If You Build It, Will They Come? Caribou Habitat Restoration for Pipeline Projects
Bibliographic record
Abstract
The federal Recovery Strategy for the Woodland Caribou (Rangifer tarandus caribou), Boreal Population in Canada, identifies coordinated actions to reclaim woodland caribou habitat as a key step to meeting current and future caribou population objectives. Actions include restoring industrial landscape features such as roads, seismic lines, pipelines, cut-lines, and cleared areas in an effort to reduce landscape fragmentation and the changes in caribou population dynamics associated with changing predator-prey dynamics in highly fragmented landscapes. Reliance on habitat restoration as a recovery action within the federal Recovery Strategy is high, identifying 65% undisturbed habitat in a caribou range as the threshold to providing a 60% chance that a local population will be self-sustaining. In alignment with the federal Recovery Strategy, Alberta’s Provincial Woodland Caribou Policy identifies habitat restoration as a critical component of long-term caribou habitat management. Habitat restoration initiatives of Alberta’s historical industrial footprint within caribou ranges began in 2001 and have largely focused on linear corridors, including pipelines. Initiatives include revegetation treatments, access control programs and studies, and restricting the growth of plant species that are favourable to moose and deer, the primary prey for wolves. Habitat restoration for pipelines also includes pre-construction planning to reduce disturbance and create line-of-sight breaks, and construction techniques that promote natural vegetation recovery. Lessons learned from habitat restoration programs implemented on pipeline projects in northeastern Alberta will be shared as an opportunity to improve common understanding of restoration techniques, the barriers to implementation, and potential outcomes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".