Temporal trends of selected POPs and the potential influence of climate variability in a Greenland ringed seal population
Bibliographic record
Abstract
Temporal trends of selected POPs (PCB-52 and 153, p,p'-DDE, HCB, α- and β-HCH) in blubber of ringed seals (Pusa hispida) collected from the early 1990s to 2010 from central West Greenland were studied. In this period, the climate of Greenland warmed and the influences of climate indices such as winter sea-ice coverage (November-May), the number of sea-ice days during winter in Disko Bay, water temperature and salinity at Fyllas Banke during the preceding summer and the Arctic Oscillation Index (AOI) during the preceding winter on concentrations of selected POPs were evaluated using multiple regressions and an information-theoretic approach. Biological co-variables such as age, sex and trophic position (as determined by δ(15)N analysis) of seals were also evaluated. Decreasing levels of the selected POPs were found in all cases and with the highest rate for α-HCH (-10.5% annually) and the lowest rate for β-HCH (-1.9% annually). Sex and age were found to have strong predictive power in the case of PCB-52 and trophic position in the case of p,p'-DDE. Among the climate indices the strongest predictive power was found for the number of sea-ice days in the case of PCB-52, the AOI winter index in the case of α-HCH and salinity at Fyllas Banke during the preceding summer in the case of β-HCH. The present study documents the need for including both biological variables and climate variability parameters in temporal trend studies of POPs in Arctic biota.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".