Influence of conifer release treatments on habitat structure and small mammal populations in south-central British Columbia
Bibliographic record
Abstract
I examined the effects of manual cutting and cut-stump applications of glyphosate herbicide on vegetation, woody debris, and small mammal populations in young mixed-conifer plantations of south-central British Columbia, Canada. The experimental design consisted of nine separate and independent plantations: 3 controls, 3 manual treatments, and 3 cut-stump treatments. Treatments were conducted between 21 September and 17 October 1992. Vegetation and woody debris were sampled once within each plantation during the last pre treatment year (1992) and again during the first post-treatment year (1993). Small mammal populations were sampled at three-week intervals within each plantation from September 1991 to October 1993 during snow-free periods. Total volumes of space occupied by herbs, coniferous trees, and woody debris were not affected by manual and cut-stump treatments for conifer release. However, both treatments reduced total volumes of shrubs and deciduous trees. The number of pieces of small diameter woody debris increased following the cutting of competing vegetation and increased the complexity of low ground cover on treated plantations. There were no discernable effects of manual or cut-stump treatments on the population size of deer mice (Peromyscus maniculatus), yellow-pine chipmunks (Tamias amoenus), southern redbacked voles (Clethrionomys gapperi), long-tailed voles (Microtus longicaudus), or meadow voles (M. pennsylvanicus). Sex ratios, body weights, reproduction, recruitment, and survival of deer mice were also similar on treatment and control plantations. Changes in habitat structure during the first post-treatment year did not appear to exceed the tolerance of small mammal populations for early successional change. Continued sampling on these plantations will establish whether there are any long-term treatment effects.
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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 | 0.001 | 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) | 0.001 | 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".