Phosphorus Speciation in Calcareous Soils Following Annual Dairy Manure Amendments
Bibliographic record
Abstract
Core Ideas High rates of repeated manure amendment to calcareous soils lead to change in P speciation Soil P species are Ca‐P minerals, P adsorbed on Fe oxides, and organic P compounds After 3 yr of manure amendment, plant‐available P increases in surface and subsurface soils Applying manure to crops may alter P speciation in the soil profile and thus affect its availability for plant uptake and transport to surface waters. The goal of this research was to determine how repeated manure amendments affect P speciation within calcareous soil. Soil samples were collected in 2013, 2014, and 2015 from two depths to analyze differences in P composition following annual applications of 17 Mg ha ‐1 manure, 52 Mg ha ‐1 manure, or NH 4 H 2 PO 4 fertilizer, and control plots (no P). To speciate the soil P, sequential chemical extraction, P K‐edge X‐ray adsorption near‐edge structure (XANES) spectroscopy, 31 P nuclear magnetic resonance spectroscopy, and microprobe element mapping were used. Total P concentration in the manure‐amended soils increased over 3 yr. The highest soil test P concentrations were in the 52 Mg ha ‐1 plots. Most extractable P in the sequential extraction procedure was removed with the most aggressive extractant, suggesting that the predominant form of P is associated with Ca‐P minerals. The XANES results showed that P species were similar among all amendments and years: 54 to 74% Ca‐P minerals (e.g., hydroxyapatite), 25 to 35% adsorbed P, and 0 to 19% organic P (predominantly phytic acid). Despite the poorly soluble Ca‐P species predominating in all soils, soil test P increased in the manure‐amended soils. The P speciation results provide a baseline to compare how long‐term changes affect P availability and will be useful for designing long‐term scenarios in manure‐amended calcareous soils to limit excess soil P that could leach into water.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".