The responses of black spruce growth to an increased proportion of aspen in mixed stands
Bibliographic record
Abstract
In the southeastern boreal forest of Canada, the presence of mixed stands of black spruce (Picea mariana (Mill.) BSP) and trembling aspen (Populus tremuloides Michx.) growing in similar abiotic conditions offers the opportunity to study the influence of aspen on stand volume and spruce growth. A regression analysis performed on field data from the ministère des Ressources naturelles du Québec showed a significant relationship between the relative basal area of aspen (aspen relative basal area was determined by the ratio of aspen basal area to total basal area of the stand) and the total stand merchantable volume after accounting for stand density. However, the relationship between total black spruce volume and relative basal area of aspen was not significant, implying that the volume gain was, in fact, aspen fibre. The positive effects of aspen on black spruce DBH and height were only present when the proportion of aspen in the stand ranged between 0% and 41% of the total stand basal area. These results suggest that aspen uses a different niche than black spruce. Furthermore, the significant increase in black spruce dominant height along the aspen gradient suggests that aspen enhances soil fertility by its influence on nutrient availability. The management of mixed stands, which make up an important proportion on the landscape, offers an example as to how commercial management of the forest can be in agreement with ecosystem management.
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.
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 | 0.001 |
| 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".