Dall's sheep horn growth and harvest management in the Mackenzie Mountains, Northwest Territories, Canada
Bibliographic record
Abstract
Abstract Across most of their native North American range, the horns of mountain sheep (Ovis spp.) males are getting smaller, a pattern attributed to selective hunting pressure. We measured the horns of 755 Dall's sheep males (Ovis dalli dalli) in the southern Mackenzie Mountains, Northwest Territories, between 2002 and 2017. For each male, we measured the circumference and length of each annulus for the right horn and calculated horn volume for each year. We examined changes in horn size in 4 different outfitter areas, using age at harvest as a covariate. Hunting pressure across years in the study area was consistently low, and this population did not experience the decline in horn size observed in several other mountain sheep populations in Canada. Over the 16‐year period, the average horn volume of harvested males was stable and even increased in 1 outfitter area. Local management of Dall's sheep delivered independently by the guide outfitters in the Mackenzie Mountains appears to contribute to maintaining a population of males that has not been adversely affected by strong selective hunting pressure. The resilience of this management strategy may be challenged by environmental changes associated with rapid warming in northern mountain environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".