A hillslope forest floor (duff) water budget and the transition to local control
Bibliographic record
Abstract
Abstract The partially decomposed organic layer (duff: F and H layers) of the forest floor is an important boundary between the soil and atmospheric processes. Here we use both empirical data and a three‐dimensional coupled heat and water budget model to explain the duff hydrological hillslope shift between very brief wet periods when lateral flow in the duff and infiltration into the mineral soil occur and dry periods when evaporative flow dominates and both lateral and mineral soil flow are not important. The duff moisture transitions from wet to dry periods were the result of low lateral flow which moves liquid and water vapour only centimetres to metres, very rapidly and mostly in the H layer immediately after precipitation. During wet periods, the net lateral fluxes were negative on divergent areas and positive on convergent areas of the hillslope, leading to a net moisture loss in divergent areas and a net gain in convergent areas. The response to lateral flow in the H layer was more rapid than in the F layer. The transition from the lateral downwards flow to mineral soil to evaporative control was within approximately 48 h of precipitation. Canopy species and aspect were important with lodgepole pine, southwest aspect and 4‐cm deep duff controlled by evaporative processes while Engelmann spruce, northeast aspect and 30‐cm duff were more controlled by hillslope redistribution processes. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.000 | 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 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".