Impact of warming and drought on carbon balance related to wood formation in black spruce
Bibliographic record
Abstract
BACKGROUND AND AIMS: Wood formation in trees represents a carbon sink that can be modified in the case of stress. The way carbon metabolism constrains growth during stress periods (high temperature and water deficit) is now under debate. In this study, the amounts of non-structural carbohydrates (NSCs) for xylogenesis in black spruce, Picea mariana, saplings were assessed under high temperature and drought in order to determine the role of sugar mobilization for osmotic purposes and its consequences for secondary growth. METHODS: Four-year-old saplings of black spruce in a greenhouse were subjected to different thermal conditions with respect to the outside air temperature (T0) in 2010 (2 and 5 °C higher than T0) and 2011 (6 °C warmer than T0 during the day or night) with a dry period of about 1 month in June of each year. Wood formation together with starch, NSCs and leaf parameters (water potential and photosynthesis) were monitored from May to September. KEY RESULTS: With the exception of raffinose, the amounts of soluble sugars were not modified in the cambium even if gas exchange and photosynthesis were greatly reduced during drought. Raffinose increased more than pinitol under a pre-dawn water potential of less than -1 Mpa, presumably because this compound is better suited than polyol for replacing water and capturing free radicals, and its degradation into simple sugar is easier. Warming decreased the starch storage in the xylem as well the available hexose pool in the cambium and the xylem, probably because of an increase in respiration. CONCLUSIONS: Radial stem growth was reduced during drought due to the mobilization of NSCs for osmotic purposes and due to the lack of cell turgor. Thus plant water status during wood formation can influence the NSCs available for growth in the cambium and xylem.
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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".