Beneficial influence of plant neighbours on tree growth in drained forested peatlands: a case study
Bibliographic record
Abstract
In boreal forest, drainage can be successfully used to lower the water-table level of postharvest forested peatland stands suffering from watering-up. The later vegetation revival and growth is suspected to gradually create a water-table drawdown described in this study as biological drainage. Its effect on the annual stump diameter increment of planted eastern larch (Larix laricina (Du Roi) K. Koch) and naturally regenerated black spruce (Picea mariana (Mill.) BSP) was studied on a postharvested and drained forested peatland located in eastern part of the Canadian boreal forest. A factor describing the neighbourhood occupancy of every subject tree was used to illustrate biological drainage in a retrospective growth analysis. Results showed the dual effect of the neighbourhood occupancy factor: competing situations close to the ditch and growth-favouring situations farther from it. In the latter case, the studied trees demonstrated better growth with moderately increasing neighbourhood occupancy. This was interpreted as evidence of the beneficial effect of biological drainage on tree growth. The presence of speckled alder (Alnus incana subsp.rugosa (Du Roi) J. Clausen) in the neighbourhood of selected trees corresponded to improved growth for both studied species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".