Evidence of Microplastic Translocation in Wild-Caught Fish and Implications for Microplastic Accumulation Dynamics in Food Webs
Bibliographic record
Abstract
The presence of microplastics within the gut of animals is well documented. Whether microplastics bioaccumulate in organisms and biomagnify in food webs remains unclear and relies on the ability of microplastics to translocate to other tissues. Here, we demonstrate the widespread presence of microplastics and other anthropogenic microparticles in the gastrointestinal tract, fillet, and livers of seven species of sportfish from Lake Simcoe, Ontario, Canada. Larger fish had a higher microplastic load compared to smaller fish, but the opposite trend was observed with translocated microplastics standardized by fish mass (i.e., smaller fish contained more translocated particles per gram wet weight than larger fish). Moreover, we observed no evidence of biomagnification as there was no significant relationship between the trophic level and total or translocated microplastics per individual. Overall, this suggests that microplastics are translocating, but that excretion of translocated particles or growth dilution may be occurring rather than bioaccumulation and biomagnification. Moreover, the assemblages of shapes and material types varied among tissues, suggesting that particle characteristics may predict biological fate. Our findings highlight the need for further work to understand the mechanisms of microplastic translocation and excretion and the implications for the dynamics of microplastics accumulation in food webs and human exposure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".