Peatland degradation reduces methanogens and methane emissions from surface to deep soils
Bibliographic record
Abstract
Peatland degradation is expected to increase the rate of aerobic decomposition in surface soil (0–30 cm). Carbon stored in both the subsurface (30–60 cm) and deeper layers (>60 cm) of peatlands is also expected to be metabolized after degradation. However, little is known about how methane were emissions from subsurface and the deeper layers of peatlands during degradation. Three peatland degradation stages: S1, intact fen with high water table; S2, lightly degraded fen with a fluctuating water table; S3, heavily degraded fen with a lower water table were chosen to quantify the differences in CH4 emissions at different peatland degradation stages. CH4 emissions and methanogens of subsurface and deep soil were also measured to reveal the contribution rates of subsurface methane emission in this study. After four-years experiment, we found that the abundance of methanogens and methane emissions decreased as peatlands were more heavily degraded. We also found that the contribution rate of methane emission decreased from peat surface to subsurface and deep layer, and this trend varied with peatland degradation. A higher contribution rate was found in the subsurface methane emissions from S1 (32.63%) and S2 (19.94%). Importantly, when peatlands were heavily degraded, the subsurface changed from a CH4 source to a sink. Decreased methane emissions of the degraded peatlands was also associated with a high abundance of methanogens (R2 = 0.75, p < 0.05). Thus, we conclude that peatland degradation reduces methanogens and methane emissions from both surface and deep soils. Peatland degradation induced aerobic condition and substrate limitation are the main reasons for the reduced methane emission from Zoige peatland.
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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) | 0.001 | 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".