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 (gs), intrinsic water-use efficiency (A/gs), photosynthetic nitrogen-use efficiency (PNUE), leaf and stemwood13C/12C isotope ratios (δ13C), stomatal density (Ds), and leaf amphistomaticity. There were no significant differences in A, PNUE, biomass, or height growth between species. On average, black cottonwood had lower gsand Ds, but higher A/gsand δ13C. Variation within provenances, in most traits, exceeded variation between species or provenances. δ13C and A/gswere highly correlated across all genotypes. Variation in A/gsseemed primarily related to gs, although positive correlations were found between δ13C 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 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 | 0.000 |
| 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) | 0.001 | 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".