Warming delays autumn declines in photosynthetic capacity in a boreal conifer, Norway spruce (<i>Picea abies</i>)
Bibliographic record
Abstract
Climate change, via warmer springs and autumns, may lengthen the carbon uptake period of boreal tree species, increasing the potential for carbon sequestration in boreal forests, which could help slow climate change. However, if other seasonal cues such as photoperiod dictate when photosynthetic capacity declines, warmer autumn temperatures may have little effect on when carbon uptake capacity decreases in these species. We investigated whether autumn warming would delay photosynthetic decline in Norway spruce (Picea abies (L.) H. Karst.) by growing seedlings under declining weekly photoperiods and weekly temperatures either at ambient temperature or a warming treatment 4 °C above ambient. Photosynthetic capacity was relatively constant in both treatments when weekly temperatures were >8 °C, but declined rapidly at lower temperatures, leading to a delay in the autumn decline in photosynthetic capacity in the warming treatment. The decline in photosynthetic capacity was not related to changes in leaf nitrogen or chlorophyll concentrations, but was correlated with a decrease in the apparent fraction of leaf nitrogen invested in Rubisco, implicating a shift in nitrogen allocation away from the Calvin cycle at low autumn growing temperatures. Our data suggest that as the climate warms, the period of net carbon uptake will be extended in the autumn for boreal forests dominated by Norway spruce, which could increase total carbon uptake in these forests.
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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".