Increased Photosynthetic Capacity as a Mechanism of Drought Adaptation in C<sub>3</sub>Plants
Bibliographic record
Abstract
Premise of research. Plant available soil moisture can influence the evolution of C3 photosynthesis in multiple ways. Water limitation could select for enhanced photosynthetic capacity in order to overcome stomatal limitations to CO2 supply. Alternatively, moisture-limited soils may select for reduced photosynthetic capacity because of the high costs of investment in N-rich Rubisco under chronic CO2 limitation.Methodology. Using literature data on photosynthetic capacity, phylogenetic information, and georeferenced climate records, we assessed the magnitude and direction of the relationship between photosynthetic capacity, as described by the carboxylation capacity of Rubisco (Vcmax) and annual precipitation (MAP). We also examined the association between leaf nitrogen content expressed on leaf area and leaf mass bases (Nmass and Narea, respectively) and MAP.Pivotal results. Both Vcmax and Nmass increased with decreasing MAP, a finding that was relatively consistent across growth forms, including deciduous and evergreen angiosperms. There was no association between Narea and MAP.Conclusions. Selection by dry environments may be responsible for the evolution of increased photosynthetic capacity and leaf N content in C3 plants despite potential metabolic costs of maintaining high investment in N-rich Rubisco. Greater photosynthetic capacity can maximize photosynthetic carbon gain per unit water transpired, making it an important adaptation to arid/semiarid environments.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".