Stone’s sheep (<i>Ovis dalli stonei</i>) lambing and nursery habitat selection
Bibliographic record
Abstract
Wildlife conservation often focuses on mitigating disturbance in critical habitats like reproductive ranges. We studied lambing and nursery habitat selection by Stone’s sheep ( Ovis dalli stonei (J.A. Allen, 1897)) in the Cassiar Mountains in British Columbia. We estimated the timing of parturition and delineated lambing and nursery habitats based on movement behaviours of collared females ( n = 18) and vaginal implant transmitters. We identified 23 lambing events in 2018 ( n = 4), 2019 ( n = 13), and 2020 ( n = 6). The median birth date was 17 May and ranged from 3 May to 14 June. Females remained in lambing habitats from 1.5 to 11.3 days with a median of 5.5 days. We examined habitat selection during the lambing and nursery periods at the home-range scale using resource selection functions, and at a finer scale using integrated step-selection analyses. Females selected southwest slopes in rugged terrain at mid-elevations, suggesting selection for warmer micro-climates and features that facilitate predator avoidance. Females avoided habitats near roads during the lambing period but showed selection for habitats near roads during the nursing period. We developed predictive maps of suitable lambing and nursery ranges to inform land planning to help reduce overlap of anthropogenic disturbance with potential reproductive habitats.
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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 | 0.001 | 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".