Midrotation effects of biosolids application on tree growth and wood properties in a<i>Pinus radiata</i>plantation
Bibliographic record
Abstract
Biosolids have been applied to a 1000 ha Pinus radiata D. Don plantation in Nelson, New Zealand, since 1996. A research trial was established in a 6-year-old stand in 1997 with three stocking rates (300, 450, and 600 stems·ha–1), and biosolids were applied at ages 6, 9, and 12 years at three application rates based on total nitrogen loading at each application of 0 (control), 300 (standard), and 600 kg N·ha–1(high). The aim of this study was to evaluate the responses of tree growth rate and wood properties to biosolids application at midrotation. Since the trial was established, tree diameter and volume increment in the biosolids-treated plots have increased markedly. This increase in growth is being maintained at midrotation, with the year 13–14 volume increment being 40% greater in the standard treatment than the control, and 46% greater in the high treatment than the control. The response in growth has occurred across all stockings in the trial, although there has been a tendency for the difference in growth between the standard and high rates to be greater at higher stockings. A small but significant reduction of basic wood density and standing-tree sonic velocity in P. radiata was found in the biosolids treatments. Although the reductions in wood density and stiffness may slightly decrease the average log value in biosolids treated trees, this will be greatly outweighed by the large increase in wood volume.
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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) | 0.001 | 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) | 0.001 | 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".