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.
Keywords: Ecotoxicology; In silico; Machine learning; Observed effects; Physico-chemical properties.
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