Clouds and cloud immersion alter photosynthetic light quality in a temperate mountain cloud forest
Bibliographic record
Abstract
Light quantity and quality strongly influence plant ecophysiology, especially in cloud forests. Only a few studies have investigated the quantitative effects of clouds on incident sunlight, and almost no studies have explored the specific effects of cloud immersion on light quality. In the present study, the spectral quantity and quality of sunlight during sunny (S), low cloud (LC), and cloud immersed (CI) days in open canopy and understory microsites are compared in high elevation cloud forests in the southern Appalachian Mountains, USA. Cumulative daily radiation measured on CI days was 85% less than on S days at open sites, but about the same as S days in understory sites. LC and CI conditions enhanced blue light by 5%–15% in open sites, but decreased it by 25%–60% in understory sites. In cloudy conditions, red light decreased by 6%–11% in open areas and increased by 25%–30% in understory sites. Cloudiness also resulted in important changes in spectral band ratios, and was associated with light diffusivity. Thus, cloud regimes had a strong influence on the photosynthetic light quality of incident sunlight.
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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".