Lower wood stiffness in old-growth than in post-cut and post-fire stands indicates forest structure is a key driver of wood properties in black spruce
Bibliographic record
Abstract
Forest fires and logging drive the structure of boreal forest landscapes. According to recent studies, stand origin is a key driver of the variation in wood properties in black spruce (Picea mariana (Mill.) BSP.), although the underlying mechanisms remain to be elucidated. By comparing post-cut, post-fire and old-growth forests, this study aimed to better distinguish the effects of stand structure from those of the seed or layer origin of the trees on wood properties. We conducted comparative analyses based on ecological characteristics of the sites and static bending tests of small, defect-free wood specimens. Black spruce stands with a regular structure established after logging or fire exhibited higher stiffness at a given cambial age than old-growth forests with irregular structures, as well as lower wood density in the first 40 rings near the pith. However, the bending strength was comparable in all three types of forests studied. Differences in wood stiffness among stand types appeared to be driven more by stand structure than by the seed or layer origin of the stems.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".