A hotspot of CH4 emission in a Danish agricultural soil: A soft spot in our knowledge?
Bibliographic record
Abstract
Danish agricultural ecosystems are one of the main contributors to the total anthropogenic emissions of greenhouse gases in Denmark. The main research focus on greenhouse gas emissions from mineral agricultural soils has been on N2O, and on how the N2O emissions respond to fertilizer addition and different agricultural practices. Studies on CH4 fluxes are scarce and mostly show a small uptake of CH4, indicating that oxidation of CH4 is dominant in agricultural soils. As part of the NATEF (National emission factors for nitrous oxide from nitrogen fertilizers and crop rotations) project, we have established a field experiment in Taastrup, Denmark. The experiment has been running since early 2019, and consists of 12 plots (4 rotation treatments × 3 blocks) that each are managed following a common Danish crop rotation (main crops: spring barley, winter wheat and oilseed rape) in addition to cover crops (oat, phacelia, oilseed radish) following winter wheat. The field experiment is one of four identical field experiments located across Denmark, thereby capturing the variation in climate and soil types seen in Denmark. The main aim of the project is to determine emission factors for nitrous oxide for Danish cropping systems. This is achieved by regular manual measurements of N2O, CH4 and CO2 fluxes by the discrete closed chamber method in all plots. Furthermore, we have deployed an automated flux chamber system (ECO2 FluX, Prenart Equipment) connected to a greenhouse gas analyzer (G2508, Picarro) to provide high-frequency measurements of the fluxes of N2O, CH4 and CO2. In each growing season, two plots were selected and three automated chambers were placed in each plot, totaling six automated chambers in the study. The automated measurements allowed us to examine the high-frequency temporal dynamics in the fluxes, e.g. periods following rain events, freeze-thaw, fertilization or tilling. As expected, we generally observed emissions of N2O across all plots with different crops. CH4 fluxes were slightly negative (i.e. uptake) or close to zero during most periods, indicating that oxidation was the dominant process. However, during the autumn of 2019, we captured CH4 emission by the automated chambers in the plot with oilseed radish, while at the same time, the automated chambers in a plot with winter wheat showed no CH4 emissions. However, spatial variation in emissions were very large indicating that edaphic and topological factors played a major role. Our results show evidence that hotspots of CH4 emissions can occur in Danish agricultural ecosystems that otherwise mostly act as a sink for CH4. We expect that similar hotspots for CH4 emissions could exist in other similar agricultural systems.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".