Influence of evaporative demand on aquaporin expression and root hydraulics of hybrid poplar
Bibliographic record
Abstract
When light levels and evaporative demand increase, dynamic physiological changes in roots may be required to restore the water balance at the whole plant level. We hypothesized that a dynamic increase in root hydraulic conductance (L(P)) and aquaporin (AQP) expression could moderate the transpiration-induced drop in water potential (Ψ), allowing continued gas exchange in hybrid poplar (Populus trichocarpa × deltoides) saplings. Fifty-six AQPs have been identified in poplar, but little information about their expression patterns in roots is available, especially from a whole-plant water relations perspective. We measured AQP expression and L(P) in plants subjected to different levels of light and evaporative demand. Shaded plants had only one-tenth the root area of plants growing at higher light levels. Shade-grown saplings experiencing a sudden increase in light exhibited a threefold higher L(P) than plants remaining in shade. This dynamic increase in L(P) corresponded with increased transcript abundance of 15 AQPs out of a total of 33 genes simultaneously assessed by quantitative RT-PCR. The tissue-level localization of transcripts of four AQPs was studied with in situ hybridization. Comprehensive expression profiling in conjunction with physiological and morphological measurements is a valuable reference for future studies on AQP function in poplar.
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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 | 0.000 | 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) | 0.001 | 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".