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“Can bivalves, water, and sediment be integrated into anthropogenic microdebris monitoring? A case study of Magallana gigas with a global comparative analysis”

Marine Pollution Bulletin 2026

Summary

Researchers simultaneously sampled water, sediment, and Pacific oyster tissue at four sites in a southwestern Atlantic estuary, finding that polyester fibers dominated across all compartments but that no statistically significant correlations emerged between environmental and biological matrices, underscoring the complexity of linking contamination levels across compartments.

Study Type Environmental

Continuous monitoring plays a key rol in assessing environmental contamination and addressing knowledge gaps related to anthropogenic microdebris (AMD) including microplastics (MPs). This study evaluates a multi-matrix framework that jointly considers water, sediment, and tissue of the sentinel bivalve Magallana gigas within a Southwestern Atlantic estuary. Sampling was conducted at four sites during spring seasons 2021 and 2022, and particles were characterized using stereoscopic microscopy and Raman spectroscopy. Mean particle abundance, after subtracting procedural blanks (〜2 items), was 0.20 ± 0.16 items g-1 ww in oyster tissue, 13 ± 6 items L-1 in water, and 210 ± 87 items kg-1 dw in sediment in 2021, and 0.28 ± 0.26 items g-1 ww, 10 ± 7 items L-1, and 117 ± 64 items kg-1 dw respectively, in 2022. Fibers between 0.5 and 1.5 mm dominated across matrices. Polyester (PES, PET), high density polyethylene (HDPE), polypropylene (PP), cellulose acetate (CA) and cotton were identified among the analyzed particles, indicating mixed anthropogenic sources. No statistically significant relationships among matrices were detected within the available dataset, highlighting the complexity of linking environmental compartments. When placed in a global context, oysters from the study area fell within the lower range of reported concentrations, although methodological heterogeneity among studies limits strict comparisons. This study provides a case-study-based multi-matrix framework that explores how biological and environmental compartments can be jointly assessed to improve interpretation of AMD contamination. The results identify elements that could support future harmonized monitoring strategies.

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