Phosphorus mobilization in unamended and magnesium sulfate-amended soil monoliths under simulated snowmelt flooding
Bibliographic record
Abstract
Enhanced release of phosphorus (P) from soils with snowmelt flooding poses a threat of eutrophication to waterbodies in cold climatic regions. Reductions in P losses with various soil amendments has been reported, however effectiveness of MgSO4 has not been studied under snowmelt flooding. This study examined (a) the P release enhancement with flooding in relation to initial soil P status and (b) the effectiveness of MgSO4 at two rates in reducing P release to floodwater under simulated snowmelt flooding. Intact soil monoliths were collected from eight agricultural fields from Southern Manitoba, Canada. Unamended and MgSO4 surface-amended monoliths (2.5 and 5.0 Mg ha−1) in triplicates were pre-incubated for 7 days, then flooded and incubated (4 °C) for 56 days. Pore water and floodwater samples collected at 7-day intervals were analyzed for dissolved reactive P (DRP), pH, Ca, Mg, Fe and Mn. Redox potential (Eh) was measured on each day of sampling. Representative soil samples collected from each field were analyzed for Olsen and Mehlich 3-P. Simulated snowmelt flooding enhanced the mobility of soil P with approximately 1.2–1.6 -fold increase in pore water DRP concentration from 0 to 21 days after flooding. Mehlich-3 P content showed a strong relationship with the pore water DRP concentrations suggesting its potential as a predictor of P loss risk during prolonged flooding. Surface application of MgSO4 reduced the P release to pore water and floodwater. The 2.5 Mg ha−1 rate was more effective than the higher rate with a 21–75% reduction in average pore water DRP, across soils. Soil monoliths amended with MgSO4 maintained a higher Eh, and had greater pore water Ca and Mg concentrations, which may have reduced redox-induced P release and favored re-precipitation of P with Ca and Mg, thus decreasing DRP concentrations in pore water and floodwater.
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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 | 0.000 | 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 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".