Leaf morphological variation among paper birch (<i>Betula papyrifera</i> Marsh.) genotypes across Canada
Bibliographic record
Abstract
Variations in leaf morphological characteristics have been extensively studied at both interand intraspecific levels although not explicitly on paper birch (Betula papyrifera Marsh). Paper birch populations might have considerable genotypic and leaf morphological variations that have allowed them to inhabit wide environmental gradients. In this study, we analyzed variations in leaf morphological characteristics in 23 paper birch populations collected across Canada and grown in a greenhouse. Furthermore, we examined whether the variations in leaf morphological characteristics observed were related to the climate of the population’s origin. We found significant genotypic differences in all leaf morphological characteristics (p five principal components (PC) explaining 84.74% of the total variance in the original data. PCs accumulated with specific leaf area, petiole and leaf width were positively related to latitudinal, longitudinal, and elevational gradients at the population’s origin. Unpredictably, these PCs were significantly negatively correlated to precipitation and aridity index at the origin. Thus, we analyzed if correlations within leaf morphological characteristics had supported the birch populations to acclimate and produce unpredictable relations with the environment of origin. Our results showed that the populations originated in limited precipitation (during growing season) had large leaf width and petiole size but low leaf hairs on adaxial surface. Thus, all these leaf morphological features provide a basis for the birch to reduce water loss from leaves and balance water use efficiency in reduced precipitation. Furthermore, the leaf characteristics measured may also include phenotypic plasticity of the birch as an acclimation to the environment as in the greenhouse.
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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 | 0.000 |
| 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 | 0.000 |
| 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".