A Carbon Source in a Carbon Sink: Carbon Dioxide and Methane Dynamics in Open‐Water Peatland Pools
Bibliographic record
Abstract
Abstract Peatlands store organic carbon available for decomposition and transfer to neighboring water bodies, which can ultimately generate carbon dioxide (CO2) and methane (CH4) emissions. The objective of this study was to clarify the biogeochemical functioning of open‐water peatland pools and their influence on carbon budgets at the ecosystem and global scale. Continuously operated automated equipment and monthly manual measurements were used to describe the CO2 and CH4 dynamics in boreal ombrotrophic peatland pools and porewater (Québec, Canada) over the growing seasons 2019 and 2020. The peat porewater stable carbon isotope ratios (δ13C) for both CO2 (median δ13C‐CO2: −3.8‰) and CH4 (median δ13C‐CH4: −64.30‰) suggested that hydrogenotrophic methanogenesis was the predominant degradation pathway in peat. Open‐water pools were supersaturated in CO2 and CH4 and received most of these dissolved carbon greenhouse gases (C‐GHG) from peat porewater input. Throughout the growing season, higher CO2 concentrations and fluxes in pools were measured when the water table was low—suggesting a steady release of CO2 from deep peat porewater. Higher CH4 ebullition and diffusion occurred in August when bottom water and peat temperatures were the highest. While this study demonstrates that peatland pools are chimneys of CO2 and CH4 stored in peat, it also shows that the C‐GHG concentrations and flux rates in peat pools are comparable to other aquatic systems of the same size. Although peatlands are often considered uniform entities, our study highlights their biogeochemical heterogeneity, which, if considered, substantially influences their net carbon balance with the atmosphere.
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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 | 0.000 |
| 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) | 0.000 | 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".