Size and Biomagnification: How Habitat Selection Explains Beluga Mercury Levels
Bibliographic record
Abstract
Mercury (Hg) levels in the Beaufort Sea beluga (Delphinapterus leucas) population increased during the 1990s; levels have since declined but remain higher than the 1980s. The diet of this beluga population is not well-known, thus it is difficult to assess dietary Hg sources. During the summer, the Beaufort Sea belugas segregate by length, sex, and reproductive status corresponding to habitat use that may result in feeding differences and ultimately Hg uptake. To test this hypothesis, we examine beluga dietary variation using fatty acid profiles and determine which biological variables best predict diet Relationships between biological variables and fatty acids were further evaluated with stable isotopes and Hg concentrations in liver and muscle. Hg concentrations in muscle were better related to liver delta15N than muscle delta15N. Stable isotopes and fatty acids are compared in their ability to describe dietary Hg processes in beluga. Fatty acids provided support for influences of whale behavior on dietary Hg uptake, whereas stable isotopes inferred tissue Hg metabolic rates. Here, we show beluga length drives diet variability leading to differences in Hg uptake and biomagnification processes dominate beluga Hg levels over Hg bioaccumulation over time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".