Clonal variation in shoot respiration and tree growth of <i>Eucalyptus</i> hybrids
Bibliographic record
Abstract
Respiration rate and efficiency in growing tissues are major determinants of plant growth. We measured apical shoot respiration and tree growth in 3-year-old clones of Eucalyptus camaldulensis Dehnhardt × Eucalyptus grandis W. Hill ex Maid. and Eucalyptus camaldulensis × Eucalyptus globulus Labill. Respiration was measured by isothermal calorimetry and the oxidation state of newly formed biomass was determined by elemental analysis. We found that the enthalpy change due to conversion of carbon substrate to biomass was too small for determining specific growth rate by an enthalpy balance model of respiration and growth. Negative phenotypic correlations were significant between respiration rate and basal area, height, volume, and volume growth. Genetic correlations between respiration rate and tree size or growth were mostly significant and estimates ranged from –0.55 to –1.02. Repeatability of the clone means was around 0.80 for respiration rate, 0.71–0.91 for summer growth, and in excess of 0.80 for tree size traits. The intraclass correlation for clones (within families) was 0.33 for rate of CO2 evolution and 0.45 for rate of metabolic heat evolution. Our results suggest considerable potential for altering respiration rate in breeding populations by selection, although the mechanisms linking respiration with growth require further investigation.
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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 | 0.001 | 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".