Phylogenetic history of vascular plant metabolism revealed using a macroevolutionary common garden
Bibliographic record
Abstract
While the fundamental biophysics of C 3 photosynthesis is highly conserved across plants, substantial leaf structural and enzymatic variation translates into variability in rates of carbon assimilation. Although this variation is well documented, it remains poorly understood how photosynthetic rates evolve, and whether macroevolutionary changes are related to the evolution of leaf morphology and biochemistry. A substantial challenge in large-scale comparative studies is disentangling evolutionary adaptation from environmental acclimation. We overcome this by using a ‘macroevolutionary common garden’ approach in which we measured metabolic traits ( J max and V cmax ) from 111 phylogenetically diverse species in a shared environment. We find substantial phylogenetic signal in these traits at moderate phylogenetic timescales, but this signal dissipates quickly at deeper scales. Morphological traits exhibit phylogenetic signal over much deeper timescales, suggesting that these are less evolutionarily constrained than metabolic traits. Furthermore, while morphological and biochemical traits (LMA, N area and C area ) are weakly predictive of J max and V c max , evolutionary changes in these traits are mostly decoupled from changes in metabolic traits. This lack of tight evolutionary coupling implies that it may be incorrect to use changes in these functional traits in response to global change to infer that photosynthetic strategy is also evolving.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".