Compound-specific isotope analyses of harp seal teeth: tools for trophic ecology reconstruction
Bibliographic record
Abstract
As sentinels of ecosystem health, high trophic level predators integrate information through all levels of the food web. Their tissues can be used to investigate spatiotemporal variability in foraging behaviour, and with the appropriate analytical methods and tools, archived samples can be used to reconstruct past trophic interactions. Harp seal Pagophilus groenlandicus teeth collected in the 1990s from the Northwest Atlantic were analysed for bulk stable carbon and nitrogen isotopes (δ13Cbulk and δ15Nbulk), and compound-specific stable nitrogen isotopes of amino acids (δ15NAA) for the first time. We developed a fine-scale, annual growth layer group (GLG) dentine sub-sampling method corresponding to the second and third year of life. In accordance with previous diet studies, while there was individual variability in δ15Nbulk, δ13Cbulk and δ15NAA measurements, we did not detect significant differences in isotopic niche widths between males and females, or between GLGs. Relative trophic position was calculated as the baseline-corrected δ15NAA values using trophic (glutamic acid) and source (phenylalanine and glycine) amino acids. Variability was measured between individuals in their relative trophic position, but within-individual variability was low, suggesting that they fed at the same trophic level over these 2 yr of life. These novel δ15NAA data may therefore suggest individual, specialist harp seal foraging behaviour in sub-adults. Our findings show that compound-specific stable isotope signatures of archived, inert predator tissues can be used as tools for the retrospective reconstruction of trophic interactions on broad spatiotemporal scales.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".