Assessing effects of permafrost thaw on C fluxes based on multiyear modeling across a permafrost thaw gradient at Stordalen, Sweden
Bibliographic record
Abstract
Abstract. Northern peatlands in permafrost regions contain a large amount of organic carbon (C) in the soil. Climate warming and associated permafrost degradation are expected to have significant impacts on the C balance of these ecosystems, but the magnitude is uncertain. We incorporated a permafrost model, Northern Ecosystem Soil Temperature (NEST), into a biogeochemical model, DeNitrification-DeComposition (DNDC), to model C dynamics in high-latitude peatland ecosystems. The enhanced model was applied to assess effects of permafrost thaw on C fluxes of a subarctic peatland at Stordalen, Sweden. DNDC simulated soil freeze–thaw dynamics, net ecosystem exchange of CO2 (NEE), and CH4 fluxes across three typical land cover types, which represent a gradient in the process of ongoing permafrost thaw at Stordalen. Model results were compared with multiyear field measurements, and the validation indicates that DNDC was able to simulate observed differences in seasonal soil thaw, NEE, and CH4 fluxes across the three land cover types. Consistent with the results from field studies, the modeled C fluxes across the permafrost thaw gradient demonstrate that permafrost thaw and the associated changes in soil hydrology and vegetation not only increase net uptake of C from the atmosphere but also increase the annual to decadal radiative forcing impacts on climate due to increased CH4 emissions. This study indicates the potential of utilizing biogeochemical models, such as DNDC, to predict the soil thermal regime in permafrost areas and to investigate impacts of permafrost thaw on ecosystem C fluxes after incorporating a permafrost component into the model framework.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".