A comparison of timber and forage values within lodgepole pine (Pinus contorta) stands in south-central British Columbia
Bibliographic record
Abstract
This research compared the influence of pre-commercial thinning (PCT) and fertilization on forage and timber values in three managed lodgepole pine (Pinus contorta Dougl. Var. latifolia Engelm.) forests in the Interior of British Columbia (BC). Cattle (Bos taurus) were grazed in two of the forests. The respective values of treatments were compared using their land expectation value (LEV). Timber values were calculated using the Tree Interpolation Program for Stand Yields (TIPSY) growth and yield model. Cattle use was calculated by relating estimated grazing densities with TIPSY-derived canopy closure estimates for known periods, and establishing a relationship using a linear regression. The value of forage as upland cattle pasture was calculated using a pasture lease rate ($/animal unit month) derived from prior market research in BC, Alberta, and the United States of America. In all study areas the unrelated control was the profit-maximizing silvicultural strategy. In the Summerland study area, no treatment was profitable. In the Kelowna study area, all the unfertilized treatments were profitable. In the Cariboo study area, all treatments were profitable. In all forests, the unfertilized 2000 stems/ha. treatment was the best alternative option, and under the right conditions could be a profit-maximizing investment. The inclusion of forage values in the comparison of investments did not change which treatment was profit-maximizing: treatments affected timber values much more than forage values. This research suggests that under conditions of high site productivity and an assumed social discount rate of 4%, PCT and intensive fertilization can be a profitable management option for interior lodgepole pine stands.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".