Increasing water use efficiency along the C3 to C4 evolutionary pathway: a stomatal optimization perspective
Bibliographic record
Abstract
C4 photosynthesis evolved independently numerous times, probably in response to declining atmospheric CO2 concentrations, but also to high temperatures and aridity, which enhance water losses through transpiration. Here, the environmental factors controlling stomatal behaviour of leaf-level carbon and water exchange were examined across the evolutionary continuum from C3 to C4 photosynthesis at current (400 μmol mol(-1)) and low (280 μmol mol(-1)) atmospheric CO2 conditions. To this aim, a stomatal optimization model was further developed to describe the evolutionary continuum from C3 to C4 species within a unified framework. Data on C3, three categories of C3-C4 intermediates, and C4 Flaveria species were used to parameterize the stomatal model, including parameters for the marginal water use efficiency and the efficiency of the CO2-concentrating mechanism (or C4 pump); these two parameters are interpreted as traits reflecting the stomatal and photosynthetic adjustments during the C3 to C4 transformation. Neither the marginal water use efficiency nor the C4 pump strength changed significantly from C3 to early C3-C4 intermediate stages, but both traits significantly increased between early C3-C4 intermediates and the C4-like intermediates with an operational C4 cycle. At low CO2, net photosynthetic rates showed continuous increases from a C3 state, across the intermediates and towards C4 photosynthesis, but only C4-like intermediates and C4 species (with an operational C4 cycle) had higher water use efficiencies than C3 Flaveria. The results demonstrate that both the marginal water use efficiency and the C4 pump strength increase in C4 Flaveria to improve their photosynthesis and water use efficiency compared with C3 species. These findings emphasize that the advantage of the early intermediate stages is predominantly carbon based, not water related.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".