Demographic and behavioural response of woodland caribou to forest harvesting
Bibliographic record
Abstract
We investigated whether woodland caribou ( Rangifer tarandus caribou ) would remain in a 2772 km2 area in eastern Quebec where the forest management plan included the preservation of large forest blocks (35–182 km2) linked with >400 m wide corridors and where cuts were amalgamated in large zones. To evaluate changes in caribou abundance and habitat selection, we conducted five aerial surveys and followed by telemetry 13 to 22 female caribou each year, from March 1998 to March 2005. Caribou numbers declined by 59% between 1999 and 2001 but gradually recovered to initial abundance. Female survival increased from 73.3% in 1999 to 87.3%–93.4% in 2004 and 2005. Caribou selected protected blocks, used corridors in proportion to their availability, and avoided logged areas. They preferred closed conifer stands without terrestrial lichens and open conifer stands with or without terrestrial lichens throughout the study. Open habitats (clearcuts and burns), regenerating sites, mixed and deciduous stands, and water bodies were avoided. The main zones used by caribou gradually shifted towards the southwest of the study area, likely as a result of disturbance and habitat loss due to logging of mature conifers in the east. We conclude that caribou numbers were maintained within the managed area as a result of the presence of protected blocks and uncut continuous forest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".