Light quality and quantity regulate aerobic methane emissions from plants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Studies have been mounting in support of the finding that plants release aerobic methane ( CH 4 ), and that these emissions are increased by both short‐term and long‐term environmental stress. It remains unknown whether or not they are affected by variation in light quantity and quality, whether emissions change over time, and whether they are influenced by physiological parameters. Light is the primary energy source of plants, and therefore an important regulator of plant growth and development. Both shade‐intolerant sunflower and shade‐tolerant chrysanthemum were investigated for the release of aerobic CH 4 emissions, using either low or high light intensity, and varying light quality, including control, low or normal red:far‐red ratio (R: FR ), and low or high levels of blue, to discern the relationship between light and CH 4 emissions. It was found that low levels of light act as an environmental stress, facilitating CH 4 release from both species. R: FR and blue lights increased emissions under low light, but the results varied with species, providing evidence that both light quantity and quality regulate CH 4 emissions. Emission rates of 6.79–41.13 ng g −1 DW h −1 and 18.53–180.25 ng g −1 DW h −1 were observed for sunflower and chrysanthemum, respectively. Moreover, emissions decreased with age as plants acclimated to environmental conditions. Since effects were similar in both species, there may be a common trend among a number of shade‐tolerant and shade‐intolerant species. Light quantity and quality are influenced by factors including cloud covering, so it is important to know how plants will be affected in the context of aerobic CH 4 emissions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it