Soil physical property changes at the North American Long-Term Soil Productivity study sites: 1 and 5 years after compaction
Bibliographic record
Abstract
The impact of forest management operations on soil physical properties is important to understand, since management can significantly change site productivity by altering root growth potential, water infiltration and soil erosion, and water and nutrient availability. We studied soil bulk density and strength changes as indicators of soil compaction before harvesting and 1 and 5 years after harvest and site treatment on 12 of the North American Long-Term Soil Productivity sites. Severe soil compaction treatments approached root-limiting bulk densities for each soil texture, while moderate compaction levels were between severe and preharvest values. Immediately after harvesting, soil bulk density on the severely compacted plots ranged from 1% less than to 58% higher than preharvest levels across all sites. Soil compaction increases were noticeable to a depth of 30 cm. After 5 years, bulk density recovery on coarse-textured soils was evident in the surface (010 cm) soil, but recovery was less in the subsoil (1030 cm depth); fine-textured soils exhibited little recovery. When measured as a percentage, initial bulk density increases were greater on fine-textured soils than on coarser-textured soils and were mainly due to higher initial bulk density values in coarse-textured soils. Development of soil monitoring methods applicable to all soil types may not be appropriate, and more site-specific techniques may be needed for soil monitoring after disturbance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".