The influence of fire history on selection of foraging sites by barren-ground caribou
Bibliographic record
Abstract
We used an information-theoretic model comparison approach to investigate the influence of forest stand attributes resulting from wildfire on the occupancy of winter habitats by barren-ground caribou (Rangifer tarandus groenlandicus) in the Northwest Territories, Canada. We used field data describing forest stand and understory attributes to develop multinomial regression models. These analyses identified a combination of ground cover type and tree volume (i.e., stand basal area) as best able to describe the observed selection of feeding sites. An observed increase in the percent ground cover of lichen had a positive influence on site selection, while an increase in the percent rock cover and basal area of conifer trees had a negative influence on selection of feeding sites by caribou. The most parsimonious regression model predicted site use with an accuracy of 87%. Lastly, we used published equations to determine the biomass of fruticose lichens on experimental and control sites classified as unburned. Our data indicated that fruticose lichen biomass on the winter range of the Bathurst herd of barren-ground caribou was high compared to winter habitats of caribou in Alaska and the Yukon Territory, and falls in the general range of lichen values reported for winter habitats of the more easterly Beverly herd, as well as portions of Saskatchewan, Manitoba, and Ungava. Overall, the analyses of feeding-site selection suggest that Bathurst caribou forage in areas with a high percentage cover and biomass of lichen, and that future increased incidence and severity of forest fires could cause a temporary decrease in the quality of winter habitat available to the Bathurst herd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".