Aligning Behavioural Ecotoxicology with Real-World Water Concentrations: Current Minimum Tested Levels for Pharmaceuticals Far Exceed Environmental Reality

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Abstract

Behavioural ecotoxicology has rapidly emerged as a key area of research, offering sensitive and ecologically meaningful endpoints for detecting sub-lethal effects of contaminants. Much of this work has focused on pharmaceutical pollutants, now widely recognised as contaminants of emerging concern in aquatic systems. Given the field’s rapid growth and the availability of large-scale open-access datasets, we have synthesized across four global databases to evaluate the environmental relevance of tested concentrations—using behavioural ecotoxicology and pharmaceutical pollutants as a case study. We compare exposure data from more than 760 behavioural studies with over 10 million aquatic pharmaceutical occurrence records from global monitoring databases. On average, minimum tested concentrations were 43 times higher than median surface water levels and 10 times higher than median concentrations in treated wastewater. Over half of all tested compounds were never evaluated at concentrations below the highest end of wastewater detections (upper 95% credible interval). Additionally, there was only weak alignment between the pharmaceuticals most frequently tested and those most commonly detected in aquatic environments. These findings reveal a disconnect between experimental design and environmental exposure, potentially limiting the ecological and regulatory relevance of behavioural endpoints in pharmaceutical risk assessment.
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This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint. You must log in to post a comment. There are no comments or no comments have been made public for this article. This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint. Add a Comment You must log in to post a comment. Comments There are no comments or no comments have been made public for this article. Behavioural ecotoxicology has emerged as a key research area, offering sensitive and ecologically meaningful endpoints for detecting contaminant effects. Much of this work has focused on pharmaceutical pollutants, now widely recognised as contaminants of emerging concern. Given the field’s rapid growth and increasing data availability, we synthesised four global databases to evaluate the environmental relevance of tested concentrations—using behavioural ecotoxicology and pharmaceuticals as a case study. We compared data from over 760 behavioural studies with more than 10 million pharmaceutical occurrence data in surface water and wastewater. On average, minimum tested concentrations were 43 times higher than median surface water levels and 10 times median concentrations in wastewater. Roughly half of all compounds were never evaluated at concentrations below the upper end of wastewater detections (95th percentile). We found weak alignment between the pharmaceuticals most frequently tested and those most commonly detected in aquatic environments. These results reveal a mismatch between experimental design and environmental exposure conditions. We recommend incorporating occurrence data into dose selection, prioritising the inclusion of at least one environmentally realistic concentration—ideally near a measure of central tendency. For pharmaceuticals, we provide a consolidated database and an automated tool to support environmentally informed study design. https://doi.org/10.32942/X2F647 Behavior and Ethology, Environmental Health Life Sciences, Life Sciences, Other Pharmacology, Toxicology and Environmental Health, Toxicology evidence synthesis, sub-lethal toxicity, experimental design, contaminants of emerging concern, ecological risk assessment, Environmental monitoring, aquatic toxicology, laboratory field comparison Published: 2025-05-13 07:56 Last Updated: 2025-08-13 08:00 CC BY Attribution 4.0 International Conflict of interest statement: None Data and Code Availability Statement: All R scripts used for data cleaning, filtering, and analysis are available on the corresponding author’s GitHub repository: https://github.com/JakeMartinResearch/field-vs-lab-doses. A rendered HTML version of the full analysis workflow is accessible at: https://jakemartinresearch.github.io/field-vs-lab-doses/. All datasets used in this study are openly available on the Open Science Framework (OSF) under the DOI: 10.17605/OSF.IO/H6CDE. Language: English

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