Temperature-dependent bioaccumulation of metals in marine mollusks: integrating thermal performance curves, machine learning, and toxicokinetic modeling

Pham, M.H.; Tran, A.T.; Duong, T.Y.N.; Peijnenburg, W.J.G.M.; Le, T.T.Y.

doi:doi:10.1021/acs.est.6c03813

Temperature regulates mollusk physiology and can alter metal bioaccumulation through filtration, uptake, growth dilution, and elimination. Yet many toxicokinetic (TK) applications treat temperature as a simple correction to a subset of rates and rarely account for trait- and context-dependence, limiting transferability across studies, seasons, and warming scenarios. Here we synthesize experimental evidence for marine univalve and bivalve mollusks and develop a temperature-aware framework that couples one-compartment mass-balance TK with temperature-dependent filtration and growth, while statistically linking absorption efficiency and elimination to temperature, species traits (e.g., body size), and metal chemical properties. Thermal responses in filtration and growth were captured with unimodal performance functions; machine learning was used for predictor screening. Evaluated against an independent data set, the framework reproduced internal concentrations across multiple orders of...Show moreTemperature regulates mollusk physiology and can alter metal bioaccumulation through filtration, uptake, growth dilution, and elimination. Yet many toxicokinetic (TK) applications treat temperature as a simple correction to a subset of rates and rarely account for trait- and context-dependence, limiting transferability across studies, seasons, and warming scenarios. Here we synthesize experimental evidence for marine univalve and bivalve mollusks and develop a temperature-aware framework that couples one-compartment mass-balance TK with temperature-dependent filtration and growth, while statistically linking absorption efficiency and elimination to temperature, species traits (e.g., body size), and metal chemical properties. Thermal responses in filtration and growth were captured with unimodal performance functions; machine learning was used for predictor screening. Evaluated against an independent data set, the framework reproduced internal concentrations across multiple orders of magnitude with good agreement (R2 approximate to 0.73). Across the compiled evidence, filtration and growth showed strong species-specific thermal sensitivity, while metal chemistry primarily structured uptake. In the limited multitemperature TK calibration data set, a positive association between temperature and elimination was observed, but this relationship should be regarded as provisional pending additional multitemperature uptake-depuration data sets. By explicitly representing temperature-sensitive filtration and turnover pathways, the approach enables scenario testing for warming and heat extremes and provides a practical basis for improving the interpretation of bioaccumulation factors, seasonal biomonitoring, and temperature-aware risk assessment under climate change.Show less

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Temperature-dependent bioaccumulation of metals in marine mollusks: integrating thermal performance curves, machine learning, and toxicokinetic modeling