Impact of Aquatic Earthworms on Methane Emission Reduction from the Paddy Field Soil in Japan
Bibliographic record
Abstract
Methane (CH4) is one of the major greenhouse gases that significantly contributes to global warming. Therefore, substantial efforts are being made to reduce CH4 emissions. Paddy fields make a major contribution to atmospheric CH4 concentration because of their anoxic soil environment. Paddy field is habitat of many aquatic earthworms which can play a crucial role in reducing CH4 emissions from paddy field, because their bioturbation activities influence the soil structure and increase oxygen penetration and hence the activity of methanotrophs. Therefore, it was hypothesized that aquatic earthworms may accelerate oxidation of CH4 through their bioturbation activity. This incubation study evaluated the effects of earthworms on the activity of methanotrophs. Soil was incubated with a full factorial combination of two levels of aquatic earthworm (with and without earthworm) and two levels of fertilizer (with and without urea) for 35 days. The addition of urea increased the earthworm density in paddy soil by nearly doubled of without urea. At 28 days after incubation (DAI) the CH4 flux decreased from 2055 mg m-2 h-1 in only urea received soil to 425 mg m-2 h-1 in soil received both urea and earthworm treatment. Phospholipid fatty acid analysis showed that the presence of aquatic earthworms contributed to an increase in the biomass of methanotrophs. The study implies that aquatic earthworms may play vital role to reduce CH4 emission form paddy fields by creating favorable environment for methanotrophs, even in the soils fertilized with urea.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".