Effect of vegetation control, harvest intensity, and soil disturbance on 20-year jack pine stand development
Bibliographic record
Abstract
Currently, there are uncertainties regarding the impacts and (or) efficacy of biomass harvesting and silvicultural practices on stand production on coarse-textured boreal soils. Replicated factorial field experiments examining effects of complete vegetation control (repeated glyphosate application) following operational stem-only harvest with disc trenching (SOT), operational whole-tree harvest with (WTT) and without (WT) disc trenching, and whole-tree harvest with complete forest floor removal by blading (WTB) and blading followed by compaction (WTBC) were installed on four sandy northern Ontario jack pine (Pinus banksiana Lamb.) sites. Over 20 years, WTB improved planted-tree survival but decreased longer term stand productivity in comparison with other harvest intensity – soil disturbance treatments. Vegetation control improved tree growth and stand productivity initially, but over time, benefits declined substantially. SOT and WTT had similar impacts on stand production. Disc trenching improved initial planted-tree growth (WTT vs. WT), particularly without vegetation control. Jack pine natural regeneration was greatest with SOT, accounting for 25% of stand biomass at year 20. Stand structure effects included increased size inequality of naturals with WTB and reduced size inequality and asymmetry of naturals with vegetation control. Overall, impacts of forest floor removal and natural regeneration on stand development have become increasingly important over time compared with those of vegetation control.
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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 | 0.001 | 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 | 0.000 | 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".