Wet‐dry cycles control the emissions and sources of greenhouse gases in agricultural soil: An incubation study
Bibliographic record
Abstract
Abstract This study examines the impact of wet‐drying cycles and nitrogen (N) fertilization on soil greenhouse gas fluxes, specifically nitrous oxide (N 2 O) and carbon dioxide (CO 2 ). Nine treatments were tested, combining three soil moisture regimes (55% constant, 55%–30% cycle, and 80%–55% cycle) with three N addition rates (0, 100, and 150 kg N ha −1 ) using 15 N‐labeled urea. Soil samples from a potato ( Solanum tuberosum ) field in Lethbridge, Alberta, were incubated for 28 days under controlled conditions. Wet‐drying cycles involved initially wetting the soil to the upper threshold (55% or 80% WFPS) and allowing it to dry to the lower threshold (30% or 55% WFPS), followed by rewetting to restore upper moisture levels. N 2 O and CO 2 fluxes were measured regularly using a recirculation chamber system to quantify gas emissions and determine N 2 O sources. Soil moisture significantly increased N 2 O and CO 2 production ( p < 0.001), with the highest emissions under wet conditions (80%–55% WFPS cycle), moderate production at 55% WFPS, and the lowest under dry conditions (30%–55% WFPS cycle). Compared to constant 55% WFPS, N 2 O and CO 2 production were 33% and 403% higher, respectively, under wet conditions and 28% and 3% lower under dry conditions. Rewetting events triggered temporary increases in gas emissions due to enhanced microbial activity. Urea addition caused a stronger priming effect on N 2 O production under wet conditions, with urea‐derived N 2 O more prominent in wetter soils.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".