Forest soil rehabilitation with tillage and wood waste enhances seedling establishment but not height after 8 years
Bibliographic record
Abstract
We evaluated soil conditions of rehabilitated log landings in the Interior Douglas-fir biogeoclimatic zone of British Columbia during the first 3 years after treatment and the growth of lodgepole pine ( Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) on these log landings over 8 years. Rehabilitation treatments included combinations of tillage and the addition of either stockpiled topsoil or one of three organic amendments: hog fuel, sort-yard waste, and a wood waste – biosolids compost. The woody amendments were either applied as a surface mulch or incorporated into the soil after tillage. Tillage and addition of wood waste reduced soil bulk density and increased carbon content. Daytime soil temperatures in summer were lower under a hog fuel mulch than for the other treatments. The plots receiving hog fuel also had higher soil moisture content. One year after treatment, soil mechanical resistance for untreated soils, and those that were simply tilled, exceeded 2500 kPa for much of the growing season. Plots receiving wood waste had lower mechanical resistance. Use of wood waste in rehabilitation improved soil conditions and contributed to improved survival rates for planted lodgepole pine seedlings. Height growth after 8 years was not significantly affected by the treatments.
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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) | 0.001 | 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".