Relationship between Manure Management Application Practices and Phosphorus and Nitrogen Export in Snowmelt Run-off Water from a Black Chernozem Saskatchewan Soil
Bibliographic record
Abstract
In Saskatchewan, soil nutrients released from land-applied solid cattle manure (SCM) and liquid hog manure (LHM) could be subject to off-field export via spring surface run-off water and/or subsurface leaching from melting snow. The objective of this study was to determine how the placement of SCM and LHM using surface and subsurface application methods affects the amounts of soluble reactive phosphorus (SRP), nitrate-nitrogen (NO3-N) and ammonium nitrogen (NH4-N) exported in simulated snowmelt run-off. Intact soil slabs were collected post-harvest in Oct. 2008 and Oct. 2009 from an annually cropped Black Chernozem in east-central Saskatchewan having treatments of: 1) a control, with no SCM or urea fertilizer added and 2) SCM applied at a rate of 60.6 t ha-1 for 2 years as: surface broadcast, broadcast and incorporated and subsurface banded. For comparison purposes, intact soil slab monoliths were collected post-harvest in Oct. 2009 from an annually cropped Black Chernozem in east-central Saskatchewan having treatments of: 1) a control, with no LHM or urea fertilizer added; 2) LHM broadcast and incorporated at a rate of 37,000 L ha-1 for 12 years; and 3) LHM subsurface banded at rates of 37,000 L ha-1 and 148,000 L ha-1 for 12 years. Run-off water and leachate were collected under two different simulated prairie spring melt conditions: 1) thawing soil slabs containing snow that slowly melted on the surface; and 2) frozen soil slabs with run-off water applied to the surface and allowed to run-off across the frozen soil surface. Export of SRP in the thawing soil slabs that had SCM applied in subsurface bands was 0.51 kg P ha-1 and was significantly higher than the non-manured control (0.07 kg P ha-1). Dissolved NO3-N exported in water running across the frozen soil slabs was highest in the broadcast and incorporated treatment (0.30 kg N ha-1). All SCM manured treatments had higher export of nitrate (0.2-0.25 kg NO3-N ha-1) compared to the non-manured control (0.07 kg ha-1). There was no significant (P ≤ 0.10) effect of placement method on SRP, NO3-N and NH4-N export on thawing or frozen SCM soil slabs. Export of SRP was less in LHM treatments than SCM treatments. In thawing soil slabs with 148,000 L ha-1 LHM treatment, the P export was 0.05 kg P ha-1 and was greater than the control treatment (0.01 kg ha-1). Rate of application and manure type appears to be more important than method of placement in influencing P and N transport in melt water on these soils.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".