Mercury Stable Isotopes in Seabird Eggs Reflect a Gradient from Terrestrial Geogenic to Oceanic Mercury Reservoirs
Bibliographic record
Abstract
Elevated mercury concentrations ([Hg]) were found in Alaskan murre (Uria spp.) eggs from the coastal embayment of Norton Sound relative to insular colonies in the northern Bering Sea-Bering Strait region. Stable isotopes of Hg, carbon, and nitrogen were measured in the eggs to investigate the source of this enrichment. Lower δ(13)C values in Norton Sound eggs (-23.3‰ to -20.0‰) relative to eggs from more oceanic colonies (-20.9‰ to -18.7‰) indicated that a significant terrestrial carbon source was associated with the elevated [Hg] in Norton Sound, implicating the Yukon River and smaller Seward Peninsula watersheds as the likely Hg source. The increasing [Hg] gradient extending inshore was accompanied by strong decreasing gradients of δ(202)Hg and Δ(199)Hg in eggs, indicating lower degrees of mass-dependent (MDF) and mass-independent Hg fractionation (MIF) (respectively) in the Norton Sound food web. Negative or zero MDF and MIF signatures are typical of geological Hg sources, which suggests murres in Norton Sound integrated Hg from a more recent geological origin that has experienced a relatively limited extent of aquatic fractionation relative to more oceanic colonies. The association of low δ(202)Hg and Δ(199)Hg with elevated [Hg] and terrestrial δ(13)C values suggested that Hg stable isotopes in murre eggs effectively differentiated terrestrial/geogenic Hg sources from oceanic reservoirs.
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 | 0.000 | 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".