Functional trade-offs in volume allocation to xylem cell types in 75 species from the Brazilian savanna Cerrado
Bibliographic record
Abstract
BACKGROUND AND AIMS: Xylem is a crucial tissue for plant survival, performing the functions of water transport, mechanical support and storage. Functional trade-offs are a result of the different assemblages of xylem cell types within a certain wood volume. We assessed how the volume allocated to different xylem cell types can be associated with wood functional trade-offs (hydraulics, mechanical and storage) in species from the Cerrado, the Brazilian savanna. We also assessed the xylem anatomical characters linked to wood density across species. METHODS: We analysed cross-sections of branches collected from 75 woody species belonging to 42 angiosperm families from the Cerrado. We estimated the wood volume fraction allocated to different cell types and performed measurements of vessel diameter and wood density. KEY RESULTS: The largest volume of wood is allocated to fibres (0.47), followed by parenchyma (0.33) and vessels (0.20). Wood density is positively correlated to cell wall (fibre and vessel wall), and negatively to the fractions of fibre lumen and gelatinous fibres. We observed a trade-off between hydraulics (vessel diameter) and mechanics (cell wall fraction), and between mechanics and storage (parenchyma fraction). The expected positive functional relationships between hydraulics (vessel diameter) and water and carbohydrate storage (parenchyma and fibre lumen fractions) were not detected, though larger vessels are linked to a larger wood volume allocated to gelatinous fibres. CONCLUSIONS: Woody species from the Cerrado show evidence of functional trade-offs between water transport, mechanical support and storage. Gelatinous fibres might be potentially linked to water storage and release by their positive relationship to increased vessel diameter, thus replacing the functional role of parenchyma and fibre lumen cells. Species can profit from the increased mechanical strength under tension provided by the presence of gelatinous fibres, avoiding expensive investments in high wood density.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".