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The complexity of micro- and nanoplastic research in the genus Daphnia : A systematic review of study variability and a meta-analysis of immobilization rates

Title data

Brehm, Julian ; Ritschar, Sven ; Laforsch, Christian ; Mair, Magdalena:
The complexity of micro- and nanoplastic research in the genus Daphnia : A systematic review of study variability and a meta-analysis of immobilization rates.
In: Journal of Hazardous Materials. Vol. 458 (2023) . - 131839.
ISSN 0304-3894
DOI: https://doi.org/10.1016/j.jhazmat.2023.131839

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
SFB 1357 Mikroplastik
391977956

Project financing: Deutsche Forschungsgemeinschaft

Related research data

https://doi.org/10.5281/zenodo.7928191

Abstract in another language

In recent years, the number of publications on nano- and microplastic particles (NMPs) effects on freshwater organisms has increased rapidly. Freshwater crustaceans of the genus Daphnia are widely used in ecotoxicological research as model organisms for assessing the impact of NMPs. However, the diversity of experimental designs in these studies makes conclusions about the general impact of NMPs on Daphnia challenging. To approach this, we systematically reviewed the literature on NMP effects on Daphnia and summarized the diversity of test organisms, experimental conditions, NMP properties and measured endpoints to identify gaps in our knowledge of NMP effects on Daphnia. We use a meta-analysis on mortality and immobilization rates extracted from the compiled literature to illustrate how NMP properties, study parameters and the biology of Daphnia can impact outcomes in toxicity bioassays. In addition, we investigate the extent to which the available data can be used to predict the toxicity of untested NMPs based on the extracted parameters. Based on our results, we argue that focusing on a more diverse set of NMP properties combined with a more detailed characterization of the particles in future studies will help to fill current research gaps, improve predictive models and allow the identification of NMP properties linked to toxicity.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Physico-chemical properties; Machine learning; Observed effects; Ecotoxicology
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology
Research Institutions > Central research institutes > Bayreuth Center of Ecology and Environmental Research- BayCEER
Research Institutions > Collaborative Research Centers, Research Unit > SFB 1357 - MIKROPLASTIK
Faculties
Research Institutions
Research Institutions > Central research institutes
Research Institutions > Collaborative Research Centers, Research Unit
Result of work at the UBT: Yes
DDC Subjects: 500 Science
500 Science > 570 Life sciences, biology
Date Deposited: 22 Jun 2023 06:20
Last Modified: 22 Nov 2023 14:22
URI: https://eref.uni-bayreuth.de/id/eprint/81378