Evaluating the potential contribution of vegetation as a nutrient source in snowmelt runoff
Bibliographic record
Abstract
Elliott, J. 2013. Evaluating the potential contribution of vegetation as a nutrient source in snowmelt runoff. Can. J. Soil Sci. 93: 435–443. On the Canadian prairies, most nutrient transport to surface waters takes place during snowmelt. The potential for a range of 11 residue types to release nitrogen (N), phosphorus (P) and carbon (C) was assessed by snowmelt simulation. Interactions between soils and residues were measured for two contrasting residues. Samples (taken in late fall) were frozen prior to snowmelt simulations that consisted of three diurnal temperature cycles from −5°C to +9°C followed by a final melt at +5°C. Releases of total and total dissolved P (TP and TDP), total dissolved N (TDN), and dissolved organic C (DOC) during simulated snowmelt were greater from actively growing residues than from crop stubble and were significantly related to plant moisture and nutrient contents. Nutrient release from wheat stubble (WS) was statistically similar to that from the underlying surface soil but releases of P and ammonia (NH 3 ) from winter wheat (WW) were at least four times greater than for the corresponding soil. When combined samples of residue and soil were tested, releases of most nutrients were less than when the residue and soil were tested separately. Potential release of nutrients from vegetation is a factor for consideration in the design of practices to reduce nutrient transport.
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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 | 0.002 | 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 | 0.001 |
| 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".