Growth of Coniferous Seedlings on a Drained and Mounded Peatland in Central Alberta
Bibliographic record
Abstract
Abstract Artificial reforestation experiments compared survival and growth of five species of coniferous containerized seedlings, and seedling browsing by ungulates on a clearcut, drained, and mounded peatland in the boreal forest. Six to seven growing seasons after planting, 91% of all seedlings had survived. Height and diameter growth in five species were ranked as follows: Siberian latch (Larix sibirica Ledeb.) > lodgepole pine (Pinus contorta var. latifolia Engelm.) > tamarack (Larix laricina [Du Roi] K. Koch) > black spruce (Picea mariana [Mill.] B.S.P.) = white spruce(Picea glauca [Moench] Voss). Overall, tamarack height and diameter growth was twice that of either spruce species. Height and diameter growth of tamarack, black spruce, and white spruce planted in the spring was 65% to 97% greater than that of the more robust seedlings for the same species planted in the fall of the same year. Repeated winter browsing by ungulates did not affect survival and growth of the five species. In an experiment where survival and growth of tamarack and black spruce seedlings planted on the mounds were compared with that of seedlings planted on the flat areas between mounds, there were no differences in survival, height, or root collar diameter growth between the two planting sites. In the event that suitable peatlands are used to augment existing timber supplies, lowering the water table through ditching, combined with mound-planting, is a feasible method of reforesting timber-harvested, boreal wet sites with Siberian latch, lodgepole pine, and white spruce. Tamarack and black spruce, however, survive and grow well on drained peatlands without mound-planting. North. J. Appl. For. 17(2):71-79.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".