Caribou in the cross-fire? Considering terrestrial lichen forage in the face of mountain pine beetle (Dendroctonus ponderosae) expansion
Bibliographic record
Abstract
Mountain pine beetle (MPB) has become an invasive forest pest of mature pine in western North America as it spreads beyond its former endemic range. Management actions such as timber harvest can reduce the spread of MPB but may affect species of conservation concern like woodland caribou. Our goal was to inform MPB management within caribou ranges by exploring the impacts of MPB on caribou habitat-focusing on terrestrial lichens, an important winter food for caribou. We evaluated differences in lichen cover among four MPB management actions: timber harvest, wildfires, leaving MPB killed trees as-is, and single-tree cut-and-burn control. We found little evidence that leaving MPB killed trees as-is or controlling MPB using single-tree cut-and-burn impacted lichen cover. However, we found that lichen cover was lower in timber harvested and burned areas compared to intact undisturbed forest but only 10 to 20 years post-disturbance, respectively. Our results suggest that despite short-term reductions in lichen cover, using timber harvesting and prescribed burns to control MPB may balance management needs for MPB while maintaining lichen cover over time. However, using timber harvesting and prescribed burns to manage MPB is likely to have detrimental population-level effects on caribou by increasing the proportion of disturbed habitat and thus predators within caribou ranges. Among the four management actions that we evaluated, the cut-and-burn control program balances the need to limit the spread of MPB while also limiting negative impacts on caribou food. Our work addresses some of the challenges of managing competing forest and ecosystem values by evaluating the consequence of forest pest management actions on an important food resource for a species-at-risk.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".