Impacts of mean annual air temperature change on a regional permafrost probability model for the southern Yukon and northern British Columbia, Canada
Bibliographic record
Abstract
Abstract. Air temperature changes were applied to a regional model of permafrost probability under equilibrium conditions for an area of nearly 0.5 × 106 km2 in the southern Yukon and northwestern British Columbia, Canada. Associated environmental changes, including snow cover and vegetation, were not considered in the modelling. Permafrost extent increases from 58% of the area (present day: 1971–2000) to 76% under a −1 K cooling scenario, whereas warming scenarios decrease the percentage of permafrost area exponentially to 38% (+ 1 K), 24% (+ 2 K), 17% (+ 3 K), 12% (+ 4 K) and 9% (+ 5 K) of the area. The morphology of permafrost gain/loss under these scenarios is controlled by the surface lapse rate (SLR, i.e. air temperature elevation gradient), which varies across the region below treeline. Areas that are maritime exhibit SLRs characteristically similar above and below treeline resulting in low probabilities of permafrost in valley bottoms. When warming scenarios are applied, a loss front moves to upper elevations (simple unidirectional spatial loss). Areas where SLRs are gently negative below treeline and normal above treeline exhibit a loss front moving up-mountain at different rates according to two separate SLRs (complex unidirectional spatial loss). Areas that display high continentally exhibit bidirectional spatial loss in which the loss front moves up-mountain above treeline and down-mountain below treeline. The parts of the region most affected by changes in MAAT (mean annual air temperature) have SLRs close to 0 K km−1 and extensive discontinuous permafrost, whereas the least sensitive in terms of areal loss are sites above the treeline where permafrost presence is strongly elevation dependent.
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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) | 0.002 | 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".