Biogeographic Provinces of Total and Methyl Mercury in Zooplankton and Fish from the Beaufort and Chukchi Seas: Results from the SHEBA Drift
Bibliographic record
Abstract
Samples of copepods (Calanus hyperboreus) and arctic cod (Boreogadus saida) were collected along the SHEBA (Surface HEat Budget of the Arctic) drift track, which commenced in the Canada Basin (October 1997) and finished in the Mendeleev Basin (October 1998). Here, we report total mercury (HgT) and CH3Hg concentrations in these biological samples and examine concentration variability along the drift track in the context of trophic variation, inputs from land, spring mercury depletion events (MDEs), and oceanographic provinces. We find background concentrations of HgT in C. hyperboreus as low as 0.02 microg/g (dw), with the Canada Basin samples exhibiting approximately 2-fold higher mercury concentrations than those from the Chukchi Plateau and Mendeleev Abyssal Plain. This east-to-west trend in mercury concentration is punctuated by two and possibly three intervals of elevated mercury (HgT, 0.10-0.12 microg/g (dw); CH3Hg, 0.023-0.028 microg/g (dw)) along the drift track. One interval of elevated HgT and CH3-Hg levels occurred during and shortly after melt. %CH3Hg reached a maximum of 60% during this time period, three times higher than any other time during the drift. This transient rise in C. hyperboreus CH3Hg concentration seems to strongly point to mercury accumulated in snow during MDEs. However, the alignment of elevated mercury samples with oceanographic fronts and the observed regional differences between basins suggest that variation of mercury concentration is primarily a consequence of ocean structure. Given that large animals such as whales selectively forage in regions of higher food concentration such as fronts, recent change in the ice climate of the western Arctic Ocean, perhaps mediated by changes in heat storage, may provide the means to change their exposure to mercury thus explaining observed increases in mercury concentrations in western beluga whales during the 1990s.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".