Biomass equations for lodgepole pine in northern Sweden
Bibliographic record
Abstract
Biomass equations for cultivated lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) were developed based on data from destructive biomass sampling of 164 trees collected from 13 sites at latitudes 61.9°N–66.2°N in northern Sweden. Stand age varied between 20 and 87 years and top height varied between 8 and 32 m. Seeded and planted stands with different densities were included. Allometric biomass equations for all above-stump components were constructed, expressing dry mass of stem, bark, living and dead branch wood, foliage, and cones, as well as total mass. Equations with one to three independent variables were constructed for each component, accounting for variances within and between sites. Estimated values for trees of different sizes were compared with corresponding estimates for lodgepole pine in Canada and Scots pine (Pinus sylvestris L.) in Sweden and Finland. Residual variation of our equations was lower than that of equations from other sources. Our equations predicted average biomass levels similar to the predictions from Canadian equations for natural stands. In comparison with Scots pine, at given stem dimensions, lodgepole pine had 50%–100% more foliage biomass and greater dead branch biomass with increasing tree size. The wide amplitude of our data and the flexible form of our equations should make them useful for wider application.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".