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Black Sea Planktonic Organisms as Bioindicators for Biological Early Warning Systems: A Systematic Review
Summary
A systematic review of 140 publications evaluated nine Black Sea planktonic species as biosensors for real-time water quality monitoring, identifying jellyfish Aurelia aurita, copepod Acartia tonsa, and ctenophore Mnemiopsis leidyi as top candidates sensitive to metals, surfactants, and microplastics. This matters for microplastic pollution research because automated biological early warning systems could enable continuous, low-cost detection of microplastic contamination in marine ecosystems.
This is the first systematic review evaluating Black Sea plankton as biosensor organisms for Biological Early Warning Systems (BEWS) – real-time monitoring approaches that de-tect sublethal behavioural or physiological responses to pollutants before irreversible eco-system damage occurs. The systematic literature review was guided by the PRISMA (Pre-ferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, ensuring methodological transparency and applicability. A total of 140 publications from data-bases (Web of Science Core Collection, Scopus, PubMed, and Google Scholar databases) were included in the final analysis. We assess nine native planktonic taxa as candidates for automated video-based water quality monitoring, using a multi-criteria framework encompassing biological sensitivity, technical detectability, and practical feasibility. Three species emerge as the most suitable candidates: Aurelia aurita as a universal indicator (sensitive to copper, surfactants, petroleum, microplastics; large size enables standard video detection); Acartia tonsa for trace contamination (reproductive toxicity at metal con-centrations 4–33× below regulatory standards); and Mnemiopsis leidyi for metal-specific discrimination (bioluminescent responses: 650% Zn, 430% Cu, 350% Hg at 0.001 mg/L). Analysis of 140 publications reveals critical gaps: 33% of species lack toxicological data, 95% of studies test single toxicants despite natural mixture exposure, and microplastic methodology varies 1000-fold in particle size. Threshold analysis suggests planktonic sublethal stress at "safe" concentrations under current standards, suggesting inadequate protection of marine food webs. A complementary monitoring approach integrating these species with computer vision algorithms offers autonomous early-warning capability for Black Sea environmental management.