Growth of Norway spruce seedlings after transplanting into silty soil amended with biochar: a bioassay in a growth chamber
Bibliographic record
Abstract
Biochar (BC), the carbon-rich by-product resulting from pyrolysis of biomass, is used for bioenergy and increasingly as a soil additive for carbon sequestration and soil improvement. However, information about the effects of BC on forest productivity and reforestation success, especially on boreal and temperate forest soils, is scant. We examined the effects of two BC types (Canadian and Finnish) added in proportions up to 60 vol.% into a common alluvial silty soil on the growth of transplanted Norway spruce (Picea abies [L.] Karst.) seedlings in a growth chamber. We found no marked differences in seedling growth among the binary growing media mixes used. Seedling growth attributes (seedling height, terminal shoot growth, root volume) differed consistently only between the BC types in the highest proportion used. The terminal shoot growth differed overall among the two BC types. These results suggest that BC may be applied into mineral soils without detrimental chemical effects on tree plantation success. Our results provide foundation for further field research on the longer-term impacts of adding BCs to boreal forest soils.
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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) | 0.001 | 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 | 0.001 |
| 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".