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Tracing pollution in Brown algae: Compositional profiles of potentially toxic elements.

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Brown algae show distinct Potentially Toxic Element (PTE) profiles, influenced by species and environment. Compositional data analysis reveals taxonomic structure, aiding marine pollution biomonitoring and bioremediation efforts.

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Area of Science:

  • Marine Ecology
  • Environmental Chemistry
  • Biomonitoring

Background:

  • Brown macroalgae are established biomonitors for marine pollution.
  • Potentially Toxic Element (PTE) composition in algae has not been analyzed using compositional data analysis (CoDA).

Purpose of the Study:

  • To apply CoDA for characterizing global PTE patterns in brown algae.
  • To investigate the influence of taxonomy and environmental factors on PTE profiles.
  • To assess the effectiveness of CoDA in biomonitoring and identifying contaminated sites.

Main Methods:

  • Utilized CoDA on over 1320 records of brown algae PTE composition.
  • Employed multivariate analyses to identify predictors of elemental profiles.
  • Extended profiling of Fucus spp. over three decades (1990-2021).

Main Results:

  • Zinc (Zn) was the dominant PTE (73.8%), followed by Copper (Cu) and Nickel (Ni).
  • Species identity was the strongest predictor of PTE profiles (R² = 33.9%).
  • Fucus spp. profiles were dominated by Iron (Fe) and Aluminum (Al), with significant temporal shifts observed, including increased Al and decreased Cu, Ni, and Cr in recent samples.

Conclusions:

  • PTE profiles in brown algae are taxonomically structured, reflecting species-specific regulation capacities and ecological niches.
  • CoDA is effective for identifying outlier samples from contaminated areas.
  • Standardized protocols are needed for improved long-term biomonitoring comparability.
  • Integrated absolute and compositional approaches enhance biomonitoring and bioremediation assessments.