Photoperiod and temperature constraints on the relationship between the photochemical reflectance index and the light use efficiency of photosynthesis in<i>Pinus strobus</i>
Bibliographic record
Abstract
The photochemical reflectance index (PRI) is a proxy for the activity of the photoprotective xanthophyll cycle and photosynthetic light use efficiency (LUE) in plants. Evergreen conifers downregulate photosynthesis in autumn in response to low temperature and shorter photoperiod, and the dynamic xanthophyll cycle-mediated non-photochemical quenching (NPQ) is replaced by sustained NPQ. We hypothesized that this shift in xanthophyll cycle-dependent energy partitioning during the autumn is the cause for variations in the PRI-LUE relationship. In order to test our hypothesis, we characterized energy partitioning and pigment composition during a simulated summer-autumn transition in a conifer and assessed the effects of temperature and photoperiod on the PRI-LUE relationship. We measured gas exchange, chlorophyll fluorescence and leaf reflectance during the photosynthetic downregulation in Pinus strobus L. seedlings exposed to low temperature/short photoperiod or elevated temperature/short photoperiod conditions. Shifts in energy partitioning during simulated autumn were observed when the pools of chlorophylls decreased and pools of photoprotective carotenoids increased. On a seasonal timescale, PRI was controlled by carotenoid pool sizes rather than xanthophyll cycle dynamics. Photochemical reflectance index variation under cold autumn conditions mainly reflected long-term pigment pool adjustments associated with sustained NPQ, which impaired the PRI-LUE relationship. Exposure to warm autumn conditions prevented the induction of sustained NPQ but still impaired the PRI-LUE relationship. We therefore conclude that alternative zeaxanthin-independent NPQ mechanisms, which remain undetected by the PRI, are present under both cold and warm autumn conditions, contributing to the discrepancy in the PRI-LUE relationship during autumn.
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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".