Limited effects of wood ash application on soil aggregate structure in a sandy loam textured soil
Bibliographic record
Abstract
As global demand for reliable renewable energy grows there has been an increase in bioenergy production. One source of bioenergy is the combustion of woody biomass, which creates wood ash. Here, we investigate the effect of adding two different wood ashes (high and low carbon ashes) to soil on the distribution of water stable aggregates in a coarse textured soil, hypothesizing that wood ash would increase aggregate stability and that the ashes would differ in their effect. Surface soils (0–10 cm) were separated into four aggregate-size classes: >2000 µm (large macroaggregates), 250–2000 µm (small macroaggregates), 53–250 µm (microaggregates), and <53 µm (silt and clay). The application of ash did not change the distribution of carbon among the size fractions compared to the control, but it increased the carbon content by 25% and widened the C:N ratio by 5 compared to the control. The application of ash increased the carbon content in the >2000 µm fraction by 64%, the 250–2000 µm fraction by 23%, the 53–250 µm fraction by 27%. There was no effect of ash application on the carbon content in the <53 µm fraction but the C:N narrowed by 5 compared to the control. Increases in the C:N in the size fractions were consistent with ash application. There were limited differences between the high and low carbon ashes with respect to their effect on the size fractions. These results suggest that wood ash can be applied to coarse textured forest soils with no negative effects on the soil structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".