Organisationseinheit: Deutschland, Umweltbundesamt, Fachgebiet IV.2.5 - Spurenanalytik , Fließ- und Stillgewässersimulation
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Berlin
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EthoCRED: a framework to guide reporting and evaluation of the relevance and reliability of behavioural ecotoxicity studies
(2024) Bertram, Michael G.; Ågerstrand, Marlene; Thoré, Eli S.J.; Allen, Joel; Balshine, Sigal; Brand, Jack A.; Brooks, Bryan W.; Dang, ZhiChao; Duquesne, Sabine; Ford, Alex; Jacob, Stefanie; Maack, Gerd; Mohr, Silvia; Sahm, René
Behavioural analysis has been attracting significant attention as a broad indicator of sub-lethal toxicity and has secured a place as an important subdiscipline in ecotoxicology. Among the most notable characteristics of behavioural research, compared to other established approaches in sub-lethal ecotoxicology (e.g. reproductive and developmental bioassays), are the wide range of study designs being used and the diversity of endpoints considered. At the same time, environmental hazard and risk assessment, which underpins regulatory decisions to protect the environment from potentially harmful chemicals, often recommends that ecotoxicological data be produced following accepted and validated test guidelines. These guidelines typically do not address behavioural changes, meaning that these, often sensitive, effects are not represented in hazard and risk assessments. Here, we propose a new tool, the EthoCRED evaluation method, for assessing the relevance and reliability of behavioural ecotoxicity data, which considers the unique requirements and challenges encountered in this field. This method and accompanying reporting recommendations are designed to serve as an extension of the “Criteria for Reporting and Evaluating Ecotoxicity Data (CRED)” project. As such, EthoCRED can both accommodate the wide array of experimental design approaches seen in behavioural ecotoxicology, and could be readily implemented into regulatory frameworks as deemed appropriate by policy makers of different jurisdictions to allow better integration of knowledge gained from behavioural testing into environmental protection. Furthermore, through our reporting recommendations, we aim to improve the reporting of behavioural studies in the peer-reviewed literature, and thereby increase their usefulness to inform chemical regulation.
Manual curation of aquatic fungal ITS2 metabarcoding OTU matrices increases community identification on the genus and species level
(2026) Baschien, Christiane; Carl, Steffen C.
We conducted six metabarcoding studies from different aquatic habitats. It has been confirmed that fungal metabarcoding has the advantages of overcoming the cultivation bias, increasing the number of possible samples by high-throughput sequencing, and enabling the detection of yet uncultivated fungal taxa. However, the already well-known limitations, in particular the lack of taxonomic accuracy when using automated classification also occurred.
During the manual curation of pipeline-retrieved datasets, the quality of the automatic classification, specifically phylogenetic rank and current nomenclature, was verified. The manual curation step revealed that only 10–20% of the Operational Taxonomic Units (OTUs) were identified correctly by the automatic classification. Re-blasting of the remaining OTUs resulted in taxonomic and nomenclatural correction of a further 30–40% of OTUs. Approximately 50% of the OTUs resulted in insufficient identifications, which can be attributed to shortcomings in the database, including yet unidentified species, missing reference sequences, and the disadvantages of the genetic marker used.
Pipeline parameters that can be adjusted to improve the classification of taxa in metabarcoding studies include adjusting the cut-off threshold for sequence similarity, updating and refining databases, and aligning and collapsing of OTUs to species hypotheses. Here, we describe a method of manual data curation and its impact on improving the taxonomic resolution of a metabarcoding dataset. Shortcomings as well as advantages are discussed to illustrate the need for bioinformatic tools that support the process of data curation. © 2026 The Authors.
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