Constraints on potential enzyme activities in thermokarst bogs: Implications for the carbon balance of peatlands following thaw
Bibliographic record
Abstract
Northern peatlands store a globally significant amount of soil organic carbon, much of it found in rapidly thawing permafrost. Permafrost thaw in peatlands often leads to the development and expansion of thermokarst bogs, where microbial activity will determine the stability of the carbon storage and the release of greenhouse gases. In this study, we compared potential enzyme activities between young (thawed ~30 years ago) and mature (~200 years) thermokarst bogs, for both shallow and deep peat layers. We found very low potential enzyme activities in deep peat layers, with no differences between the young and mature bogs. Peat quality at depth was found to be highly humified (FTIR analysis) in both the young and mature bogs. This suggests that deep, old peat was largely stable following permafrost thaw, without a rapid pulse of decomposition during the young bog stage. For near-surface peat, we found significantly higher potential enzyme activities in the young bog than in the mature-associated with differences in peat quality derived from different Sphagnum species. A laboratory incubation of near-surface peat showed that differences in potential enzyme activity were primarily influenced by peat type rather than oxygen availability. This suggested that the young bog can have higher rates of near-surface decomposition despite being substantially wetter than the mature bog. Overall, our study shows that peat properties are the dominant constraint on potential enzyme activity and that peatland site development (successional pathways and permafrost history) through its influence on peat type and chemistry is likely to determine peat decomposition following permafrost thaw.
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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 | 0.001 | 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".