Use of a Process‐Based Model to Predict Nitrous Oxide Emissions From Intensive Crop Production Under a Changing Climate
Bibliographic record
Abstract
ABSTRACT In cold temperate regions, nongrowing season (November‐April) nitrous oxide (N 2 O) emissions from croplands can be substantial, particularly during the rapid freeze‐thaw cycles of the late winter‐spring. Despite their potential environmental impact, the extent and underlying climatic triggers of these emissions remain poorly understood. Using the Denitrification and Decomposition (DNDC) model, N 2 O fluxes and climatic triggers of N 2 O emissions were assessed by simulating historical (1990–2019) and 30‐year future (2038–2067) winter and early spring emissions under intensive grain corn production in Southern Quebec. In the historical period, mean winter N 2 O emissions were greatest in warm‐wet years, and increased over the years as the snow‐water equivalent (SWE) declined. Future scenario simulations predict a 10% increase in winter/spring N 2 O emissions, driven by a 1°C rise in winter soil temperature and an 8% increase in water‐filled pore space (WFPS). SWE is also expected to decrease by 1 mm annually. These shifts suggest a substantial increase in future winter N₂O emissions, highlighting the urgency of developing mitigation strategies for agricultural soils.
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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".