Cryptic Ice Wedge Networks in Holocene Peat, Yukon‐Kuskokwim Delta, Alaska
Bibliographic record
Abstract
ABSTRACT The Yukon‐Kuskokwim Delta (YKD), covering ~75,000 km 2 of Alaska's discontinuous permafrost zone, has a historic (1902–2023) mean annual air temperature of ~−1°C and was previously thought to lack ice wedge networks. However, our recent investigations near Bethel, Alaska, revealed numerous near‐surface ice wedges. Using 20 cm resolution aerial orthoimagery from 2018, we identified ~50 linear km of ice wedge troughs in a 60 km 2 study area. Fieldwork in 2023 and 2024 confirmed ice wedges up to ~1.5 m wide and ~2.5 m in vertical extent, situated on average 0.9 m below the tundra surface ( n = 29). Ground‐penetrating radar (GPR) detected additional ice wedges beyond those visible in the remote sensing imagery, suggesting an underestimation of their true abundance. Coring of polygonal centers revealed late‐Quaternary deposits, including thick early Holocene peat, late‐Pleistocene ice‐rich silts (reworked Yedoma), charcoal layers from tundra fires, and the Aniakchak CFE II tephra (~3600 cal yrs BP). Stable water isotopes from Bethel's wedge ice (mean δ 18 O = −15.7 ‰, δ 2 H = −113.1 ‰) indicate a relatively enriched signature compared to other Holocene ice wedges in Alaska, likely due to warmer temperatures and maritime influences. Expanding our mapping across the YKD using high‐resolution satellite imagery from 2012 to 2024, we estimate that the Holocene ice wedge zone encompasses ~30% of the YKD tundra region. Our findings demonstrate that ice wedge networks are more widespread across the YKD than previously recognized, emphasizing both the resilience and vulnerability of the region's warm, ice‐rich permafrost. These insights are crucial for understanding permafrost responses to climate change and assessing agricultural potential and development in the region.
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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 | 0.001 |
| 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) | 0.001 | 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 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".