Phosphorus release from intact soil monoliths of manure amended fields under simulated snowmelt flooding
Bibliographic record
Abstract
Anaerobic conditions developed in soils with flooding can enhance the release of soil phosphorus (P) to overlying water, but little information is available for soils with a long history of manure application. We examined the P release from manure-amended soils under simulated snowmelt flooding. Intact monoliths from manured (solid-swine, SSM or liquid swine, LSM) and unamended (control) field plots were collected from Carman, Manitoba. Monoliths were frozen for seven days, then thawed, flooded and incubated at +4±1 °C. Redox potential, pH, and concentrations of dissolved reactive P (DRP), Ca, Mg, Fe and Mn in pore water and floodwater were determined weekly up to 56 days after flooding (DAF), and then at 84 DAF. Redox potential decreased with DAF with a greater, and more rapid, decrease in SSM (from initial value of ~300 mV to < 0 mV by 84 DAF) compared to LSM and control (~100 mV by 84 DAF). Pore water and floodwater DRP concentrations were significantly greater in manured treatments than the control at all DAFs, and in SSM than LSM for most DAFs. While floodwater DRP concentrations remained relatively stable in the control treatment, concentrations in manured treatments increased substantially from the onset of flooding to 35-42 DAF (3-4-fold increase) and remained relatively stable thereafter. Significantly greater P release from SSM- than LSM-treated monoliths was due to greater input of P, as well as the higher organic matter content in SSM treated soils. These favored the rapid development of anaerobic conditions that further induced P release.
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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) | 0.000 | 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".