Ecologically driven selection of nonstructural carbohydrate storage in oak trees
Bibliographic record
Abstract
Leaf habit is a major axis of plant diversity that has consequences for carbon balance since the leaf is the primary site of photosynthesis. Nonstructural carbohydrates (NSCs) produced by photosynthesis can be allocated to storage and serve as a resiliency mechanism to future abiotic and biotic stress. However, how leaf habit affects NSC storage in an evolutionary context has not been shown. Using a comparative physiological framework and an analysis of evolutionary model fitting, we examined if variation in NSC storage is explained by leaf habit. We measured sugar and starch concentrations in 51 oak species (Quercus spp.) growing in a common garden and representing multiple evolutions of three different leaf habits (deciduous, brevideciduous and evergreen). The best fitting evolutionary models indicated that deciduous oak species are evolving towards higher NSC concentrations than their brevideciduous and evergreen relatives. Notably, this was observed for starch (the primary storage molecule) in the stem (a long-term C storage organ). Overall, our work provides insight into the evolutionary drivers of NSC storage and suggests that a deciduous strategy may confer an advantage against stress associated with a changing world. Future work should examine additional clades to further corroborate this idea.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".