Alum and Gypsum Amendments Decrease Phosphorus Losses from Soil Monoliths to Overlying Floodwater under Simulated Snowmelt Flooding
Bibliographic record
Abstract
Phosphorus (P) loss from soils poses a threat of eutrophication to downstream waterbodies. Alum (Al2(SO4)3·18H2O) and gypsum (CaSO4·2H2O) are effective in reducing P loss from soils; however, knowledge on their effectiveness under cold temperatures is limited. This study examined the reduction of P loss from soils with alum and gypsum amendment under simulated snowmelt flooding. Intact soil monoliths (15 cm depth) collected from eight agricultural fields in flood-prone areas of Manitoba, Canada, were surface amended with alum or gypsum, pre-incubated for 2 weeks, then flooded and incubated at 4 °C for 8 weeks. Porewater and floodwater samples collected weekly were analyzed for dissolved reactive P (DRP), dominant cations and anions. An enhanced P release with flooding time was observed in all soils whether amended or unamended; however, alum/gypsum amendment reduced DRP concentrations in porewater and floodwater in general, with alum showing a more consistent effect across soils. The reduction in floodwater DRP concentrations (maximum DRP concentration during flooding) with alum and gypsum ranged from 34–90% and 1–66%, respectively. Based on Visual MINTEQ thermodynamic model predictions, precipitation of P and formation of P-sorbing mineral species with alum and gypsum amendment reduced DRP concentrations at latter stages of flooding.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".