Operational biomass recovery of small trees: equations for six central Ontario tree species
Bibliographic record
Abstract
Accurate estimates of the amount of biomass that can be recovered at the roadside are needed to make informed decisions about whether to implement an increased utilization harvesting system to supply additional bioenergy feedstocks. Current estimates of recovery are based on total aboveground biomass equations that do not always account for the volume lost to the unharvested stumps or to tops and branches broken during forestry operations. The study took place in a white pine (Pinus strobus L.) mixedwood forest at the Petawawa Research Forest in central Ontario. Equations to describe recoverable biomass were developed from 371 cut and skidded trees, which ranged from 3 to 24 cm in diameter at breast height, across six species. For each species and diameter size class, we evaluated the difference between estimates produced by locally developed equations and those from published equations produced for other locations and forest types. Our recovered biomass estimates were generally higher than the Canadian national averages but within the observed range of published values from across North America. We report that small trees are recovered nearly in their entirety, with little breakage and loss during operations. The high degree of variability among estimates produced by the various equations poses one of the biggest challenges in accurately estimating roadside biomass in an operational setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".