Ecotracer set up to trace microplastics up the Black Sea marine food web

Natalia Serpetti, Chiara Piroddi, William J. Walters, Elisa Garcia-Gorriz, Svetla Miladinova and Diego Macias

Ecological Modelling, 2025, vol. 509, issue C

Abstract: Around 70 % of all litter in the sea is plastic that, rather than decomposing, breaks down into ever-smaller pieces that can be ingested by marine organisms. However, we lack an understanding of consumption risk by marine species. In this study, particles of microplastic (MP) were traced-up the Black Sea food web, through the calibration process of the Ecotracer module against species-specific MP stomach content observations. These observations, were collected through a literature review: records of MP ingestion for over 60,000 individuals across 780 species within fish and invertebrates were gathered. Statistical analysis, performed on these records, revealed that MP uptake was higher in species inhabiting the Indian Ocean, the Caspian and the China seas. The calibration of the MP model, showed that, at steady state, small benthic and pelagic primary consumers showed the highest concentrations of MP per unit of biomass, led by high direct environmental uptake, and potentially as a consequence of MP bioaccumulation. Secondary consumers, at higher trophic levels, revealed higher MP trophic uptake (biomagnification through diet). Differences in Ecotracer set-up and the calibration procedures were discussed across other recent publications addressing plastic pollution in food-webs. The results were interpreted in relation to species ecological behaviors and physiological characteristics. The approach here, presented with the accessible global database on MP in stomach contents, aims to be a reference for setting up and calibrating MP in food webs.

Keywords: Ecopath with ecosim; Ecotracer; Microplastic; Food-web modeling; Black sea (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:509:y:2025:i:c:s0304380025002571

DOI: 10.1016/j.ecolmodel.2025.111271

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