Long-term responses of mammalian herbivores to stand thinning and fertilization in young lodgepole pine (<i>Pinus contorta</i>var.<i>latifolia</i>) forest
Bibliographic record
Abstract
Snowshoe hares (Lepus americanus Exrleben, 1777), mule deer (Odocoileus hemionus (Rafinesque, 1817)), and moose (Alces alces (L., 1758)) commonly occur in young coniferous forests. This study was designed to test the hypothesis that large-scale pre-commercial thinning (PCT) and repeated fertilization 15–20 years after the onset of treatments in young lodgepole pine (Pinus contorta var. latifolia Engelm. ex S. Wats.) stands would enhance relative habitat use by hares, deer, and moose compared with unmanaged stands. Study areas were located in south-central British Columbia, Canada. Habitat use was measured by fecal pellet and pellet-group counts. Understory vegetation and coniferous stand structure were measured in all stands. Habitat use by deer and moose was highest in heavily thinned stands, probably due to the higher levels of forage and cover provided by understory shrubs and conifers in thinned stands. Habitat use by snowshoe hares was highest in high-density stands, but also in lower-density (≤1000 stems·ha–1) stands where an increase in understory conifers provided essential cover for hares. Managers should consider the long-term nature of understory development in young stands managed for timber production. Heavy thinning (≤1000 stems·ha–1) will generate suitable understory habitat for these herbivores sooner than conventional PCT at higher stand densities.
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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".