Autumn photosynthetic decline and growth cessation in seedlings of white spruce are decoupled under warming and photoperiod manipulations
Bibliographic record
Abstract
Climate warming is expected to increase the seasonal duration of photosynthetic carbon fixation and tree growth in high-latitude forests. However, photoperiod, a crucial cue for seasonality, will remain constant, which may constrain tree responses to warming. We investigated the effects of temperature and photoperiod on weekly changes in photosynthetic capacity, leaf biochemistry and growth in seedlings of a boreal evergreen conifer, white spruce [Picea glauca (Moench) Voss]. Warming delayed autumn declines in photosynthetic capacity, extending the period when seedlings had high carbon uptake. While photoperiod was correlated with photosynthetic capacity, short photoperiods did not constrain the maintenance of high photosynthetic capacity under warming. Rubisco concentration dynamics were affected by temperature but not photoperiod, while leaf pigment concentrations were unaffected by treatments. Respiration rates at 25 °C were stimulated by photoperiod, although respiration at the growth temperatures was increased in warming treatments. Seedling growth was stimulated by increased photoperiod and suppressed by warming. We demonstrate that temperature is a stronger control on the seasonal timing of photosynthetic down-regulation than is photoperiod. Thus, while warming can stimulate carbon uptake in boreal conifers, the extra carbon may be directed towards respiration rather than biomass, potentially limiting carbon sequestration under climate change.
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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".