Rapid response of nonstructural carbohydrate allocation and photosynthesis to short photoperiod, low temperature, or elevated <scp>CO<sub>2</sub></scp> in <i>Pinus strobus</i>
Bibliographic record
Abstract
Abstract During autumn, decreasing photoperiod and temperature temporarily perturb the balance between carbon uptake and carbon demand in overwintering plants, requiring coordinated adjustments in photosynthesis and carbon allocation to re‐establish homeostasis. Here we examined adjustments of photosynthesis and allocation of nonstructural carbohydrates (NSCs) following a sudden shift to short photoperiod, low temperature, and/or elevated CO2 in Pinus strobus seedlings. Seedlings were initially acclimated to 14 h photoperiod (22/15°C day/night) and ambient CO2 (400 ppm) or elevated CO2 (800 ppm). Seedlings were then shifted to 8 h photoperiod for one of three treatments: no temperature change at ambient CO2 (22/15°C, 400 ppm), low temperature at ambient CO2 (12/5°C, 400 ppm), or no temperature change at elevated CO2 (22/15°C, 800 ppm). Short photoperiod caused all seedlings to exhibit partial nighttime depletion of starch. Short photoperiod alone did not affect photosynthesis. Short photoperiod combined with low temperature caused hexose accumulation and repression of photosynthesis within 24 h, followed by a transient increase in nonphotochemical quenching (NPQ). Under long photoperiod, plants grown under elevated CO2 exhibited significantly higher NSCs and photosynthesis compared to ambient CO2 plants, but carbon uptake exceeded sink capacity, leading to elevated NPQ; carbon sink capacity was restored and NPQ relaxed within 24 h after shift to short photoperiod. Our findings indicate that P. strobus rapidly adjusts NSC allocation, not photosynthesis, to accommodate short photoperiod. However, the combination of short photoperiod and low temperature, or long photoperiod and elevated CO2 disrupts the balance between photosynthesis and carbon sink capacity, resulting in increased NPQ to alleviate excess energy.
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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 | 0.001 |
| 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".