Post-lambing Spatial Distribution of Dall’s Sheep in Southwest Yukon
Bibliographic record
Abstract
Dall’s sheep (Ovis dalli dalli) are a subspecies of thinhorn sheep that inhabit the rugged, mountainous environments of North America. Low-growing vegetation is important forage for Dall’s sheep and open, rocky slopes are important for predator avoidance. There is concern that climate change is reducing habitat availability for Dall’s sheep. One of the densest global populations of Dall’s sheep is in Kluane National Park and Reserve, in southwest Yukon. Since 1977, Park staff have conducted comprehensive aerial surveys of sheep on four mountain ranges within the park, forming what is now one of the longest-term datasets available on the species. I analyzed the spatial component of this dataset to assess the distribution of sheep on these ranges from 1977 to 2022 for the purpose of: (1) characterizing the habitat used by sheep (including by both nursery groups and ram groups separately) during the post-lambing period, and (2) determining whether the spatial distribution of these groups in the four surveyed ranges has changed over the monitoring period. A kernel density analysis was performed on the survey data to understand where sheep were being observed, followed by random forest modelling to understand the habitat characteristics of these areas. A pixel-wise Thiel-Sen analysis was performed on yearly kernel density distributions of sheep on each range to understand spatial trends in habitat use over time. These analyses showed that elevation and distance to glacial ice act as the two strongest predictors of Dall’s sheep habitat use, and that frequently used habitat can be characterised by mid-to high elevations on steep and rugged south-facing slopes. The relationship between sheep habitat and distance to ice differed between ranges. The analysis also showed that the majority of each range remains unchanged with respect to sheep habitat use, with only a few small areas of increasing or decreasing use on each range. Of these small areas of change, areas of increased use tended to be at higher elevations than areas of decreased use. This information will contribute to the management of Dall’s sheep in Kluane National Park and Reserve in helping prioritize conservation actions.
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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 | 0.001 |
| 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".