Seal Occurrence and Habitat Use during Summer in Petermann Fjord, Northwestern Greenland
Bibliographic record
Abstract
Ice-associated seals are considered especially susceptible and are potentially the first to modify distribution and habitat use in response to physical changes associated with the changing climate. Petermann Glacier, part of a unique ice-tongue fjord environment in a rarely studied region of northwestern Greenland, lost substantial sections of its ice tongue during major 2010 and 2012 calving events. As a result, changes in seal habitat may have occurred. Seal occurrence and distribution data were collected in Petermann Fjord and adjacent Nares Strait region over 27 days (2 to 28 August) during the multidisciplinary scientific Petermann 2015 Expedition on the icebreaker Oden. During 239.4 hours of dedicated observation effort, a total of 312 individuals were recorded, representing four species: bearded seal (Erignathus barbatus), hooded seal (Crystophora cristata), harp seal (Pagophilus groenlandicus), and ringed seal (Pusa hispida). Ringed seals were recorded significantly more than the other species (χ2 = 347.4, df = 3, p < 0.001, n = 307). We found significant differences between species in haul-out (resting on ice) behavior (χ2 = 133.1, df = 3, p < 0.001, n = 307). Bearded seals were more frequently hauled out (73.1% n = 49), whereas ringed seals were almost exclusively in water (93.9%, n = 200). Differences in average depth and ice coverage where species occurred were also significant: harp seals and bearded seals were found in deeper water and areas of greater ice coverage (harp seals: 663 ± 366 m and 65 ± 14% ice cover; bearded seals: 598 ± 259 m and 50 ± 21% ice cover), while hooded seals and ringed seals were found in shallower water with lower ice coverage (hooded seals: 490 ± 163 m and 38 ± 19% ice cover; ringed seals: 496 ± 235 m, and 21 ± 20% ice cover). Our study provides an initial look at how High Arctic seals use the rapidly changing Petermann Fjord and how physical variables influence their distribution in one of the few remaining ice-tongue fjord environments.
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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 | 0.000 |
| 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".