Bioaccumulation and trophic magnification of emerging and legacy per- and polyfluoroalkyl substances (PFAS) in a St. Lawrence River food web
Bibliographic record
Abstract
Research on per- and polyfluoroalkyl substances (PFAS) in freshwater ecosystems has focused primarily on legacy compounds and little is still known on the presence of emerging PFAS. Here, we investigated the occurrence of 60 anionic, zwitterionic, and cationic PFAS in a food web of the St. Lawrence River (Quebec, Canada) near a major metropolitan area. Water, sediments, aquatic vegetation, invertebrates, and 14 fish species were targeted for analysis. Levels of perfluorobutanoic acid (PFBA) in river water exceeded those of perfluorooctanoic acid (PFOA) or perfluorooctane sulfonate (PFOS), and a zwitterionic betaine was observed for the first time in the St. Lawrence River. The highest mean PFAS concentrations were observed for the benthopelagic top predator Smallmouth bass (Micropterus dolomieu, Σ60PFAS ∼ 92 ± 34 ng/g wet weight whole-body) and the lowest for aquatic plants (0.52–2.3 ng/g). Up to 33 PFAS were detected in biotic samples, with frequent occurrences of emerging PFAS such as perfluorobutane sulfonamide (FBSA) and perfluoroethyl cyclohexane sulfonate (PFECHS), while targeted ether-PFAS all remained undetected. PFOS and long-chain perfluorocarboxylates (C10–C13 PFCAs) dominated the contamination profiles in biota except for insects where PFBA was predominant. Gammarids, molluscs, and insects also had frequent detections of PFOA and fluorotelomer sulfonates, an important distinction with fish and presumably due to different metabolism. Based on bioaccumulation factors >5000 and trophic magnification factors >1, long-chain (C10–C13) PFCAs, PFOS, perfluorodecane sulfonate, and perfluorooctane sulfonamide qualified as very bioaccumulative and biomagnifying. Newly monitored PFAS such as FBSA and PFECHS were biomagnified but moderately bioaccumulative, while PFOA was biodiluted.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".