Leaf hydraulic conductivity and photosynthesis are genetically correlated in an annual grass
Bibliographic record
Abstract
Comparative studies suggest that a positive correlation between xylem water transport and photosynthesis is adaptive. A requirement for the adaptive evolution of coordination between xylem and photosynthetic functions is the presence of genetic variation and covariation for these traits within populations. Here it was determined whether there was genetic variation and covariation for leaf blade hydraulic conductivity (K(W)), photosynthetic rate (A), stomatal conductance (g(s)), and time to flowering in a population of recombinant inbred lines of Avena barbata, a Mediterranean annual grass. Significant (P < 0.05) broad-sense heritabilities (H(2)) were detected for K(W) (H(2) = 0.33), A (H(2) = 0.23) and flowering time (H(2) = 0.62), but not for g(s). Significant positive genetic covariation between A and K(W) was also observed. There was no other genetic covariation among traits. The first evidence of genetic variation for K(W) within a species was obtained. These results also indicate that there is a genetic basis for the positive association between xylem water transport and photosynthesis. The presence of significant genetic variation and covariation for these traits in natural populations would facilitate correlated evolution between xylem and leaf functions.
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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 | 0.001 |
| 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 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".