Effects of repeated fertilization in a young spruce stand in central British Columbia
Bibliographic record
Abstract
Sustained growth responses and large reductions in rotation length can be achieved by repeatedly fertilizing young boreal forests. This paper reports the effects of different regimes and frequencies of fertilization on the foliar nutrition and growth of 10-year-old sub-boreal white spruce ( Picea glauca (Moench) Voss) in central British Columbia. Mean stand volume in treatment plots fertilized twice (at 6-year intervals) with N and B (totaling 400 kg N/ha and 3 kg B/ha) was 20 m3/ha (75%) greater than in the unfertilized control at year 12. Significantly larger stand volume gains (34 m3/ha, 128%) were obtained when S (totaling 100 kg S/ha) was added to this treatment. The inclusion of other nutrients (P, K, and Mg) with N, S, and B did not result in further incremental growth gains. When combined with other nutrients, yearly applications of 100–200 kg N/ha (totaling 1600 kg N/ha) produced 74 m3/ha (277%) more volume compared with the unfertilized stand at year 12. The large effects of fertilization on stand growth were accompanied by large increases in leaf area. Results indicate that repeated fertilization of young sub-boreal spruce forests may offer an excellent opportunity to increase fibre yield and reduce rotation length.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".