Growth and nutrition of trembling aspen in harvested black spruce forests in northwestern Québec
Bibliographic record
Abstract
Trembling aspen (Populus tremuloides Michx.) were observed growing along roads far north from the area where it dominates, in sites dominated by black spruce (Picea mariana (Mill.) B.S.P.) forests. This study examined the distribution of aspen at an early development stage and the conditions in which they are growing in a black spruce/feathermoss forest type in northwestern Abitibi, Quebec six years following harvesting. In this region, aspen are appearing in logged and burned areas that had been previously dominated by black spruce. The relationship of aspen growth with Ca availability and mineral soil access is the main focus of the study. Soil and foliar samples from aspen seedlings were collected from roadside, slash and cutover locations during the summer of 2003. Trees were also measured for height and basal diameter. Microsites where aspen was growing and where it was absent were compared to determine whether aspen was associated with specific microsites soil properties. The results suggest that there are differences in the growing conditions for aspen between different locations but that the trees are growing successfully in all of the three location types. In the cutovers, aspen seedlings were consistently found in association with patches of Polytrichum moss. All the sets of data indicate that Ca availability and access to mineral soil are not the main factors influencing the distribution of aspen but that soil pH, or a factor relating to pH, may be important.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".