Effects of Planting, Vegetation Management, and Pre-Commercial Thinning on the Growth and Yield of Lodgepole Pine Regenerated after Harvesting in Alberta, Canada
Bibliographic record
Abstract
A large long-term field trial was established in the Upper and Lower Foothills sub-regions of the Canadian boreal forest to monitor the effects of planting, vegetation management, and pre-commercial thinning on the development of lodgepole pine stands following harvesting. Data collected at the end of the trial’s regeneration phase, 17 to 20 years after its establishment, were tested for treatment effects and projected to rotation age. Planting generally improved stocking and increased projected growth and yield of lodgepole pine. On modal sites, planted trees were often greatly outnumbered by natural regeneration; however, on others, typically with either poorer or richer soils, satisfactory restocking was not achieved without planting. Control of competing vegetation by herbicide application facilitated regeneration of pine where it was otherwise difficult or impossible on sites with excessive herbaceous or hardwood competition. Pre-commercial thinning accelerated the growth of individual trees and was projected to shorten rotations in dense stands. Responses to the treatments varied depending on environmental factors. Particular treatments may be effective to meet management objectives under some site conditions but unnecessary or counterproductive elsewhere.
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 | 0.001 | 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 | 0.000 | 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".