Growth responses of Abies amabilis advance regeneration to overstory removal, nitrogen fertilization and release from Vaccinium competition
Bibliographic record
Abstract
Abies amabilis advance regeneration may take several years to acclimate to overstory removal, and poor performance has been attributed to unfavorable microclimate, nutrient stress, and competition from ericaceous vegetation. Our objective was to examine potential factors limiting growth of advance regeneration of Abies amabilis on a montane site in coastal British Columbia. In 1996, 72 experimental plots were established at the Montane Alternative Silvicultural Systems site, Vancouver Island, to provide a design with 12 plots within each of 2 replicate blocks of 3 overstory removal treatments [clearcut (CC), shelterwood (SW), green tree retention (GT)]. Two plots within each replicate block were randomly allocated to each level of 3 nitrogen (N) treatments (0, 100, 250 kg ha -1 , applied as urea) x 2 Vaccinium treatments (shoots present or removed). The three overstory removal treatments differed in the amount of solar radiation received beneath the canopy, in the order CC > GT > SW. Three to five growing seasons after treatment, advance regeneration in the GT and CC treatments exposed to >70% incoming solar radiation had the greatest height, stem diameter, and dry weight. N content, new N uptake (inferred from uptake of applied 15 N), and allocation of uptake to new shoots were greatest in the CC followed by the GT and SW treatments. N fertilization had no effect on seedling growth. Removal of Vacciniumshoots increased stem diameter of advance regeneration, and increased new shoot dry weight in the GT treatment. Allocation of N to new shoots was greatest in advance regeneration from plots where Vaccinium was removed.
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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".