Determination of the site of CO2 sensing in poplar: is the area-based N content and anatomy of new leaves determined by their immediate CO2 environment or by the CO2 environment of mature leaves?
Bibliographic record
Abstract
Exposure to an elevated CO(2) concentration ([CO(2)]) generally decreases leaf N content per unit area (N(area)) and stomatal density, and increases leaf thickness. Mature leaves can 'sense' elevated [CO(2)] and this regulates stomatal development of expanding leaves (systemic regulation). It is unclear if systemic regulation is involved in determination of leaf thickness and N(area)-traits that are significantly correlated with photosynthetic capacity. A cuvette system was used whereby [CO(2)] around mature leaves was controlled separately from that around expanding leaves. Expanding leaves of poplar (Populus trichocarpa×P. deltoides) seedlings were exposed to elevated [CO(2)] (720 μmol mol(-1)) while the remaining mature leaves inside the cuvette were under ambient [CO(2)] of 360 μmol mol(-1). Reverse treatments were performed. Exposure of newly developing leaves to elevated [CO(2)] increased their thickness, but when mature leaves were exposed to elevated [CO(2)] the increase in thickness of new leaves was less pronounced. The largest response to [CO(2)] was reflected in the palisade tissue thickness (as opposed to the spongy tissue) of new leaves. The N(area) of new leaves was unaffected by the local [CO(2)] where the new leaves developed, but decreased following the exposure of mature leaves to elevated [CO(2)]. The volume fraction of mesophyll cells compared with total leaf and the mesophyll cell density changed in a manner similar to the response of N(area). These results suggest that N(area) is controlled independently of the leaf thickness, and suggest that N(area) is under systemic regulation by [CO(2)] signals from mature leaves that control mesophyll cell division.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".