Evaluating Four Silvicultural Prescriptions for Selective Harvest in the Great Lakes-St. Lawrence Forest, Ontario, Canada
Bibliographic record
Abstract
Selective harvesting of forests, also known as thinning, is a widely used treatment in the Great Lakes-St. Lawrence Forest ecosystem that dominates the central part of the province of Ontario. Increasingly, the application of selective harvest is discussed as a method of reducing the risk of forest fire and increasing the availability of biomass for emerging bioproducts. There are a variety of approaches to selective harvest that can be employed, including single tree selection (STS), diameter limit cutting (DLC), financial maturity selection (FMS), and intensive crop-tree release (ICTR). These silvicultural treatments are tested against control plots (CON) in a research forest (Blue Heron Demonstration Forest) located within the Haliburton Forest and Wildlife Reserve, in Haliburton, Ontario. The objectives of this research are to assess stand level responses to these silvicultural treatments (including harvested material and regrowth potential) as well as individual tree species response to these treatments, using measurements of tree basal area and stand basal area. These measurements are taken across 28 compartments delineated within the Blue Heron Demonstration Forest, using four sample plots per compartment. A scoring methodology is proposed to help determine the optimal silvicultural treatment. At the stand level, the treatments that provided the most timber are diameter limit cutting (DLC), delivering an average of 16.9 m2/ha, followed by FMS, ICTR, and finally STS. For regrowth, the best performing prescriptions are STS, followed by DLC, FMS, and finally ICTR. At a species level, the best growth rates for sugar maple are observed with STS, followed closely by DLC, FMS, ICTR, and finally the control. For American beech, the best performance is found with DLC, followed by FMS, STS, ICTR, and the control. Overall, the scores indicate that the best treatment to provide timber, promote regrowth, and support species diversity is STS, followed closely by DLC, then FMS. By comparison, ICTR does not perform well, providing less biomass and less regrowth than the other prescriptions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".