Temperature effects on wood anatomy, wood density, photosynthesis and biomass partitioning of Eucalyptus grandis seedlings
Bibliographic record
Abstract
Wood density, a gross measure of wood mass relative to wood volume, is important in our understanding of stem volume growth, carbon sequestration and leaf water supply. Disproportionate changes in the ratio of wood mass to volume may occur at the level of the whole stem or the individual cell. In general, there is a positive relationship between temperature and wood density of eucalypts, although this relationship has broken down in recent years with wood density decreasing as global temperatures have risen. To determine the anatomical causes of the effects of temperature on wood density, Eucalyptus grandis W. Hill ex Maiden seedlings were grown in controlled-environment cabinets at constant temperatures from 10 to 35 degrees C. The 20% increase in wood density of E. grandis seedlings grown at the higher temperatures was variously related to a 40% reduction in lumen area of xylem vessels, a 10% reduction in the lumen area of fiber cells and a 10% increase in fiber cell wall thickness. The changes in cell wall characteristics could be considered analogous to changes in carbon supply. Lumen area of fiber cells declined because of reduced fiber cell expansion and increased fiber cell wall thickening. Fiber cell wall thickness was positively related to canopy CO2 assimilation rate (Ac), which increased 26-fold because of a 24-fold increase in leaf area and a doubling in leaf CO2 assimilation rate from minima at 10 and 35 degrees C to maxima at 25 and 30 degrees C. Increased Ac increased seedling volume, biomass and wood density; but increased wood density was also related to a shift in partitioning of seedling biomass from roots to stems as temperature increased.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".