Wood ash as a fertilizer on drained mires growth and foliar nutrients of Scots pine
Bibliographic record
Abstract
The availability of phosphorus (P) and potassium (K) commonly limits tree growth on drained peatlands. The nutritional status and volume growth of Scots pine (Pinus sylvestris L.) after varying doses of wood ash fertilization were investigated in seven field experiments located on deep-peated sites in Finland between latitudes 63°N and 67°N. Needle samples were taken 1420 years after fertilization and trees measured 15 years after fertilization. Annual growth rates and differences in foliar nutrients were analyzed with a two-way ANOVA model. A regression model was used in the analysis of periodic relative volume growth. High doses of wood ash (100265 kg P·ha1, 225450 kg K·ha1) resulted in greater changes in foliar nutrient concentrations and in a stronger growth response than low doses (550 kg P·ha1, 14210 kg K·ha1). Significant increases in needle mass and concentrations of P, K, and B were observed in the ash-fertilized stands, with a good status for these elements 20 years after fertilization. Depending on the ash dose, the mean annual volume growth was 0.51.4 m3·ha1 higher than in the control plots during the 15 year postfertilization period.
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 | 0.000 |
| 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".