Three causes of variation in the photochemical reflectance index (<scp>PRI</scp>) in evergreen conifers
Bibliographic record
Abstract
The photochemical reflectance index (PRI) reflects diurnal xanthophyll cycle activity and is also influenced by seasonally changing carotenoid : Chl pigment ratios. Both changing pigment pools and xanthophyll cycle activity contribute to photoprotection in evergreen conifers exposed to boreal winters, but they operate over different timescales, and their relative contribution to the PRI signal has often been unclear. To clarify these responses and their contribution to the PRI signal, leaf PRI, pigment composition, temperature and irradiance were monitored over 2 yr for two evergreen conifers (Pinus contorta and Pinus ponderosa) in a boreal climate. PRI was affected by three distinct processes operating over different timescales and exhibiting contrasting spectral responses. Over the 2 yr study period, the greatest change in PRI resulted from seasonally changing carotenoid : Chl pigment ratios, followed by a previously unreported shifting leaf albedo during periods of deep cold. Remarkably, the smallest change was attributable to the xanthophyll cycle. To properly distinguish these three effects, interpretation of PRI must consider temporal context, physiological responses to evolving environmental conditions, and spectral response. Consideration of the separate mechanisms affecting PRI over different timescales could greatly improve efforts to monitor changing photosynthetic activity using optical remote sensing.
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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 | 0.001 | 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".