Effect of climate on lodgepole pine stem taper in British Columbia, Canada
Bibliographic record
Abstract
The taper equations used by the Ministry of Forests, Lands and Natural Resource Operations in British Columbia (BC), Canada, date back to the mid-1950s. Very little work has been done on examining the effect of climate on taper, particularly for BC but elsewhere as well. The objective of our research was to determine whether climate has an effect on tree taper for lodgepole pine (Pinus contorta Dougl. ex Loud.) in BC. The data for this project consisted of multiple diameter inside bark measurements along the stems of 270 trees across eight biogeoclimatic zones. In addition, 20 climate variables for the sample sites were predicted from the ClimateWNA model. Kozak's variable-exponent taper model was refitted with the climate variables in the exponent of the model. The single temperature- and precipitation-related variables that provided the best fit were incorporated into the final taper model. The model was analysed as a mixed-effects model, with spatial correlation and heteroscedastic errors being explicitly modelled. Mean annual precipitation and the Julian date of the first frost after the summer growing period were the best predictors of taper. Further work is required to understand why these variables are important predictors of taper, but a possible linkage is through the tree's crown.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".