Influence of water table decline on growth allocation and endogenous gibberellins in black cottonwood
Bibliographic record
Abstract
Cottonwoods occur in riparian areas where water table depth generally varies with the elevation of the adjacent river. Plant adaptation to the riparian zone requires the coordination of root elongation to maintain contact with the water table during the summer decline. We investigated the effects of rate of water decline on growth allocation and concentrations of endogenous gibberellins (GAs) in black cottonwood (Populus trichocarpa Torr. & A. Gray ex Hook.) saplings. Rhizopods were used to achieve water decline rates of 0, 2 and 4 cm day(-1). Root elongation approximately doubled in response to the 2 cm day(-1) treatment, whereas leaf area was reduced. A water decline rate of 4 cm day(-1) led to water stress, as evidenced by reduced growth, increased leaf diffusive resistance, decreased water potential, and leaf senescence and abscission. Endogenous GAs were extracted, purified and analyzed by gas chromatography-selected ion monitoring with internal [(2)H(2)]GA standards. Across the sampled plant organs, GAs were generally highest in shoot tips and sequentially lower in basal stems, root tips, leaves and upper roots; GAs were thus abundant in rapidly growing tissues. Of the GAs measured, GA(1) tended to predominate, followed sequentially by GA(3), GA(8), GA(19), GA(20), GA(29) and GA(4). There was little relationship between GA concentration and growth allocation across the water table decline treatments, although GA(8) was consistently reduced in plants experiencing water table decline. Because GA(8) is the final gibberellin in the metabolic sequence, it might be useful for assessing historic patterns of GAs and growth rate. This study demonstrated changes in growth allocation in response to water table decline, but provided little evidence that endogenous GAs play a primary role in the regulation of root elongation in response to water table decline.
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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".