Concerns about Reproducibility, Use of the Akaike Information Criterion, and Related Issues in Hoondert et al. 2019

Our exploratory study on the quantitative structure-activity relationship (QSAR)-based species sensitivity distributions (SSDs)-which boils down to directly deriving SSDs for untested compounds from those of tested compounds (Hoondert et al. 2019)-has been appreciated by Iwasaki and Hayashi (2020). However, they also voice concerns about the statistics used in the study, particularly concerning the improper use of statistical methods and parameters in selecting appropriate models and the reproducibility of outcomes. Herewith we provide our reply to the comments, hoping to clarify our methods and reemphasize the higher aim of the study, which is to help forward this field to maturity.

show abstract

Reply to “Concerns About Reproducibility, Use of the Akaike Information Criterion, and Related Issues in Hoondert et al. 2019” and Focus in Developing QSAR‐Based Species Sensitivity Distributions

Hoondert

Oldenkamp

Zwart³

et al. 2020

Enviro Toxic and Chemistry

View full text Add to dashboard Cite

show abstract

Estimating species sensitivity distributions on the basis of readily obtainable descriptors and toxicity data for three species of algae, crustaceans, and fish

Iwasaki

Sorgog

2021

PeerJ

View full text Add to dashboard Cite

Estimation of species sensitivity distributions (SSDs) is a crucial approach to predicting ecological risks and water quality benchmarks, but the amount of data required to implement this approach is a serious constraint on the application of SSDs to chemicals for which there are few or no toxicity data. The development of statistical models to directly estimate the mean and standard deviation (SD) of the logarithms of log-normally distributed SSDs has recently been proposed to overcome this problem. To predict these two parameters, we developed multiple linear regression models that included, in addition to readily obtainable descriptors, the mean and SD of the logarithms of the concentrations that are acutely toxic to one algal, one crustacean, and one fish species, as predictors. We hypothesized that use of the three species’ mean and SD would improve the accuracy of the predicted means and SDs of the logarithms of the SSDs. We derived SSDs for 60 chemicals based on quality-assured acute toxicity data. Forty-five of the chemicals were used for model fitting, and 15 for external validation. Our results supported previous findings that models developed on the basis of only descriptors such as log KOW had limited ability to predict the mean and SD of SSD (e.g., r2 = 0.62 and 0.49, respectively). Inclusion of the three species’ mean and SD, in addition to the descriptors, in the models markedly improved the predictions of the means and SDs of SSDs (e.g., r2 = 0.96 and 0.75, respectively). We conclude that use of the three species’ mean and SD is promising for more accurately estimating an SSD and thus the hazardous concentration for 5% of species in cases where limited ecotoxicity data are available.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Concerns about Reproducibility, Use of the Akaike Information Criterion, and Related Issues in Hoondert et al. 2019

Cited by 2 publications

References 3 publications

Reply to “Concerns About Reproducibility, Use of the Akaike Information Criterion, and Related Issues in Hoondert et al. 2019” and Focus in Developing QSAR‐Based Species Sensitivity Distributions

Reply to “Concerns About Reproducibility, Use of the Akaike Information Criterion, and Related Issues in Hoondert et al. 2019” and Focus in Developing QSAR‐Based Species Sensitivity Distributions

Estimating species sensitivity distributions on the basis of readily obtainable descriptors and toxicity data for three species of algae, crustaceans, and fish

Contact Info

Product

Resources

About