Large size (>100‐μm) microplastics are not biomagnifying in coastal marine food webs of British Columbia, Canada
Bibliographic record
Abstract
Microplastics (MPs) contamination in marine environments is of increasing concern, as plastic particles are globally ubiquitous across ecosystems. A large variety of aquatic taxa ingest MPs, but the extent to which animals accumulate and transfer MPs through food webs is largely unknown. In this study, we quantified MP uptake in bivalves, crabs, echinoderms, and fish feeding at different trophic levels at three sites on southern Vancouver Island. We paired stable-isotope food web analysis with MP concentrations in digestive tracts across all trophic levels and in fish livers. We then used Bayesian generalized linear mixed models to explore whether bioaccumulation and biomagnification were occurring. Our results showed that MPs (100-5000 μm along their longest dimension) are not biomagnifying in marine coastal food webs, with no correlation between the digestive tract or fish liver MP concentrations and trophic position of the various species. Ecological traits did, however, affect microplastic accumulation in digestive tracts, with suspension feeder and smaller-bodied planktivorous fish ingesting more MPs by body weight. Trophic transfer occurred between prey and predator for rockfish, but higher concentrations in full stomachs compared with empty ones suggested rapid excretion of ingested MPs. Collectively, our findings suggested the movement of MP through marine food webs is facilitated by species-specific mechanisms, with contamination susceptibility a function of species biology, not trophic position. Furthermore, the statistical methods we employ, including machine learning for classifying unknown particles and a probabilistic way to account for background contamination, are universally applicable to the study of microplastics. Our findings advance understanding of how MPs enter and move through aquatic food webs, suggesting that lower-trophic-level animals are more at risk of ingesting >100-μm MPs, relative to higher-trophic-level animals. Our work also highlights the need to advance the study of <100-μm MPs, which are still poorly understood and may need to be considered separately in ecological risk assessments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".