Movements, foraging habits, and habitat use strategies of northern woodland caribou during winter: Implications for forest practices in British Columbia
Bibliographic record
Abstract
Land managers face increasing challenges as they try to balance timber harvesting with the habitat requirements of wildlife, including those of woodland caribou in north-central British Columbia. With the aim of conserving caribou by improving forest practices, we employed a hierarchical, scale-explicit approach to study the processes governing movement and distribution of the northern woodland caribou ecotype. Investigations of foraging sites north of Prince George, British Columbia revealed that caribou in forested and alpine areas cratered at locations with relatively low snow depths and relatively large amounts of terrestrial lichens. When snow depth, snow hardness, and snow density increased, caribou fed more frequently at trees supporting abundant arboreal lichens. Feeding activities of caribou in forested foraging patches were positively related to the biomass of several terrestrial lichen species and to decreasing snow depth; the number of arboreal feeding sites increased as snow depth and hardness increased. We identified three scales of habitat selection based on movement rates of caribou fitted with GPS collars. For all scales, caribou selected pine-lichen woodland and windswept rocky slopes. Predation risk was greatest for caribou travelling between habitat patches, was lowest for caribou in alpine habitats, and had no apparent influence on intra-patch movements.Land use plans should address the needs of northern woodland caribou by ensuring that large patches of widely distributed pine-lichen woodland are maintained on the landscape, recognize the limiting effects of deep snow (i.e., > 50–80 cm), and encourage silvicultural strategies that minimize the creation of early seral-stage forests adjacent to caribou movement routes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".