Precommercial Thinning Reduces Snowshoe Hare Abundance in the Short Term
Bibliographic record
Abstract
ABSTRACT Management of young forests is not often considered in conservation plans, but young forests provide habitat for some species of conservation concern. Snowshoe hares ( Lepus americanus ), critical prey of forest carnivores including the United States federally threatened Canada lynx ( Lynx canadensis ), can be abundant in young montane and subalpine forests with densely spaced saplings and shrub cover. Precommercial thinning (PCT) is a silvicultural technique that reduces sapling and shrub density on young forest stands. We tested for effects of PCT on snowshoe hare abundance for 2 years after experimental treatment at 3 replicate study areas. We also tested the effectiveness of a precommercial thinning with reserves (PCT‐R) prescription, where 20% of the total stand was retained in uncut quarter‐hectare patches. All stands were in montane—subalpine coniferous forests of western Montana, USA, where there is a persistent population of Canada lynx. Posttreatment changes in abundance were strongly negative on stands treated with standard PCT prescriptions (100% of the stand was treated), relative to both controls and stands treated with PCT‐R. Trapping, snowtrack, and winter fecal‐pellet indices indicated that snowshoe hares used the quarter‐ha retention patches more than thinned portions of the PCT‐R‐treated stands in winter. We suggest that managing forest landscapes for high snowshoe hare abundance will require adoption of silvicultural techniques like PCT‐R for stands that will be thinned, in addition to conservation of structurally valuable early and late‐successional forest stands.
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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 | 0.000 | 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) | 0.001 | 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".