Winter Tracking Data Suggest that Migratory Seabirds Transport Per- and Polyfluoroalkyl Substances to Their Arctic Nesting Site
Bibliographic record
Abstract
Seabirds are often considered sentinel species of marine ecosystems, and their blood and eggs utilized to monitor local environmental contaminations. Most seabirds breeding in the Arctic are migratory and thus are exposed to geographically distinct sources of contamination throughout the year, including per- and polyfluoroalkyl substances (PFAS). Despite the abundance and high toxicity of PFAS, little is known about whether blood concentrations at breeding sites reliably reflect local contamination or exposure in distant wintering areas. We tested this by combining movement tracking data and PFAS analysis (nine compounds) from the blood of prelaying black-legged kittiwakes ( Rissa tridactyla ) nesting in Arctic Norway (Svalbard). PFAS burden before egg laying varied with the latitude of the wintering area and was negatively associated with time upon return of individuals at the Arctic nesting site. Kittiwakes ( n = 64) wintering farther south carried lighter burdens of shorter-chain perfluoroalkyl carboxylates (PFCAs, C 9 –C 12 ) and heavier burdens of longer chain PFCAs (C 13 –C 14 ) and perfluorooctanesulfonic acid compared to those wintering farther north. Thus, blood concentrations prior to egg laying still reflected the uptake during the previous wintering stage, suggesting that migratory seabirds can act as biovectors of PFAS to Arctic nesting sites.
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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 | 0.000 | 0.000 |
| 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".