Sulfur isotopes (δ34S) in Arctic marine mammals: indicators of benthic vs. pelagic foraging
Bibliographic record
Abstract
Consumer tissue stable carbon isotope compositions (δ 13 C) are well established indicators of benthic and pelagic foraging in marine ecosystems. Stable sulfur isotope compositions (δ 34 S) are also potentially useful in this regard but have not been widely utilized outside of estuaries and salt marsh ecosystems. To test the ability of δ 13 C and δ 34 S to reflect benthic and pelagic foraging, we analyzed the stable carbon, nitrogen (δ 15 N), and sulfur isotope compositions of bone collagen from walrus (an obligate benthic feeder) and ringed seal (a mixed benthic/pelagic feeder) sampled from across the North American Arctic. Both had relatively low δ 34 S values compared to those typically observed in marine consumers. These data suggest an important role for benthic microalgae in coastal marine food webs in the Arctic. At all of the 10 locations where both taxa could be sampled, walrus had lower δ 34 S values than ringed seal, suggesting that this measurement is a useful indicator of benthic and pelagic foraging in nearshore Arctic environments. Contrary to expectations, there were no consistent differences in δ 13 C between walrus and ringed seal at any of these sites, suggesting that this measurement may not always be best interpreted in light of benthic vs. pelagic foraging, particularly when comparisons are made across trophic levels. When the foraging ecology of a consumer is unknown, our data suggest that δ 34 S may be a more sensitive indicator of the relative importance of benthic and pelagic prey in the diet than δ 13 C.
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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 | 0.001 | 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".