Interspecies calibration for biomonitoring metal contamination in coastal waters using oysters and mussels.

Differences in metal bioaccumulation among species make it difficult to compare biomonitoring results obtained using different marine bivalve species. To address this challenge and improve the interpretation of biomonitoring data, we studied the toxicokinetic mechanisms underlying these differences and developed a method to estimate seawater metal concentrations based on metal concentrations in the organisms. We transplanted six common species of oysters and mussels found in Chinese coastal waters into the Jiulong River estuary and monitored metal concentrations in the organisms, water, and suspended particles every three days over a six-week period. A one-compartment first-order toxicokinetic model was used to describe the relationship between metal bioaccumulation and metal concentrations in the environment. The model parameters, including aqueous uptake (ku) and dietary assimilation (kp) rate constants, and elimination rate constant (ke), were estimated using a Markov Chain Monte Carlo fitting method with a priori information from a systematic review we conducted. The toxicokinetic model successfully fitted the temporal changes in metal bioaccumulation in all six bivalve species and explained the interspecies differences. Using the calibrated models, we were able to calculate metal concentrations in the seawater at the bivalve collection sites and enable comparisons of biomonitoring data across multiple species. In conclusion, we have established a toxicokinetic framework to explain interspecies differences in metal bioaccumulation in six commonly found bivalves and provided a useful tool for interpreting biomonitoring data in coastal environments.

• Publication year

  2023

• Venue

  Science of the Total Environment

• Publication date

  2023-04-01

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.2139/ssrn.4377326PMID 37105479
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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