Atmospheric impact of nitrous oxide uptake by boreal forest soils can be comparable to that of methane uptake
Bibliographic record
Abstract
Abstract Aims Environmental factors controlling nitrous oxide (N 2 O) uptake in forest soils are poorly known, and the atmospheric impact of the forest N 2 O sink is not well constrained compared to that of methane (CH 4 ). Methods We compared nitrous oxide (N 2 O) and CH 4 fluxes over two growing seasons in boreal forest soils located in Eastern Finland. Within a spruce forest, we compared plots with long-term nitrogen (N) fertilization history and non-fertilized plots, and additionally pine forest plots without a fertilization history. The flux data was complemented with measurements of climatic conditions and soil physical and chemical characteristics, in order to identify factors affecting N 2 O and CH 4 fluxes. Results Non-fertilized spruce forest soils showed the highest cumulative N 2 O uptake among the sites, whereas the pine forest site displayed low cumulative N 2 O emission. Nitrous oxide uptake was favored by high soil silt and water content. The low temperature seasons, spring and autumn, had the highest N 2 O uptake, likely associated with high soil water content typical for these seasons. In the spruce forest the N 2 O uptake was seasonally decoupled from the CH 4 uptake. Conclusions Applying the Global Warming Potential (GWP) approach, the cooling effect of N 2 O uptake in the spruce forest was on average 35% of that of CH 4 uptake showing that N 2 O uptake should be considered when evaluating the atmospheric impact of boreal forests.
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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) | 0.001 | 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) | 0.001 | 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".