Displacement of Mountain Caribou From Winter Habitat by Snowmobiles
Bibliographic record
Abstract
Abstract: Mountain caribou are an ecotype of woodland caribou ( Rangifer tarandus caribou ) that live in subalpine forests in southeastern British Columbia, Canada, extending into northern Idaho and Washington, USA. These caribou are listed as Threatened in Canada, Endangered in the United States, and are the subject of recovery planning efforts in both countries. Many areas of mountain caribou winter habitat experience intensive use by recreational snowmobilers. During 4 surveys, we recorded caribou on all 4 census blocks with little or no snowmobile activity (x̄ density = 0.41 caribou/km 2 ), but during 3 of 4 years, we observed no caribou on the census block with intensive snowmobile activity. The year we observed caribou on the snowmobile block, most were using areas inaccessible to snowmobiles. We used a Resource Selection Function (RSF) based on radiotelemetry data for the area to compare habitat quality among the different census blocks. The absence of caribou from the intensive snowmobile area during most years could not be explained by differences in habitat quality. The RSF predicted that the intensive snowmobile area could support 53‐96 caribou (95% CI). We conclude that intensive snowmobiling has displaced caribou from an area of suitable habitat. We recommend that snowmobile activity be restricted from all or most high‐quality mountain caribou habitat as part of the recovery planning process.
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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 | 0.001 |
| 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".