Phosphorus and Nitrogen in Runoff after Phosphorus‐ or Nitrogen‐based Manure Applications
Bibliographic record
Abstract
Application of beef cattle () manure based on nitrogen (N) requirements of crops has resulted in elevated concentrations of soil test phosphorus (P) in surface soils, and runoff from this cropland can contribute to eutrophication of surface waters. We conducted a 3-yr field study (2005-2007) on a Lethbridge loam soil cropped to dryland barley () in southern Alberta, Canada to evaluate the effect of annual and triennial P-based and annual N-based feedlot manure on P and N in runoff. The manure was spring applied and incorporated. There was one unamended control plot. A portable rainfall simulator was used to generate runoff in the spring of each year after recent manure incorporation, and the runoff was analyzed for total P, total dissolved P, total particulate P, dissolved reactive P, total N, total dissolved N, total particulate N, NO-N, and NH-N. Annual or triennial P-based application resulted in significantly ( ≤ 0.05) lower (by 50 to 94%) concentrations or loads of mainly dissolved P fractions in runoff for some years compared with annual N-based application, and this was related to lower rates of annual manure P applied. For example, mean dissolved reactive P concentrations in 2006 and 2007 were significantly lower for the annual P-based (0.12-0.20 mg L) than for the annual N-based application (0.24-0.48 mg L), and mean values were significantly lower for the triennial P-based (0.06-0.13 mg L) than for the annual N-based application. In contrast, other P fractions in runoff were unaffected by annual P-based application. Our findings suggested no environmental benefit of annual P-based application over triennial P-based application with respect to P and N in runoff. Similar concentrations and loads of N fractions in runoff for the P- and N-based applications indicated that shifting to a P-based application would not significantly influence N in runoff.
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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) | 0.001 | 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".