Distribution of epicormic branches and foliage on Douglas-fir as influenced by adjacent canopy gaps
Bibliographic record
Abstract
The influence of adjacent canopy gaps on spatial distribution of epicormic branches and delayed foliage (originating from dormant buds) was investigated in 65-year-old coastal Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco). Sample trees were selected across a broad range of local densities (adjacent canopy gap sizes) from a repeatedly thinned stand in which gaps had been created 12 years prior to our study. Lengths and stem locations of original and epicormic branches were measured within the south-facing crown quadrant, along with extents to which branches were occupied by sequential (produced in association with terminal bud elongation) and (or) delayed foliage. Epicormic branches, while prevalent throughout crowns, contributed only 10% of total branch length and 2% of total foliage mass. In contrast, delayed foliage occupied over 75% of total branch length, accounted for nearly 39% of total foliage mass, and often overlapped with sequential foliage. Canopy gap size did not influence original or epicormic branch length or location. On original branches, larger gaps may have modestly negatively influenced the relative extent of sequential foliage on branches and (or) slightly positively influenced delayed foliage mass. Delayed foliage appears to contribute substantially to Douglas-fir crown maintenance at this tree age, but canopy gap size had a minor influence, at least in the short term.
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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 | 0.001 | 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) | 0.000 | 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".