Low stomatal and internal conductance to CO<sub>2</sub> versus Rubisco deactivation as determinants of the photosynthetic decline of ageing evergreen leaves
Bibliographic record
Abstract
A novel A-Ci curve (net CO2 assimilation rate of a leaf -An- as a function of its intercellular CO2 concentration -Ci) analysis method (Plant, Cell & Environment 27, 137-153, 2004) was used to estimate the CO2 transfer conductance (gi) and the maximal carboxylation (Vcmax) and electron transport (Jmax) potentials of ageing, non-senescing Pseudotsuga menziesii leaves in relation to their nitrogen (N) content and protein and pigment composition. Both gi and the stomatal conductance (gsc) of leaves were closely coupled to Vcmax, Jmax and An with all variables decreasing with increasing leaf age. Consequently, both Ci and Cc (chloroplastic CO2 concentration) remained largely conserved through successive growing seasons. The N content of leaves, as well as the amount of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) and other sodium dodecyl sulfate-soluble proteins, increased during the first three growing seasons, then stabilized or decreased only slightly afterwards. Thus, the age-related photosynthetic nitrogen use efficiency (PNUE) decline of leaves was not a consequence of decreased allocation of N towards Rubisco and other proteins involved in bioenergetics and light harvesting. Rather, loss of photosynthetic capacity was the result of the decreased activation state of Rubisco and proportional down-regulation of electron transport towards the photosynthetic carbon reduction (PCR) and photorespiratory (PCO) cycles in response to a reduction of CO2 supply to the chloroplasts' stroma. This study emphasizes the regulatory potential and homeostaticity of Cc- rather than photosynthetic metabolites or Ci- in relation to the commonly observed correlation between photosynthesis and gsc.
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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".