JOURNAL ARTICLE

Functional versus compositional tests in the risk assessment of the impacts of pesticides on the soil microbiome.

  • Published In: Environmental Toxicology & Chemistry, 2025, v. 44, n. 4. P. 1120 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Sweeney, Christopher J; Bottoms, Melanie; Kaushik, Rishabh; Aderjan, Eva; Sherborne, Neil 3 of 3

Abstract

This article focuses on comparing functional and compositional testing methods in assessing the impacts of pesticides on the soil microbiome within regulatory risk assessment frameworks. Using dose-response Organisation for Economic Co-operation and Development (OECD) 216 nitrogen transformation tests with two chemicals—nitrapyrin, a nitrification inhibitor, and streptomycin, a broad-spectrum antibiotic—the study derived ecotoxicological endpoints from both traditional functional assays (nitrate formation rates) and amplicon sequencing-based compositional analyses of soil bacterial communities. Results showed that while various compositional endpoints could be generated, their sensitivity varied widely depending on calculation methods and compound mode of action; notably, many compositional metrics failed to detect nitrapyrin effects at ecotoxicologically relevant concentrations, unlike the functional OECD 216 endpoints. The study concludes that amplicon sequencing approaches currently do not consistently outperform or provide greater protection than established functional tests in pesticide risk assessment, highlighting the need for further research across diverse compounds and soils before integrating such methods into regulatory frameworks.

Additional Information

  • Source:Environmental Toxicology & Chemistry. 2025/04, Vol. 44, Issue 4, p1120
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:0730-7268
  • DOI:10.1093/etojnl/vgaf012
  • Accession Number:184192813
  • Copyright Statement:Copyright of Environmental Toxicology & Chemistry is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.