Low root reserve accumulation during drought may lead to winter mortality in poplar seedlings
Bibliographic record
Abstract
Climate models suggest that more frequent drought events of greater severity and length, associated with climate change, can be expected in the coming decades. Although drought-induced tree mortality has been recognized as an important factor modulating forest demography at the global scale, the mechanisms underlying drought-induced tree mortality remain contentious. Above- and below-ground growth, gas exchange, water relations and carbon reserve accumulation dynamics at the organ and whole-plant scale were quantified in Populus tremuloides and P. balsamifera seedlings in response to severe drought. Seedlings were maintained in drought conditions over one growing and one dormant winter season. Our experiment presents a detailed description of the effect of severe drought on growth and physiological variables, leading to seedling mortality after an extended period of drought and dormancy. After re-watering following the dormant period, drought-exposed seedlings did not re-flush, showing that the root system had died off. The results of this study suggest a complex series of physiological feedbacks between the measured variables in both Populus species. Further, they reveal that reduced reserve accumulation in the root system during drought decreases the conversion of starch to soluble sugars in roots, which may contribute to the root death of drought-exposed seedlings during the dormant season by compromising the frost tolerance of the root system.
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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) | 0.000 | 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".