Variable mesophyll conductance revisited: theoretical background and experimental implications
Bibliographic record
Abstract
The CO(2) concentration at the site of carboxylation inside the chloroplast stroma depends not only on the stomatal conductance, but also on the conductance of CO(2) between substomatal cavities and the site of CO(2) fixation. This conductance, commonly termed mesophyll conductance (g(m) ), significantly constrains the rate of photosynthesis. Here we show that estimates of g(m) are influenced by the amount of respiratory and photorespiratory CO(2) from the mitochondria diffusing towards the chloroplasts. This results in an apparent CO(2) and oxygen sensitivity of g(m) that does not imply a change in intrinsic diffusion properties of the mesophyll, but depends on the ratio of mitochondrial CO(2) release to chloroplast CO(2) uptake. We show that this effect (1) can bias the estimation of the CO(2) photocompensation point and non-photorespiratory respiration in the light; (2) can affect the estimates of ribulose 1·5-bisphosphate carboxylase/oxygenase (Rubisco) kinetic constants in vivo; and (3) results in an apparent obligatory correlation between stomatal conductance and g(m) . We further show that the amount of photo(respiratory) CO(2) that is refixed by Rubisco can be directly estimated through measurements of g(m) .
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".