Assessment of a New Approach Method for Grouped Chemical Hazard Estimation: The Toxicity-Normalized Species Sensitivity Distribution (SSDn)

Abstract

New approach methods are being developed to address the challenges of reducing animal testing and assessing risks to the diversity of species in aquatic environments for the multitude of chemicals with minimal toxicity data. The toxicity-normalized species sensitivity distribution (SSDn) approach is a novel method for developing compound-specific hazard concentrations using data for toxicologically similar chemicals. This approach first develops an SSDn composed of acute toxicity values for multiple related chemicals that have been normalized by the sensitivity of a common species tested with each compound. A toxicity-normalized hazard concentration (HC5n) is then computed from the fifth percentile of the SSDn. Chemical-specific HC5 values are determined by back-calculating the HC5n using the chemical-specific sensitivity of the normalization species. A comparison of the SSDn approach with the single-chemical SSD method was conducted by using data for nine transition metals to generate and compare HC5 values between the two methods. We identified several guiding principles for this method that, when applied, resulted in accurate HC5 values based on comparisons with results from single-metal SSDs. The SSDn approach shows promise for developing statistically robust hazard concentrations when adequate taxonomic representation is not available for a single chemical.

Advancing Fifth Percentile Hazard Concentration Estimation Using Toxicity-Normalized Species Sensitivity Distributions

“…Chemical-specific HC5s are then back-calculated from the SSDn-estimated HC5 and the chemical-specific toxicity value of the normalizing species. In the current study, the SSDn approach of Giddings et al 8 and Lambert et al 1 was modified to include all possible normalizing species to allow for more accurate HC5 estimation with quantifiable low uncertainty. This improved SSDn approach was assessed using a case study of acute toxicity values for organophosphate and carbamate insecticides with high diversity in species composition and order of magnitude ranges in toxicity values.…”

“…For example, the nSMAV for the nSpecies will always equal 1, and the nSMAV for a species 4 times less sensitive than the nSpecies would be 4. (3) We geometrically averaged the nSMAV for each species across all chemicals within the combination to generate a single nSMAV to represent that species in the SSDn . (4) Using the same procedure as single-chemical SSD generation, we fitted the nSMAVs to four different distributions (log–normal, log–logistic, gamma, and Weibull) using the “fitdistrplus” package in R .…”

“…Following general SSD development practice as described in Posthuma et al 13 and Stephan et al, 5 we first calculated the geometric mean of toxicity values for each species within the group. Using the best-fit method described in Lambert et al, 1 we then fitted toxicity values to four statistical distributions (log−normal, log−logistic, gamma, and Weibull) using the "fitdistrplus" package in R. 14 Though other distribution-fitting methods exist, we opted to fit these symmetrical two-parameter distributions for their simplicity and to compare our results directly to those of Lambert et al 1 We determined the best-fit distribution using the lowest Anderson−Darling statistic and extracted the HC5 value from the fifth percentile of the best-fit distribution. We then extracted the upper and lower confidence limits of the best-fit distribution at the fifth percentile.…”

“…Chemical-specific HC5s are then back-calculated from the SSDn-estimated HC5 and the chemical-specific toxicity value of the nSpecies. Lambert et al 1 extended the SSDn method using a case study of heavy metals and provided guidelines for computing HC5 estimates for chemicals that lack adequate taxonomic representation in conventional single-chemical SSDs. Despite advantages of leveraging toxicity data across a group of chemicals to increase taxonomic diversity and species number, a key limitation of the SSDn approach has been the requirement of a single nSpecies tested in all compounds within the chemical group.…”

“…Despite advantages of leveraging toxicity data across a group of chemicals to increase taxonomic diversity and species number, a key limitation of the SSDn approach has been the requirement of a single nSpecies tested in all compounds within the chemical group. 1,8 To address this limitation in developing a pyrethroid insecticide SSDn, Giddings et al 8 conducted supplemental toxicity tests on the nSpecies (Hyalella azteca) so that all chemicals in the group shared a common test species.…”