Evaluating the potential for snowmelt phosphorus losses from perennial forage crops
Bibliographic record
Abstract
Abstract In cold regions, there is concern that losses of P with snowmelt runoff following freeze and thaw of vegetation may be greater from perennial forages relative to annual crops. We evaluate the drivers of P losses with snowmelt runoff over a network of field‐scale small watersheds in Manitoba, Canada, following annual crops (59 site‐years), perennial forage (19 site‐years), or tillage to terminate a forage (4 site‐years). Vegetation type was not significantly related to concentrations of P lost in snowmelt or load ( p > 0.05), and 0–5 cm Olsen‐P in soil was the best predictor of flow‐weighted mean concentrations of total dissolved P ( r 2 = 0.46, p < 0.001) and total P ( r 2 = 0.45, p < 0.001) across the 82 site‐years of data. Sites having a recent (10‐year) land use history without tillage had greater P stratification in the top 5 cm of soil than those with tillage, irrespective of vegetation type ( p < 0.001). Residual variation in snowmelt P concentration and loads were negatively related to water yield and positively related to proportion of soil surface area covered by crop residue (independent of type of residue). Loads of P exported with snowmelt were primarily a function of water yield, and at a similar level of snow water equivalent, perennial forages exhibit lower water yield than annual crop sites. These results suggest that with careful management of soil P, adding perennial plants to crop rotations will not increase losses of P with snowmelt and through impacts on hydrology, reductions in overall loading may occur.
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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".