Soil Wetness and Traffic Level Effects on Bulk Density and Air‐Filled Porosity of Compacted Boreal Forest Soils
Bibliographic record
Abstract
Soil compaction is a common consequence of forest harvesting that has the potential to affect several soil processes and forest productivity. Our objective was to quantify the relationships between soil trafficking, soil wetness, and soil air‐filled porosity, and the compacted bulk density and air‐filled porosity of 14 boreal forest soils in West‐Central Alberta, Canada. Bulk density and air‐filled porosity were measured on nontrafficked soil and adjacent areas immediately after the site was subjected to 3, 7, and 12 cycles of skidding with mostly wide‐tired skidders. Significant increases in bulk density ( P < 0.05) occurred after three cycles at each site when the soil water potential was higher than −15 kPa; the significant increase occurred to a depth of at least 22 cm. The increase in bulk density became asymptotic between 7 and 12 cycles, but the increases were not significantly different from the bulk density at three cycles. The relationship between air‐filled porosity and trafficking was the inverse of the level of bulk density and trafficking, but the increase in bulk density of wet soil was limited by an air‐filled porosity of about 0.10 m 3 m −3 Soil compaction only occurred when the soils were at or wetter than field capacity, which can easily be measured in the field with a hand‐held tensiometer or alternatively, estimated from a field measure of soil consistence. Managing felling operations to maximize transpiration of trees to reduce soil wetness is an effective tactic to avoid significant soil compaction by these types of equipment in this environment.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".