Effects of winter pulsed warming and snowmelt on soil nitrogen cycling in agricultural soils: A lysimeter study
Bibliographic record
Abstract
In cold regions, climate change is expected to result in warmer winter temperatures and increased temperature variability. Coupled with changing precipitation regimes, these changes can decrease soil insulation by reducing snow cover, exposing soils to colder temperatures and more frequent and extensive soil freezing and thawing. Freeze-thaw events can exert an important control over winter soil processes and the cycling of nitrogen (N), with consequences for soil health, nitrous oxide (N2O) emissions, and nearby water quality. These impacts are especially important for agricultural soils and practices in cold regions. We conducted a lysimeter experiment to assess the effects of winter pulsed warming, soil texture, and snow cover on N cycling in agricultural soils. We monitored the subsurface soil temperature, moisture, and porewater geochemistry together with air temperature, precipitation, and N2O fluxes in four agricultural field-controlled lysimeter systems (surface area of 1 m2 and depth of 1.5 m) at the University of Guelph’s Elora Research Station over one winter (December 2020 to April 2021). The lysimeters featured two soil types (loamy sand and silt loam) which were managed under a corn-soybean-wheat rotation with cover crops. Additionally, ceramic infrared heaters located above two of the lysimeters were turned on after each snowfall event to melt the snow and then turned off to mimic snow-free winter conditions with increased soil freezing. Porewater samples collected from five depths in the lysimeters were analyzed for total dissolved nitrogen (TDN), nitrate (NO3−), nitrite (NO2−), and ammonium (NH4+). N2O fluxes were measured using automated soil gas chambers installed on each lysimeter. The results from the snow removed lysimeters were compared to those of lysimeters without heaters (with snow). As expected, the removal of the insulating snow cover resulted in more intense soil freeze-thaw events, causing increased dissolved N loss from the lysimeter systems as N2O (from the silt loam system) and via NO3− leaching (from the loamy sand system). In the silt loam lysimeter, we attribute the freeze thaw-enhanced N2O fluxes to de novo processes rather than gas build up and release. In the loamy sand lysimeter, we attribute the increased NO3− leaching to the larger pore size and therefore lower water retention capacity of this soil type. Overall, our study illustrates the important role of winter snow cover dynamics and soil freezing in modulating the coupled responses of soil moisture, temperature, and N cycling.
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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 | 0.000 |
| 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 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".