Effets du drainage sur la croissance et le statut nutritif dun peuplement dépinette noire de structure inéquienne : résultats de 10 ans
Bibliographic record
Abstract
We present the 10-year results of a forest drainage experiment conducted in a pre-mature uneven-aged black spruce (Picea mariana [Mill.] BSP) stand, in Bas-Saint-Laurent, Québec, Canada. The set up included 20, 30, 40, 50 and 60 m ditch spacings, and the data were pooled in three diameter classes, ≤ 4 cm (small stems), 610 cm (medium-size stems) and ≥ 12 cm (large stems), in order to take into account stand structure in the analysis. The diameter growth of large stems (dominant cover, height ~ 812 m) was not improved by drainage. Medium-size stems (intermediate story, ~ 48 m) showed a better growth at a 510 m distance from the ditches, while small stems (understory ~ 14 m) reacted well to drainage, proportionally to ditch closeness. Generally, growth and gain attributable to drainage increased with the live crown ratio, from one third of the total tree height. We did not detect any effect of drainage or distance from the nearest ditch on the nutrient content of the current year foliage of the large stems. For small stems, even the individuals located at 2530 m from the ditches showed a growth increase compared to the control, although the understory did not benefit from full light conditions. Results suggest that drainage aiming at correcting watering-up following harvesting could permit a rapid growth increase of advance growth. Key words: diameter growth, foliar analysis, forest drainage, black spruce, Picea mariana, forested peatland
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".