Effects of snow cover on soil freezing, water movement, and snowmelt infiltration: A paired plot experiment
Bibliographic record
Abstract
A dramatic reduction in soil frost depth has been reported for Hokkaido Island of northern Japan over the last 20 years. Since soil frost strongly affects snowmelt infiltration and runoff, the reduction in frost depth may have altered the water and nutrient cycles in this region. A paired‐plot experiment was conducted in an agricultural field in Tokachi, Hokkaido, to compare the movement of soil water at different frost depths, controlled by manipulating the depth of snow cover. Snow was removed to enhance soil freezing in the treatment plot and was undisturbed in the control plot. The soil froze to a maximum depth of 0.43 m under the treatment plot and 0.11 m under the control plot. During the freezing period, the amount of upward soil water flux toward the freezing front in the treatment plot was more than double that in the control plot. During the snowmelt period, infiltration of meltwater was unimpeded by the thin frozen layer in the control plot, whereas the relatively thick frozen layer in the treatment plot impeded infiltration and generated 63 mm of runoff. These results clearly show that the changes in the timing and thickness of snow cover deposition can cause a dramatic reduction of frost depth and change in the soil water dynamics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".