Short-term effects of cut-to-length versus full-tree harvesting on conifer regeneration in jack pine, mixedwood, and black spruce forests in Manitoba
Bibliographic record
Abstract
This study compares the effects of full-tree versus cut-to-length forest harvesting methods on tree regeneration in jack pine (Pinus banksiana Lamb.), mixedwood (Picea glauca (Moench) Voss Populus tremuloides Michx. Abies balsamea (L.) Mill.), and black spruce (Picea mariana (Mill.) BSP) sites in southeastern Manitoba, Canada. We surveyed tree regeneration densities, disturbance characteristics, and understorey vegetation in replicated control and harvested plots in each site type preharvest (1993) and 1 and 3 years postharvest (1994, 1996). In jack pine sites, the full-tree harvest method promoted regeneration of Pinus banksiana through increased disturbance of soil and the moss layer, and decreased slash deposition relative to the cut-to-length method. Conversely, in mixedwood sites the cut-to-length method resulted in less damage to advance regeneration and proved better at promoting postharvest regeneration of Abies balsamea and Picea glauca relative to the full-tree method. In black spruce sites, there were few differences in the impact of the two harvesting methods on regeneration of Picea mariana, which increased in frequency and density after both types of harvesting.
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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 | 0.000 | 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) | 0.001 | 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".