity of wildlife species.