Seaweed‐eating sheep show that <i>δ</i> <sup>34</sup> S evidence for marine diets can be fully masked by sea spray effects
Bibliographic record
Abstract
Rationale Stable sulfur isotope compositions ( δ 34 S values) are a useful marker of terrestrial (lower δ 34 S) versus marine (higher δ 34 S) diets. In coastal areas, 34 S‐enriched sea spray can obscure these marine/terrestrial differences. We sought to establish whether δ 34 S values of sea spray‐affected terrestrial fauna can be distinguished from those of marine‐feeding terrestrial fauna. Methods We measured bone and dentine collagen δ 34 S values, as well as stable carbon ( δ 13 C) and nitrogen ( δ 15 N) isotope compositions via continuous flow elemental analysis/isotope ratio mass spectrometry of 21 sheep ( Ovis aries ) raised on an island (North Ronaldsay, UK) of <7 km 2 that had widely divergent access to marine (seaweed) and heavily sea spray‐affected terrestrial (grass) food sources. We also analyzed the bone collagen of marine and terrestrial fauna from this island. Results Sheep bone collagen showed well‐defined trends with highly significant correlations between δ 13 C and δ 15 N values indicative of feeding along a continuum of fully terrestrial to fully marine diets, consistent with other modern baseline data from marine and terrestrial animals in the same area. In contrast, δ 34 S values were generally elevated for all sheep and were not significantly correlated with either δ 13 C or δ 15 N values. Conclusions Our findings demonstrate that δ 34 S values are poorly suited for differentiating marine and terrestrial diets in terrestrial animals in areas with pronounced sea spray effects. Care must be taken to characterize the isotopic compositions of potential food items before δ 34 S values are used as a marker for reliance on marine protein in modern and ancient contexts.
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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 | 0.000 | 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) | 0.001 | 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".