Greenhouse gas production potential and associated degradation of organic carbon in warming permafrost – an incubation experiment coupled to biomarker analyses from drained lake basin sediments on the Yukon Coastal Plain, Canada
Bibliographic record
Abstract
Permafrost carbon pools are vulnerable to a warming climate and bear the potential to alter the terrestrial carbon cycle. In the extensive drained lake basin wetlands that cover Arctic lowlands, enhanced degradation of organic-rich deposits upon permafrost thaw could lead to greenhouse gas emissions to the atmosphere. This study investigates processes and intensity of organic matter decomposition and associated potential greenhouse gas production in thawed sediment from drained lake basins on the Yukon Coastal Plain in the western Canadian Arctic. We conducted three-month low temperature (4 °C) incubation experiments, assessing the greenhouse gas production potential in the active layer, transition layer, and permafrost of sediment cores from two adjacent drained lake basins under aerobic and anaerobic conditons. The study was supplemented by comprehensive geochemical and biomarker analyses before and after the incubation experiments. Our findings revealed a higher carbon turnover of up to 2.7 % of the available organic carbon to CO2 under aerobic conditions. Carbon loss from mineral permafrost layers matched that of surface peat samples, whereas nitrogen limitation constrained short term carbon mineralization in pioneer peat layers that accumulated shortly after lake drainage. The GHG production under anaerobic conditions exhibited a high depth-dependency, with permafrost layer samples deviating from the otherwise observed high methanogenesis in active and transition layer samples within the short incubation period. High contributions of the potent greenhouse gas methane of up to 94 % enhanced the climate forcing effect of anaerobic emissions. Consequently, the determined relative climate forcing is higher under anaerobic compared to aerobic conditions in active and transition layers, suggesting that waterlogged conditions within drained lake basins are more unfavorable in the short term. While established degradation proxies C:N, δ13C and CPI did not distinctly trace significant degradation of terrestrial organic matter, we observed major shifts in lipid composition, reflected in increasing concentrations of n-alkanols and n-alkanes.
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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 | 0.001 | 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".