Genetic variation of hydraulic and wood anatomical traits in hybrid poplar and trembling aspen
Bibliographic record
Abstract
Intensive forestry systems and breeding programs often include either native aspen or hybrid poplar clones, and performance and trait evaluations are mostly made within these two groups. Here, we assessed how traits with potential adaptive value varied within and across these two plant groups. Variation in nine hydraulic and wood anatomical traits as well as growth were measured in selected aspen and hybrid poplar genotypes grown at a boreal planting site in Alberta, Canada. Variability in these traits was statistically evaluated based on a blocked experimental design. We found that genotypes of trembling aspen were more resistant to cavitation, exhibited more negative water potentials, and were more water-use-efficient than hybrid poplars. Under the boreal field test conditions, which included major regional droughts, height growth was negatively correlated with branch vessel diameter (Dv ) in both aspen and hybrid poplars and differences in Dv were highly conserved in aspen trees from different provenances. Differences between the hybrid poplars and aspen provenances suggest that these two groups employ different water-use strategies. The data also suggest that vessel diameter may be a key trait in evaluating growth performance in a boreal environment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".