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Updated: Jul 4, 2026

Ecotoxicological Methodologies to Evaluate Biomarkers at Different Scales in Neotropical Anurans
Published on: April 28, 2023
In search of the smoking gun: Linking results of effect-based assessment to anthropogenic stressors
Delia Hof1, Thomas Bing2, Gustav Glock Brown1
1Goethe University Frankfurt, Faculty of Biological Sciences, Department of Aquatic Ecotoxicology, Max‑von‑Laue‑Str. 13, 60438, Frankfurt am Main, Germany.
Abstract:
The quality of surface waters is affected by a variety of anthropogenic stressors, of which chemical pollution is one of the most important. In addition to conventional chemical analytical methods, effect-based methods offer the potential to identify contaminations of even complex samples. But for an effective water management, those effects must be clearly interpretable and ideally traceable to potential sources of pollution. Therefore, this study was designed to verify the sensitivity of selected effect-based methods and to provide a better explanation of the measured effects. We assessed water and sediment samples from 30 different sites. We tested in vitro for baseline toxicity, oxidative stress responses, aryl hydrocarbon receptor activity, endocrine and mutagenic effects and in vivo for lethal, sub-lethal and phytotoxic endpoints. First, we evaluated the sensitivity and applicability of different effect-based methods. In vitro assays generally detected significant effects more frequently than in vivo assays, which is at least partly attributable to SPE enrichment of the samples. The results were then associated with chemical analytical data, land use and wastewater treatment plant influence using correlation, simple and multiple regression models. Simple correlations could only explain part of the ecotoxicological effects from chemical data, as effect-based methods appear to cover a wider range of pollutants. Individual land use types were less suitable, the influence of treated wastewater effluents and increased erosion potential contributed most to the explained variance of the measured data of all selected variables. Based on these results, recommendations for future effect-based monitoring were formulated.
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