Soil phosphorus fractions of two contrasting temperate acidic soils receiving forest-derived liming by-products
Bibliographic record
Abstract
Soil acidification, a major issue responsible for cropland degradation, can be efficiently addressed by forest-derived alkaline residues. However, indirect effect of these by-products on phosphorus (P) forms and their availability to crops is not well recognized in temperate acidic soils. Using the Hedley fractionation procedure, a study was conducted to characterize the P forms, after a 40-week laboratory incubation, of a gleyed clay and a podzolized sandy loam soils, each receiving six different forest materials and a calcitic lime. Lime mud, two types of wood ash (papermill biosolids and wood bark), two biochars (maple and pine), and a de-inking paper sludge were applied at a CaCO 3 equivalence-based rate to achieve a target pH of 6.5 in each soil. Results indicated that all liming materials decreased organic P (Po) in both soils. However, the inorganic P (Pi) fractions reacted differently depending on soil. For the clay, there was a shift of P from organic pools (NaHCO 3 -Po and NaOH-Po) and NaOH-Pi toward NaHCO 3 -Pi, an available P form for crops. For the sandy loam, P from organic pools and NaHCO 3 -Pi moved toward stable pools (HCl-P + residual P), mostly associated with Ca. This redistribution of P was largely associated with the soil pH increases. Apart from pH, wood ash also contributed to increase soil total Pi owing to their P content. By contrast, pine biochar had minimal effect on soil P fractions. We conclude that addition of forest alkaline residues to cropland improved soil pH and also modified the P availability to plants.
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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".