Establishing Trees on Cut-Over Peatlands in Eastern Canada
Bibliographic record
Abstract
Four major tree-planting trials on cut-over peatlands in eastern Canada were surveyed in 2002, in order to evaluate the potential use of trees in rehabilitation following horticultural peat extraction. At one of the sites, an experiment to determine the appropriate fertilisation rate for trees planted on cut-over peatlands was also conducted over several years. Tree performance was assessed by measuring survival, total height and annual growth of red maple ( Acer rubrum L.), tamarack ( Larix laricina (Du Roi) Koch.), black spruce ( Picea mariana (Mill.) B.S.P.), jack pine ( Pinus banksiana Lamb.) and hybrid poplar ( Populus spp.). Establishment and growth of tamarack and black spruce in cut-over peatlands showed good potential when compared to performance in conventional forestry plantations. Red maple and jack pine gave poor productivity but promising survival, whilst hybrid poplar plantings failed. Adding nutrients was essential for growth but dosages above 122.5 g of 3.4N-8.3P-24.2K per tree gave no further improvement. Therefore, several different tree species can be planted to reclaim cut-over peatlands in eastern Canada, so long as the appropriate species are chosen and nutrients are provided.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".