Modelling the Effects of Climate Change and Disturbance on Permafrost Stability in Northern Organic Soils
Bibliographic record
Abstract
Boreal and arctic regions are predicted to warm faster and more strongly than temperate latitudes. Peatlands in these regions contain large stocks of soil carbon in frozen soil and these may effect a strong positive feedback on climate change. We modelled the predicted effects of climate change and wildfire on permafrost in organic soils using a peatland-specific soil thermal model to simulate soil temperatures. We evaluated the model at a lowland black spruce site in Alaska and a sedge-dominated Canadian arctic fen. We estimated the response of soil temperatures and the active layer thickness (AcLTh) under several climate change scenarios. With surface soil temperatures increased by 4.4 °C−5.4 °C, soil temperatures at 100 cm depth increased by 3.6 °C−4.3 °C, the AcLTh increased by 12−30 cm, the zone of partially thawed soil increased, and the number of thaw days increased by 17−26 %. Wildfire caused AcLTh to increase by 26−48 % in the year following fire; AcLTh differences in 2091−2100 were significant (8 cm) at one site. By 2100, climate change effects on AcLTh were larger than wildfire effects suggesting that persistent temperature increases will have a more substantial effect on permafrost than the transient effects of disturbance.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".