Stable isotope analysis reveals habitat-mediated variability in the ecology of Pacific hagfish <i>Eptatretus stoutii</i>
Bibliographic record
Abstract
The coastal shelves of the Northeast Pacific have supported fisheries for centuries, resulting in numerous studies on the ecology of target species. However, our understanding of species that are not actively targeted by fisheries, such as Pacific hagfish Eptatretus stoutii (Lockington, 1878), is not as resolved. We conducted stable isotope analysis on Pacific hagfish from an experimental fishery within three distinct habitats along Canada’s west coast—a narrow fjord, a sound, and a continental shelf—revealing intraspecific variability in δ 13 C and δ 15 N isotopic signatures. Hagfish collected from the fjord had the lowest δ 13 C and δ 15 N isotopic signatures, those in the sound had intermediate values, and those from offshore on the continental shelf had the highest isotopic signatures. We propose that this trend is the result of varying amounts of terrestrial nutrient inputs based on proximity to shore, in addition to variable chemoautotrophic activity. Terrestrial nutrients are introduced into marine food webs through runoff and are known to exhibit more depleted isotopic signatures than marine-based nutrients. Chemoautotrophy also produces low δ 13 C and δ 15 N signatures. These results provide novel insight on stable isotope signatures in Pacific hagfish in British Columbia and may act to inform future research on this species.
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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 | 0.000 | 0.001 |
| 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".