Below ground chemical and microbial community responses of wood ash addition to a hardwood forest in central Ontario
Bibliographic record
Abstract
The use of wood ash as a soil amendment remains restricted in many parts of Canada. To better understand belowground biogeochemical responses to wood ash, soil solution chemistry was measured over 3 years following the application of wood ash (0, 2.5, 5.0, and 7.5 Mg·ha−1) at a hardwood stand in Ontario, after which soil microbial response was assessed using 16S rRNA gene and internal transcribed spacer sequencing. Metal concentrations in the locally sourced wood ash were below provincial regulatory limits. Significant increases in soil solution pH were observed within the forest floor in the first year of the trial, and significant increases in calcium and magnesium were also observed in later years of the trial. Concentrations of most metals in soil water either decreased or exhibited no significant change in response to wood ash. There was an increase in diversity and richness of soil prokaryotic groups in the FH horizon at the highest wood ash treatment that is most likely linked to the large increase in pH. This study indicates that wood ash has a strong ameliorative effect on soil and soil water chemistry without major changes to soil microbial communities and is a viable amendment to forest soils at dosages below 5 Mg·ha−1.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".