Emergence and survival of <i>Populus tremula </i>seedlings under varying moisture conditions
Bibliographic record
Abstract
Aspen produces large numbers of seeds, even though it mainly reproduces asexually with root suckers. The aim of this study was to find out how different moisture conditions affect emergence and survival of Populus tremula L. seedlings. This was studied with a sowing experiment (totally randomized factorial design). There were altogether 10 blocks, each containing 16 microsites and three treatments (sowing time, watering, sowing shelter) replicated twice in each block. Seedlings emerged on 56% of microsites. Sowing time affected seedling emergence. Both the proportion of microsites with seedlings and the number of seedlings per microsite were lower after first than after second sowing, when the weather was rainier. Watering increased the number of seedlings per microsite, but the proportion of micro sites with at least one seedling was not affected. Sowing shelter had a negative effect on the seedling emergence, especially after second sowing. The survival of seedlings was low (10%) and strongly dependent on watering. The effect of block and its interactions with treatments indicated that seedling emergence and survival depended also on seedbed conditions. We conclude that sexual reproduction of aspen may occur in nature, but it is rare. The seeds also maintained their germinability longer than earlier observed.
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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 | 0.000 | 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".