Climate Variability and Temporal Trends of Persistent Organic Pollutants in the Arctic: A Study of Glaucous Gulls
Bibliographic record
Abstract
The impact of climate variability on temporal trends (1997-2006) of persistent organic pollutants (POPs; polychlorinated biphenyls [PCB], hexachlorobenzene [HCB], and oxychlordane) was assessed in glaucous gulls (Larus hyperboreus) breeding in the Norwegian Arctic (n = 240). The Arctic Oscillation (AO: an index of sea-level pressure variability in the Northern Hemisphere above 20 degrees N) with different time lags was used as a climate proxy. The estimated concentrations of POPs in glaucous gull blood/plasma declined substantially (16-60%) over the time period. Multiple regression analyses showed that the rates of decline for POPs were correlated to climate variation when controlling for potential confounding variables (sex and body condition). More specifically AO in the current winter showed negative associations with POP concentrations, whereas the relationships with AO measurements from the year preceding POP measurements (AO preceding summer and AO preceding winter) were positive. Hence, gulls had relatively higher POP concentrations in breeding seasons following years with high air transport toward the Arctic. Furthermore, the impact of AO appeared to be stronger for HCB, a relatively volatile compound with high transport potential, compared to heavy chlorinated PCB congeners. This study thus suggests that predicted climate change should be considered in assessments of future temporal trends of POPs in Arctic wildlife.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".