Stumping trials in British Columbia — organic matter removal and compaction effects on tree growth from seedlings to midrotation stands
Bibliographic record
Abstract
There is considerable interest in understanding the repercussions of compaction and organic matter removal on soil quality and forest productivity. However, long-term field trials examining the effects of machinery and forest biomass removal on soil quality and stand regeneration are scarce. We present 20–31 years of tree growth results from four unique stump removal field trials. Each site had both treatments with varying amounts of organic matter removal (from tree stem harvesting to removal of tree stumps to loss of roots) and treatments with different levels of compaction due to site preparation machinery. Tree heights among the different treatments at midrotation were the same or taller than those with minimal organic matter removal and compaction. However, when stand development was evaluated using the quantity of tree volume for the given number of trees planted, treatment effects were clearly evident; tree volumes were significantly lower in compacted treatments, whereas organic matter removal did not appear to effect stand production. Although the sites were not directly comparable, when combined, the field trials provide insights to the possible implications of forest biomass harvesting on stand regeneration and overall forest soil quality.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".