Wood quality of trembling aspen (Populus tremuloides Michx) and white spruce (Picea glauca (Moench) Voss) in the boreal mixedwood forest
Bibliographic record
Abstract
The boreal forest is the most widespread forest type in Canada, with a large percentage represented by mixedwood forests of white spruce (Picea glauca (Moench) Voss) and trembling aspen (Populus tremuloides Michx). It serves as not only a vast ecological reserve, but also as the supply source for forest-based industries. A better understanding of the interactions between the different species and their affects on productivity and wood quality traits helps create a more efficient industry that better utilizes the available resources, and concurrently preserves as much forest of ecological reserves and societal vistas. In this study, three sites composed of trembling aspen and white spruce, with varying compositions (one composed of mainly aspen, one of mainly spruce, and a mixed site with both species) were compared to determine how the presence of one species affects the growth and wood quality traits of the other. Four main wood quality traits were examined: wood density, microfibril angle (MFA), fibre traits (fibre length, fibre width and fibre coarseness) and cell wall chemistry. Along with site comparisons, social classes were determined for each site in an attempt to provide a more in-depth comparison across sites. Wood density showed very little variation among sites for both species, with only significant variations occurring between social classes. The aspen site showed statistically lower MFAs than the aspen from the mixed site, however, no differences were observed between the spruce from the mixed and spruce sites. Fibre length, width and coarseness were higher in the pure species sites for both trembling aspen and white spruce. In terms of cell wall composition, there were no differences in carbohydrate contents across sites for both species. Lignin content did vary, with the aspen site possessing higher lignin content than the mixed site, while for spruce the spruce site showed a lower lignin content. Overall, the use of social classes did not refine the characterization of site, producing similar results to those obtained when comparing trees by site, regardless of class.
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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 | 0.001 | 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".