Economic analysis of vegetation management alternatives in Ontario
Bibliographic record
Abstract
Vegetation management practices have become an integral component of forest management. Economics of alternative vegetation management treatments were analyzed in this thesis on the basis of two journal papers. Six research sites established and managed by Vegetation Management Alternatives Program of Ontario were the sources of data. In the first paper, differences in stem quality, and volume and value of fibre produced by planted white spruce [Picea glauca (Moench) Voss] 16 years after vegetation management treatments in northwestern Ontario were examined. Forest Vegetation Simulator (FVSOntario) was used to pro-ject the total and merchantable volume to age 70 and BUCK-2 was used to opti-mize the resulting product mix. Projected value was based on 2009 prices for hog fuel and SPF (spruce-pine-fir) eastern green lumber prices. At 16 years post-treat-ment, gross total volumes in herbicide-treated and mechanically cut plots were significantly higher (120-165% and 94-98%, respectively) than that in control plots (14.73 m3 ha-1). Based on height, diameter, and taper criteria, observed tree quality did not differ among treatments. The projected value of the fibre produced was 36 to 53% higher in herbicide-treated plots and 24 to 37% higher in mechanically cut plots than in control plots ($18,486.76 ha-1). \nSecond paper presents the stand-level benefit-cost analyses of 12 vegeta-tion management treatments applied at six study sites in northern Ontario. Net present value (NPV), benefit-cost ratio (BCR), and internal rate of return (IRR) for crop and all species in each treatment and site were calculated and compared using 2009 constant dollars and variable real discount rates. Aerial herbicide treatments produced the highest NPV, BCR, and IRR. Internal rates of return of 4.32% for aerial herbicide, 2.90% for manual brush cutting, 2.82% for ground ap-plied herbicide, and 2.50% for brush cutting plus herbicide treatments indicated that all of the vegetation management alternatives evaluated are economically viable.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| 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) | 0.021 | 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".