Comparative resource-use efficiencies and growth of<i>Populus trichocarpa</i>and<i>Populus balsamifera</i>under glasshouse conditions
Bibliographic record
Abstract
Amongst other traits, ideal poplar genotypes for afforestation programs would be fast growing and have high resource-use efficiencies. Black cottonwood (Populus trichocarpa Torr. & A. Gray) and balsam poplar (Populus balsamifera L.) are closely related species that together extend over much of the forested area of Canada. Within their respective ranges, however, black cottonwood attains much greater size than balsam poplar. Two populations of each species, each with three replicates of 9–10 genotypes, were grown from stem cuttings for 60 days in a greenhouse under long days to examine variation in biomass, height growth, net photosynthesis (A), stomatal conductance (g s ), intrinsic water-use efficiency (A/g s ), photosynthetic nitrogen-use efficiency (PNUE), leaf and stemwood 13 C/ 12 C isotope ratios (δ 13 C), stomatal density (D s ), and leaf amphistomaticity. There were no significant differences in A, PNUE, biomass, or height growth between species. On average, black cottonwood had lower g s and D s , but higher A/g s and δ 13 C. Variation within provenances, in most traits, exceeded variation between species or provenances. δ 13 C and A/g s were highly correlated across all genotypes. Variation in A/g s seemed primarily related to g s , although positive correlations were found between δ 13 C and A in the P. balsamifera populations, which more generally met expectations for sink-driven differences in water-use efficiency. There is potential to identify fast-growing genotypes with relatively high use efficiencies for both water and nitrogen.
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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 | 0.000 | 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".