Height growth determinants and adaptation to temperature in pines: a case study of<i>Pinus contorta</i>and<i>Pinus monticola</i>
Bibliographic record
Abstract
In this study we aimed to compare and explain the height growth performance of two contrasting pine species: lodgepole pine (Pinus contorta Dougl. ex. Loud) and western white pine(Pinus monticola Dougl. ex D. Don.). We compiled measurements of total height growth at different ages and shoot elongation phenology realized in several provenance test trials for 109 provenances of lodgepole pine and 54 provenances of western white pine. The response of shoot elongation to temperature was assessed using a phenological model fitted on provenance mean growth curves. Although total height growth followed the same geographic trends in both species, the response of shoot elongation to temperature was different between the two, with few (lodgepole pine) or no differences among provenances (western white pine) from diverse geographic regions. The temperature for which potential cell growth rate is 50% was 10.8 ± 0.13 °C (mean ± standard error) for western white pine compared to 5.26 ± 0.075 °C for lodgepole pine. Phenology did not explain growth performance differences among geographical regions in both species, which instead were explained by differences in the number of internodes set the preceding summer; provenances originating from stressful environments produced the fewest internodes, possibly due to reallocation of carbohydrates to stress resistance.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".