Multi-dietary tracer approach reveals little overlap in foraging ecology between seasonally sympatric ringed and harp seals in the high Arctic
Bibliographic record
Abstract
The rapid rate of climate change in the Arctic is causing broad-scale changes to the physical environment and biological communities. Characterizing the foraging ecology and habitat use of Arctic marine top predators of high ecological and cultural significance is essential to our understanding of their vulnerability to ecosystem change, especially when there is potential for dietary resource competition in spatially co-occurring species. We therefore undertook this study to explore dietary resource competition between seasonally sympatric ringed seals (Pusa hispida) and harp seals (Pagophilus groenlandicus) in Mittimatalik (previously known as Pond Inlet), Nunavut, Canadian Arctic. We used bulk stable isotopes (δ13C and δ15N), fatty acid-specific carbon isotopes (δ13C), fatty acid profiles, and diatom lipid biomarkers in a multi-tracer framework to track carbon and trophic pathways in liver and muscle of both seal species. Altogether, the dietary tracers showed little overlap in the diet between ringed seals and harp seals when they co-occurred in the open-water season in northwest Baffin Bay. Though a high dependence on sea ice-derived carbon sources for both species was found, dietary tracers suggested that ringed seals relied to a far greater extent on sympagic carbon sources (~80% vs. 50% for harp seals) and a greater extent of benthic/coastal prey species compared to the more pelagic feeding harp seals. Ringed seal samples were available year-round, and analyses revealed a clear seasonal pattern of foraging on sympagic and benthic prey during ice-covered months of the year and shifting to greater reliance on pelagic prey during the summer open-water season. Overall, ringed seals may be more vulnerable to changes in sea-ice dynamics in the rapidly changing Arctic than harp seals, though it remains difficult to predict future dietary plasticity and competition between co-occurring top predators in an increasingly ice-free Arctic with a changing prey community.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".