[Published]: A dynamic dietary-proportion model for polychlorinated biphenyl accumulation in juvenile bluefin tuna


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The dietary habits of tuna in marine ecosystems are opportunistic, depend on prey availability, and change as tuna transition from larval to juvenile to adult. This behavior likely influences variations in toxic pollutant accumulation in their bodies. To develop a practical method for simulating pollutant concentrations and assessing marine environmental risk, this study created a theoretical model and numerical computation algorithm that accounts for the dynamic dietary proportions in tuna...

Ecotoxicol Environ Saf. 2025 Jul 21;302:118710. doi: 10.1016/j.ecoenv.2025.118710. Online ahead of print.

ABSTRACT

The dietary habits of tuna in marine ecosystems are opportunistic, depend on prey availability, and change as tuna transition from larval to juvenile to adult. This behavior likely influences variations in toxic pollutant accumulation in their bodies. To develop a practical method for simulating pollutant concentrations and assessing marine environmental risk, this study created a theoretical model and numerical computation algorithm that accounts for the dynamic dietary proportions in tuna predation. The opportunistic and stochastic nature of predation was represented by a statistical distribution of body length ratios between prey and predator, using a Bayesian-inferred approach to stochastically determine prey species and incorporate daily dietary composition changes. This model was applied to simulate the accumulation of Polychlorinated Biphenyls (PCBs) in juvenile bluefin tuna. Comparisons between calculated and measured PCB concentrations showed good agreement, validating the model. During the larval stage, zooplankton was the dominant prey. In the juvenile stage, its proportion decreased, while cephalopods and fish alternately increased. These findings highlight the importance of incorporating growth-dependent dietary shifts into bioaccumulation models.

PMID:40694911 | DOI:10.1016/j.ecoenv.2025.118710

Jiawen Hao, Yucong Liu, Yoshiki Nishi

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