Radial Growth Response of Black Spruce Stands Ten Years after Experimental Shelterwoods and Seed-Tree Cuttings in Boreal Forest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Partial cutting is thought to be an alternative to achieve sustainable management in boreal forests. However, the effects of intermediate harvest intensity (45%–80%) on growth remain unknown in black spruce (Picea mariana (Mill.) B.S.P.) stands, one of the most widely distributed boreal species with great commercial interest. In this study, we analysed the effect of three experimental shelterwood and one seed-tree treatments on tree radial growth in even-aged black spruce stands, 10 years after intervention. Our results show that radial growth response 8–10 years after cutting was 41% to 62% higher than in untreated plots, with stand structure, treatment, tree position relative to skidding trails, growth before cutting and time having significant interactions. The stand structure conditioned tree growth after cutting, being doubled in younger and denser stands. Tree spatial position had a pronounced effect on radial growth; trees at the edge of the skidding trails showed twice the increase in growth compared to interior trees. Dominant trees before cutting located close to the skidding trails manifested the highest growth response after cutting. This research suggests that the studied treatments are effective to enhance radial wood production of black spruce especially in younger stands, and that the edge effect must be considered in silvicultural management planning.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it