Advanced regeneration and seedling establishment in small cutblocks in high-elevation sprucefir forest at Sicamous Creek, southern British Columbia
Bibliographic record
Abstract
We examined the potential of natural regeneration for stocking 1-ha patch cuts in high-elevation Engelmann spruce (Picea engelmannii Parry) subalpine fir (Abies lasiocarpa (Hook.) Nutt.) forests. Using the Sicamous Creek Silvicultural Systems site, which was harvested during winter 19941995, we established 1-m2 plots in patch cuts, forest edge, and untreated control forest. We marked and recorded microsite characteristics for all advanced regeneration and new recruits for up to 5 years; over 12 000 individuals were included. Advanced regeneration was abundant and was about one-quarter spruce. Spruce and fir germinants occurred in all years, but numbers varied greatly, with a very large cohort in 1998. Both advanced regeneration and new recruits were concentrated on decaying logs. Mortality of advanced regeneration was high in the patch cuts following harvest, but subsequent survival was good, approaching rates in the untreated forest within 4 years. Survival rates were higher for spruce than fir, but differed little among surface types and microtopographic positions. Survival of new recruits was high, approximately 50% the first year and 70% during the second, and was similar between spruce and fir. If the 1998 cohort has similar survival, the patch cuts could be adequately stocked. Use of natural regeneration, in combination with infill planting, is a viable option for stocking small openings in wet high-elevation forests in southern British Columbia.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".