Living in a burned landscape: woodland caribou (<i>Rangifer</i> <i>tarandus caribou</i>) use of postfire residual patches for calving in a high fire – low anthropogenic Boreal Shield ecozone
Bibliographic record
Abstract
Environment and Climate Change Canada (ECCC) calculated that 55% of Saskatchewan’s Boreal Shield has been disturbed by wildfire in the last 40 years. The 2012 Canadian Federal Recovery Strategy for woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)) states that these large-scale natural disturbances can cause caribou to cease use of portions of their range. This assumption neglects the potential habitat value of postfire residuals. We tested this assumption using 2 years of GPS data obtained from 56 female caribou to identify calving site selection. Seventy-nine calving events were identified from 91 individual calving seasons. For both calving and postcalving periods, woodland caribou preferred nonburned (>40 years) over burned habitats (≤40 years). Within burned areas, residual patches dominated by bogs–fens were preferred, indicating that burns with residuals are important woodland caribou calving habitat. The residuals may act as island refuges providing food–security, while surrounding burns provide reduced visual obstruction from which caribou can detect approaching predators. Although more data are necessary to make robust conclusions, this study provides novel insight into the ecological interactions of forest fires with woodland caribou in northern Saskatchewan, and offers important considerations regarding critical habitat identification and range-level planning to ensure all suitable caribou habitats are identified.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".