Impacts of Degrading Ice‐Wedges on Ground Temperatures in a High Arctic Polar Desert System
Bibliographic record
Abstract
Abstract Ice‐wedge ice is the most widespread type of massive ice found in the continuous permafrost zone. Polygonal networks of ice‐wedges drive environmental changes and feedback that will likely be exacerbated with future climate change. Recent decadal‐scale observations have shown that ice‐wedges are degrading rapidly within the entire Circum‐Arctic Region but observations of feedback associated with ground temperature regimes are still lacking in many areas. We present over a year's worth of field observations from an area with cold (−16.5°C), thick (>500 m) continuous permafrost and a mean annual air temperature of −19.7°C in the Canadian high Arctic. Topographic surveys, thaw depths, vegetation cover, soil moisture, and annual shallow (12 cm) ground temperature measurements were collected for seven ice‐wedge troughs and two polygon centers in a high‐centered polygon system. We show that geomorphic changes caused by ice‐wedge degradation generate new responses in soil moisture, vegetation cover, and snow distribution that create a mosaic of ground temperatures that range by 5.1°C for mean annual, 2.5°C in summer, and 15.2°C in winter between polygon‐centers and ice‐wedge troughs. Our results show that snow redistribution due to wind induces the cooling of polygon centers, thus promoting new thermal contraction cracking and ice‐wedge formation. We provide an example based on high‐resolution remote sensing data on how these ice‐wedge trough densities vary spatially in our study area. Capturing these fine scale geomorphic differences and resulting ground temperatures will be critical to accurately assess future changes of these common Arctic landscapes.
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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 | 0.001 | 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) | 0.000 | 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".