Ground Temperatures and Permafrost Warming from Forest to Tundra, Tuktoyaktuk Coastlands and Anderson Plain, NWT, Canada
Bibliographic record
Abstract
Abstract Annual mean ground temperatures ( T g ) decline northward from approximately −3.0°C in the boreal forest to −7.0°C in dwarf‐shrub tundra in the Tuktoyuktuk Coastlands and Anderson Plain, NWT, Canada. The latitudinal decrease in T g from forest to tundra is accompanied by an increase in the range of values measured in the central, tall‐shrub tundra zone. Field measurements from 124 sites across this ecotone indicate that in undisturbed terrain T g may approach 0°C in the forest and −4°C in dwarf‐shrub tundra. The greatest range of local variation in T g (~7°C) was observed in the tall‐shrub transition zone. Undisturbed terrain units with relatively high T g include riparian areas and slopes with drifting snow, saturated soils in polygonal peatlands and areas near lakes. Across the region, the warmest permafrost is associated with disturbances such as thaw slumps, drained lakes, areas burned by wildfires, drilling‐mud sumps and roadsides. Soil saturation following terrain subsidence may increase the latent heat content of the active layer, while increases in snow depth decrease the rate of ground heat loss in autumn and winter. Such disturbances increase freezeback duration and reduce the period of conductive ground cooling, resulting in higher T g and, in some cases, permafrost thaw. The field measurements reported here confirm that minimum T g values in the uppermost 10 m of permafrost have increased by ~2°C since the 1970s. The widespread occurrence of T g above −3°C indicates warm permafrost exists in disturbed and undisturbed settings across the transition from forest to tundra. Copyright © 2017 Government of the Northwest Territories. Permafrost and Periglacial Processes © 2017 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".