Use of Wood Waste in Rehabilitation of Landings Constructed on Fine-Textured Soils, Central Interior British Columbia, Canada
Bibliographic record
Abstract
Abstract Rehabilitation of temporary landings and roads constructed on fine-textured Alfisols must ameliorate poor soil structure, high bulk densities, and greatly reduced organic matter. A long-term field experiment in the central interior of British Columbia (BC) was begun in 1995 to compare soil properties and seedling growth on landings rehabilitated with three operationally feasible treatments: (1) incorporation of waste wood chips (140 t/ha, oven-dry basis), supplemented with 600 kg N/ha; (2) subsoiling; and (3) shallow tillage combined with recovery and spreading of topsoil. After 4 years, soil bulk density at 7–14 cm depth was lowest in the chip incorporation treatment. Although total C, N, and S, and mineralizable N concentrations were highest in the topsoil recovery treatment, the chip incorporation treatment had the highest 3-year growth rates of hybrid white spruce (Picea glauca × engelmannii). Foliar analyses indicated that macro- and micronutrient concentrations were generally adequate, with only S and Mg being of concern. Establishment of paper birch (Betula papyrifera) did not succeed due to severe rodent damage to seedlings, perhaps encouraged by rapid and dense revegetation by seeded agronomic legumes. Silviculturists should consider treatments involving incorporation of chipped wood wastes, with appropriate supplementary N fertilization, in rehabilitation of access structures on fine-textured soils in the BC central interior. West. J. Appl. For. 19(3):175–183.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".