Small-mammal response to group-selection silvicultural systems in Engelmann spruce – subalpine fir forests 14 years postharvest
Bibliographic record
Abstract
Concerns about the impacts of clear-cut harvesting on ecosystem components in subalpine forests have generated a variety of alternative silvicultural systems in high-elevation forests in western North America. We examined responses of forest-floor small mammals, 14 years posttreatment, in four replicate units, uncut forest, a 1.0 ha group-selection cut, a large (>30 ha) clearcut, and the edge between the group-selection cut and uncut forest, in the Engelmann Spruce ( Picea engelmannii Parry ex Engelm.) – Subalpine Fir ( Abies lasiocarpa (Hook.) Nutt.) biogeoclimatic zone in south-central British Columbia, Canada. Populations of small mammals were livetrapped during five sessions from June to September 2006. The mean abundance of southern red-backed voles ( Myodes gapperi Vigors) was significantly lower on large clearcuts than in uncut old-growth forests, with intermediate numbers in 1 ha cuts. The opposite trend was found for dusky shrews ( Sorex monticolus Merriam), while there was no significant difference in mean abundance of deer mice ( Peromyscus maniculatus Wagner) among treatments. Trappability, proportion of adult females breeding, and rate of survival of red-backed voles and deer mice were similar among treatments. Our results suggest that group-selection silviculture conducted in subalpine forests may have fewer negative impacts on the small-mammal community than large clearcuts.
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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".