Muskoxen in the high Arctic‐temporal and spatial differences in body size
Bibliographic record
Abstract
Abstract The life history of ungulates is affected by factors such as climate, population density and resource availability. With focus on the muskoxen Ovibos moschatus living in Kangerlussuaq in western Greenland, Jameson Land in north‐eastern Greenland and on Banks and Victoria Islands in northern Canada, we tested spatial variation in life‐history traits measured by mandibular growth. In accordance with expectations, we found that muskoxen in the southernmost and low Arctic area (Kangerlussuaq) grew faster, matured earlier, reproduced earlier, reached larger adult size and additionally had a higher reproduction than muskoxen living in the more northern areas. In the Kangerlussuaq population, mandible lengths in adult males changed temporally with density, with significant smaller adult males present in high population densities in western Greenland. It was especially the male mandible lengths that responded to environmental factors. In females, spatial differences were less pronounced than in males and is probably explained by females facing a trade‐off between investment in own growth and reproduction, whereas a large body size is more important for the males, which are exposed to sexual selection. This explanation was, furthermore, supported by the fact that the calf percentage was higher in western Greenland than in any of the other studied areas in spite of the density‐dependent effects detected within the male gender.
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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".