Forest soil biotic communities show few responses to wood ash applications at multiple sites across Canada
Bibliographic record
Abstract
Abstract There is interest in utilizing wood ash as an amendment in forestry operations as a mechanism to return nutrients to soils that are removed during harvesting, with the added benefit of diverting this bioenergy waste material from landfill sites. Existing studies have not arrived at a consensus on what the effects of wood ash amendments are on soil biota. We collected forest soil samples from studies in managed forests across Canada that were amended with wood ash to evaluate the effects on arthropod, bacterial and fungal communities using metabarcoding of F230, 16S, 18S and ITS2 sequences as well as enzyme analyses to assess its effects on soil biotic function. Ash amendment did not result in consistent effects across sites, and those effects that were detected were small. Overall, this study suggests that ash amendment applied to managed forest systems in amounts (up to 20 Mg ha−1) applied across the 8 study sties had little to no detectable effects on soil biotic community structure or function. When effects were detected, they were small, and site-specific. These non-results support the application of wood ash to harvested forest sites to replace macronutrients (e.g., calcium) removed by logging operations, thereby diverting it from landfill sites, and potentially increasing stand productivity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".