Near-surface permafrost studies near Bethel and remotely sensing ice wedge networks across the Yukon Kuskokwim Delta, Alaska 2025
Bibliographic record
Abstract
This dataset documents the occurrence, distribution, and characteristics of cryptic ice wedge networks in the Yukon-Kuskokwim Delta (YKD), Alaska. The dataset is derived from remote sensing analyses, field-based permafrost coring, ground-penetrating radar (GPR) surveys, and stable water isotope analyses. High-resolution aerial orthoimagery from 2018 enabled the identification of ~50 linear kilometers (km) of ice wedge trough networks within a 60 square kilometers (km²) study area near Bethel, Alaska, revealing ice wedge networks previously undocumented in the region. Fieldwork in 2023 and 2024 confirmed the presence of ice wedges up to 1.5 meter (m) wide and 2.5 m tall, with wedge tops averaging 0.9 m below the surface. GPR transects identified additional ice wedges beyond those visible in imagery, suggesting that remote sensing analyses may underestimate their true abundance. Coring of polygon centers revealed a suite of late-Quaternary deposits, including early Holocene peat, ice-rich late-Pleistocene permafrost (reworked Yedoma), charcoal layers indicating past tundra fires, and the Aniakchak CFE II tephra (~3,600 calendar years before present [cal yrs BP]). Stable water isotope analyses of wedge ice (mean δ¹⁸O = -15.7 ‰, δ²H = -113.1 ‰) indicate relatively enriched values compared to other Holocene ice wedges in Alaska, reflecting the region's warm maritime climate influence. Expanding the mapping analysis across the YKD using very high-resolution satellite imagery, we found that 95 % of observed ice wedge networks occur at elevations between 4 and 80 meters above sea level (m asl), predominantly within tundra vegetation classes. These areas, covering ~32 % of the YKD tundra region, may contain additional ice wedges, peat deposits, and relict Yedoma. This dataset provides a new framework for understanding the spatial distribution and environmental controls on ice wedge development in warm permafrost regions, with implications for permafrost resilience, climate change vulnerability, and land use planning in the YKD.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".