Rapidly increasing methyl mercury in endangered ivory gull (Pagophilaeburnea) feathers over a 130 year record
Bibliographic record
Abstract
(Uploaded by Plazi for the Bat Literature Project) Mercury (Hg) is increasing in marine food webs, especially at high latitudes. The bioaccumulation and biomagnification of methyl mercury (MeHg) has serious effects on wildlife, and is most evident in apex predators. The MeHg body burden in birds is the balance of ingestion and excretion, and MeHg in feathers is an effective indicator of overall MeHg burden. Ivory gulls ( Pagophila eburnea ), which consume ice-associated prey and scavenge marine mammal carcasses, have the highest egg Hg concentrations of any Arctic bird, and the species has declined by more than 80% since the 1980s in Canada. We used feathers from museum specimens from the Canadian Arctic and western Greenland to assess whether exposure to MeHg by ivory gulls increased from 1877 to 2007. Based on constant feather stable-isotope ( δ 13 C, δ 15 N) values, there was no significant change in ivory gulls' diet over this period, but feather MeHg concentrations increased 45× (from 0.09 to 4.11 µg g −1 in adults). This dramatic change in the absence of a dietary shift is clear evidence of the impact of anthropogenic Hg on this high-latitude threatened species. Bioavailable Hg is expected to increase in the Arctic, raising concern for continued population declines in high-latitude species that are far from sources of environmental contaminants.
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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".