The utility of the two-pass harvesting system: an analysis using the ecosystem simulation model FORECAST
Bibliographic record
Abstract
The ecosystem model FORECAST was used to simulate the yield potential in Saskatchewan mixedwoods of the two-pass harvesting system. The simulated two-pass stand consisted of an overstory population of pure trembling aspen (Populus tremuloides Michx.) with a white spruce (Picea glauca (Moench) Voss) understory. The aspen was removed at year 60, and yields of the understory spruce and resprouting aspen were simulated for 80 years thereafter. The two-pass simulations were compared with two simulated conventional harvesting systems. The first system consisted of a single final harvest at year 140. In the second system, a clearcut was conducted at year 60. White spruce was then planted in the subsequent year at 400, 600, or 800 stems/ha, and aspen also permitted to resprout. Growth was then simulated for a further 80 years. FORECAST projections indicated that the two-pass system might be effective for releasing the white spruce understory, achieving at least a twofold gain in spruce volume relative to conventional methods. Furthermore, total volumes exceeded those derived from the unmanaged stand, while second rotation yields of aspen declined with spruce understory density. These simulations suggest the two-pass harvesting system has strong potential as a tool for mixedwood management.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".