<i>Populus deltoides</i> is suitable for moist and short-term flooded soil conditions on the basis of its relative growth rate and stoichiometry
Bibliographic record
Abstract
The aim of this study was to understand the effects of water stress on plant growth, nutrients distribution and their stoichiometry in different organs of poplar seedlings, and further explore the validation of growth rate hypothesis (GRH) under water stress treatments. Poplar seedlings ( Populus deltoides “Nanlin 3804”) were grown under drought (D), normal water management (CK), low-level flooding (LF), high-level flooding (HF), and high-level flooding followed by flood recovery (FR) treatments in 60 days. Poplar seedling growth, nutrients contents, and stoichiometry among different treatments were analyzed. The seedlings had greater relative growth rate of biomass, height, and stem-basal diameter (BRGR, HRGR, and SRGR, respectively) under flooding treatments, especially in FR treatment ( P < 0.05). Among different organs, stem had the highest BRGR. The N, P, and K concentrations were highest in D treatment ( P < 0.05). Leaves and stems had greater nutrient concentrations and stoichiometries than roots under different treatments ( P < 0.05). The plant stoichiometry were positively correlated with BRGR and HRGR but negatively correlated with SRGR from whole-plant perspective. In organ level, BRGR were negatively correlated with root stoichiometry, but were positively correlated with stem and leaf stoichiometry. Poplar seedlings are suitable for cultivation in relatively moist soil or under short-term periodic flooding conditions. This study provides a scientific basis for the cultivation of high-quality seedlings and the selection of suitable afforestation sites for existing poplar clones.
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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".