Effects of green pruning on growth of <i>Pinus radiata</i>
Bibliographic record
Abstract
Pruning of plantation trees is completed to produce knot-free timber and veneer logs, thus increasing the value of the plantation. A long-term study (11 years) was established to investigate the effects of selective pruning on radiata pine (Pinus radiata D. Don) stem growth. The 175 stems selected for the experiment had been pruned to 2.4 m at 6 years of age. At ages 8 and 10, the trees were pruned to 45%, 60%, or 75% of tree height and growth was compared with a control (first lift pruned only). Pruning to 45% of tree height had no effect on growth to age 13 years. Responses to the other treatments were apparent soon after pruning and continued until measurements ceased at 17 years of age. Pruning to 60% or 75% of tree height at second lift reduced diameter increment, and increment decreased as pruning severity increased. There was a further separation of the growth curves following third-lift pruning to 60% or 75% of tree height. The results suggested that maintaining a live crown ratio of 55% would minimize effects of pruning on diameter growth. The effect of severe pruning on diameter increment was greater for subdominant trees than for dominant stems. Pruning had less effect on height than diameter increment, but all treatments involving pruning to 75% of height at third lift resulted in trees that were approximately 10% shorter than unpruned trees at 13 years of age. More severe second-lift pruning resulted in smaller diameter over stubs at the time of third-lift pruning. Second-lift pruning to 60% of total height produced acceptable diameter over stubs. Implications for management are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".