Methanogenic potential of Arctic and Antarctic subglacial environments with contrasting organic carbon sources
Bibliographic record
Abstract
Abstract Subglacial environments are largely anoxic, contain organic carbon ( OC ) overridden by glacier ice during periods of advance, and harbour active microbial communities. This creates favourable conditions for OC degradation via methanogenesis. It has been hypothesized that OC beneath ice sheets is converted to methane ( CH 4 ) and may be released to the atmosphere during retreat. However, there are limited data available to support this contention. Here, we present new data on the abundance, diversity and activity of methanogenic archaea and the amount and character of OC in subglacial sediments from Arctic and Antarctic glacial systems based on different substrate types. We employed long‐term laboratory incubations to quantify the CH 4 production potential in different subglacial settings. Significant numbers of methanogens (up to 7 × 10 4 cells g −1 ) were detected in the samples and clones of Methanomicrobiales and Methanosarcinales were identified in clone libraries. Long lag periods (up to >200 days) were observed before significant CH 4 concentrations were measured. We report order of magnitude differences in rates of CH 4 production (10 1 –10 5 fmol g −1 d −1 ) in different subglacial sediments, reflecting contrasts in the origin of the sediment and the OC character. Hence, we predict that contrasting rates of CH 4 production are likely to occur beneath glaciers and ice sheets that overran different types of substrate. We subsequently estimated the potential for CH 4 production beneath the Laurentide/Inuitian/Cordilleran and Fennoscandian Ice Sheets during a typical 85 ka Quaternary glacial/interglacial cycle. CH 4 production from lacustrine‐derived OC is likely to be an order of magnitude higher (~6.3–27 Pg C) than that from overridden soils (~0.55–0.68 Pg C), possibly due to a difference in lability between lacustrine and soil OC . While representing a fraction of the entire OC pool (~418–610 Pg C), this finding highlights the importance of considering the character of different OC pools when calculating subglacial CH 4 production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".