Movement pathways and habitat selection by woodland caribou during spring migration
Bibliographic record
Abstract
Woodland caribou (Rangifer tarandus caribou) are a threatened species throughout Canada. Special management is therefore required to ensure habitat needs are met, particularly because much of their current distribution is heavily influenced by resource extraction activities. Although winter habitat is thought to be limiting and is the primary focus of conservation efforts, maintaining connectivity between summer and winter ranges has received little attention. We used global positioning system data from an interprovincial, woodland caribou herd to define migratory movements on a relatively pristine range. Non-linear models indicated that caribou movement during migration was punctuated; caribou traveled for some distance (movement phase) followed by a pause (resting/foraging phase). We then developed resource selection functions (RSFs), using case-controlled logistic regression, to describe resting/foraging sites and movement sites, at the landscape scale. The RSFs indicated that caribou traveled through areas that were less rugged and closer to water than random and that resting/foraging sites were associated with older forests that have a greater component of pine, and are further from water than were random available locations. This approach to analyzing animal location data allowed us to identify two patterns of habitat selection (travel and foraging/resting) for caribou during the migratory period. Resultant models are important tools for land use planning to ensure that connectivity between caribou summer and winter ranges is maintained.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".