Origin of Sulfur in Diet Drives Spatial and Temporal Mercury Trends in Seabird Eggs From Pacific Canada 1968–2015
Bibliographic record
Abstract
Mercury (Hg) is a neurotoxin that can be particularly harmful to top predators because it biomagnifies through the food web. Due to variation in the food web structure, variation in Hg exposure in predators may represent variation in diet rather than Hg availability. We measured Hg in eggs from six seabird species ( N = 537) over 47 years. In contrast to expectation, storm-petrels feeding partially on invertebrates had the highest Hg burden while herons feeding on large fish had the lowest Hg burden. A multiple regression showed that Hg correlated with δ 34 S ( R 2 = 0.86) rather than trophic level (δ 15 N of “trophic” amino acids). Sulfate-rich environments (high δ 34 S) have sulfate-reducing bacteria that produce methylmercury. Variation in Hg within and among seabirds near the top of the food web was associated with variation in δ 34 S at the base of the food web more so than trophic position within the food web. Hg levels in seabirds only changed over time for those species where δ 34 S also varied in tandem; after accounting for diet (δ 34 S), there was no variation in Hg levels. Variation in Hg in seabirds across space and time was associated with the origin of sulfur in the diet.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".