Skidder Traffic Effects on Water Retention, Pore‐Size Distribution, and van Genuchten Parameters of Boreal Forest Soils
Bibliographic record
Abstract
Compaction by harvesting equipment has a potential to decrease the quality of root environment through alteration of soil pore space. Effects of skidder traffic on soil water retention and pore‐size distribution were studied on medium‐textured Inseptic and Oxyaquic Haplocryalfs, and Typic Dystrocryepts at 14 sites in Alberta foothill and boreal forests. Treatments included 3, 7, and 12 cycles by skidders equipped mostly with wide tires. Soil cores were collected at four random points of each treatment at an average depth of 5 and 10 cm. Soil water content of each core was measured at six potentials. Tempe cells were used to measure water retention at potentials from −2 to −30 kPa; a conventional pressure plate was used in the range of −100 to −1500 kPa. The four‐parameter water retention function developed by van Genuchten (1980) was fitted to the data. The pore space of trafficked soil was not significantly affected when soil was drier than field capacity. At higher soil water contents, the first few skidding cycles caused a decrease in θ s and α parameters, which reflected flattening of water retention curves in the high potential range and a simultaneous shift of the steepest part of the slope to a lower potential. The result of compaction was a decrease in air‐filled porosity below 0.10 m 3 m −3 , which restricted aeration without changing field capacity or available water holding capacity. Most modifications of soil pore space by wide‐tired skidders can be avoided if the soils are drier than field capacity.
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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 | 0.001 | 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".