Tree-based intercropping may reduce, while fertilizer nitrate may increase, soil methane emissions
Bibliographic record
Abstract
Tree-based intercropping (TBI) systems have shown some promise in mitigating greenhouse gas emissions, such as by sequestering carbon and decreasing soil nitrous oxide emissions. However, the effects of TBI on soil methane fluxes remain unknown. In a field study, we failed to show differences in soil CH4 production between TBI and conventional monocropping (CM) systems. Within TBI plots, however, we found significantly lower CH4 concentrations near the middle of the alleys than closer to tree rows. Soil CH4 concentrations also decreased with soil depth, even dipping below mean global atmospheric concentrations. Laboratory assays revealed a higher CH4 oxidation potential in soils collected from TBI plots compared with CM plots. These assays also revealed a decrease in CH4 oxidation potential after soils were amended with nitrate. We conclude that TBI could potentially reduce soil CH4 emissions, whereas fertilizer nitrate may increase them.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".