Phosphorus Losses through Agricultural Tile Drainage in Nova Scotia, Canada
Bibliographic record
Abstract
Tile drainage water from agricultural fields commonly exceeds environmental guidelines for phosphorus (P) in rivers and streams. The loss of P through artificial drainage is spatially and temporally variable, and is related to local factors. This study characterizes variability in total P (TP) and soluble reactive P (SRP) concentrations in weekly drainage samples from 39 agricultural fields in Nova Scotia, Canada, from April 2002 through December 2003. We examined connections between P concentrations and the factors: (i) soil texture; (ii) discharge flow rate; (iii) soil test P (STP); (iv) manure type; and (v) crop cover. Generally, variability between fields and samples was great, and fields with standard deviations exceeding the mean for TP, SRP, and flow rate were 71, 54, and 79%, respectively. It was evident that poultry and swine manure contributed to high STPs, and to constantly high TP concentrations with high proportions of SRP. Concentrations varied from week to week, and particularly in April, May, October, and November when the greatest TP, SRP, and flow rate averages were measured. Mean TP concentrations exceed the USEPA (1994) TP guideline of 0.10 mg L(-1) at 82% of the fields, and periodically concentrations more than 10 times, and occasionally more than 50 times higher than the guideline were found. The proportion of SRP in TP had a tendency to be higher when TP levels were high in coarse textured soils. In Nova Scotia, dairy manure is most often applied on permanent cover crops, which did not show as much P concentration variability as crop rotations. Daily or hourly observation of short-term increases in P concentrations related to the described factors would help to characterize the changes in P concentrations observed during frequent heavy drainage flow events.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".