Seasonal Changes in Photosynthetic Energy Utilization in a Desert Shrub (Artemisia ordosica Krasch.) during Its Different Phenophases
Bibliographic record
Abstract
Our understanding of the mechanisms of plant response to environment fluctuations during plants’ phenological phases (phenophases) remains incomplete. Continuous chlorophyll fluorescence (ChlF) measurements were acquired from the field to quantify the responses in a desert shrub species (i.e., Artemesia ordosica Krasch. (A. ordosica)) to environmental factors by assessing variation in several ChlF-linked parameters and to understand plant acclimation to environmental stresses. Maximal quantum yield of PSII photochemistry (Fv/Fm) was shown to be reduced by environmental stressors and to be positively correlated to air temperature (Ta) during the early and late plant-growing stages, indicating a low temperature-induced inhibition during the leaf expansion and coloration phases. Effective quantum yield of PSII photochemistry (ΦPSII) was negatively correlated to incident photosynthetically active radiation (PAR) irrespective of phenophase, suggesting excessive radiation-induced inhibition at all phenophases. The main mechanism for acclimating to environmental stress was the regulatory thermal dissipation (ΦNPQ) and the long-term regulation of relative changes in Chl a to Chl b. The relative changes in photosynthetic energy utilization and dissipation in energy partitioning meant A. ordosica could acclimatize dynamically to environmental changes. This mechanism may enable plants in arid and semi-arid environments to acclimatize to increasingly extreme environmental conditions under future projected 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) | 0.000 | 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".