Release of phosphorus and metal(loid)s from manured soils to floodwater during a laboratory simulation of snowmelt flooding
Bibliographic record
Abstract
Abstract Phosphorus (P) and metal accumulation in manured agricultural soils and subsequent losses to waterways have been extensively studied; however, the magnitudes and the factors governing their losses during spring snowmelt flooding are less known. We examined the P and metal release from long‐term manured soil to floodwater under simulated snowmelt flooding with recent manure additions. Intact soil columns collected from field plots located in Randolph, Southern Manitoba, 2 weeks after liquid swine manure treatments (surface‐applied, injected, or control with no recent manure addition) were flooded and incubated for 8 weeks at 4 ± 1°C to simulate snowmelt conditions. Floodwater (syringe filtered through 0.45 µm) and soil porewater (extracted using Rhizon‐Mom samplers) samples were periodically extracted and analyzed for dissolved reactive phosphorus (DRP), pH, zinc (Zn), manganese (Mn), iron (Fe), magnesium (Mg), calcium (Ca), and arsenic (As). Mean floodwater DRP concentrations (mg L −1 ) for manure injected (2.0 ± 0.26), surface‐applied (2.6 ± 0.26), and control (2.2 ± 0.26) treatments did not differ significantly. Despite manure application, DRP loss to floodwater did not significantly increase compared to the control, possibly due to the elevated residual soil P at this site from the long‐term manure use. At the end of simulated flooding, the DRP concentrations increased by 1.5‐fold and 5‐fold in porewater and floodwater, respectively. Metal(loid) concentrations were not affected by manure treatments in general, except for Zn and Mg on certain days. Unlike DRP, where porewater and floodwater concentrations increased with time, metalloid concentration in porewater and floodwater did not show consistent trends with flooding time.
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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 | 0.001 | 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".