Permafrost Causes Unique Fine‐Scale Spatial Variability Across Tundra Soils
Bibliographic record
Abstract
Abstract Spatial analysis in earth sciences is often based on the concept of spatial autocorrelation, expressed by W. Tobler as the first law of geography: “everything is related to everything else, but near things are more related than distant things." Here, we show that subsurface soil properties in permafrost tundra terrain exhibit tremendous spatial variability. We describe the subsurface variability of soil organic carbon (SOC) and ground ice content from the centimeter to the landscape scale in three typical tundra terrain types common across the Arctic region. At the soil pedon scale , that is, from centimeters to 1–2 m, variability is caused by cryoturbation and affected by tussocks, hummocks and nonsorted circles. At the terrain scale , from meters to tens of meters, variability is caused by different generations of ice‐wedges. Variability at the landscape scale , that is, ranging hundreds of meters, is associated with geomorphic disturbances and catenary shifts. The co‐occurrence and overlap of different processes and landforms creates a spatial structure unique to permafrost environments. The coefficient of variation of SOC at the pedon scale (21%–73%) exceeds that found at terrain (17%–66%) and even landscape scale (24%–67%). Such high values for spatial variation are otherwise found at regional to continental scale. Clearly, permafrost soils do not conform to Tobler's law, but are among the most variable soils on Earth. This needs to be accounted for in mapping and predictions of the permafrost carbon feedbacks through various ecosystem processes. We conclude that scale deserves special attention in permafrost regions.
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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) | 0.010 | 0.001 |
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".