Nutrient losses from tile-drained croplands in the winter: Effects of crop cover
Bibliographic record
Abstract
Warmer winters are becoming more common in seasonally snow-covered agricultural landscapes, resulting in a greater proportion of annual nutrient losses occurring in the so-called ‘dormant’ season. This is a particular problem in tile-drained agricultural landscapes, where nutrient-rich soils, limited plant cover and artificial drainage create ideal conditions for winter nutrient export. Winter crop cover can mitigate the extent of nutrient loss, but there are few multi-year studies that contrast nitrogen (N) vs. phosphorus (P) losses in tiles draining different types of winter field covers. To address this gap, we monitored N and P concentrations at 12 tile outlets draining operational fields under the conventional corn ( Zea mays L. )-soybean ( Glycine max L.) -winter wheat ( Triticum L. spp. ) rotation that dominates much of eastern North America. Measurements occurred over a 28-month period (October 2020– April 2023), which included two growing seasons (GS; May-September, inclusive) and three non-growing seasons (NGS; October–April, inclusive). A winter cover crop mixture (including oats, rye, turnip, daikon radish, berseem clover, sunflowers, buckwheat, hairy vetch, sorghum, fava beans, and peas) was included in the rotation following the harvest of winter wheat, which allowed three different types of winter covers (i.e., living but dormant winter wheat vs. corn residue vs. cover crop mixture) to be compared simultaneously over the three NGSs. Unexpectedly, both total N and nitrate-N concentrations were consistently highest in tiles draining dormant winter wheat fields in the NGS, despite winter wheat providing a living soil cover. Similarly, total P (TP) concentrations were unexpectedly high during winter melt events, but only in tiles draining fields planted with mixed cover crops, and consistent increases in TP and total organic carbon and declines in NO 3 -N during these events suggest that bypass flow is occurring in these no-till soils. Our results suggest that winter cover plant selection is important, as different covers had variable effects on N vs. P retention. Information on the effects of different types of winter cover is needed to inform agricultural best management practices for mitigating nutrient losses in the increasingly hydrologically active non-growing season months.
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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 | 0.000 | 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".