Hydraulic properties of Orthic Gray Luvisolic soils and impact of winter logging
Bibliographic record
Abstract
Runoff as overland flow and interflow from hillslopes on the Boreal Plain Ecozone of North America is likely to depend on near-surface hydraulic properties. Hydraulic properties were examined in Orthic Gray Luvisolic soil profiles in Alberta, Canada, over several years following clear-cut winter logging and contrasted to those in adjacent forested areas. Infiltration characteristics were determined with double ring infiltrometers at both logged and forested sites. Saturated hydraulic conductivity (Ksat) of Ae and Bt horizons was measured in logged areas with undisturbed Uhland core samples. Infiltration parameters derived by the Kostiakov equation suggest that initial infiltration rates are higher at forested sites than logged. Steady-state infiltration was greater under forest. Vertical Ksat of the Ae was less than the Bt horizon, and horizontal Ksat of the Ae horizon exceeded vertical, indicating anisotropy. Compaction and soil swelling resulting from increased soil water content after logging probably reduced macro-porosity and lowered infiltration capacity. Similarity of Ksat between Ae and Bt horizons in logged areas may have reflected compaction. Logging then may temporarily increase the potential for overland flow but may reduce interflow through Ae horizons until time restores soil hydraulic characteristics to that of an older forest. Key words: infiltration, hydraulic conductivity, Gray Luvisolic.
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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) | 0.000 | 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".