Genetic variation in basal area increment phenology and its correlation with growth rate in loblolly and slash pine families and clones
Bibliographic record
Abstract
We quantified basal area increment phenology over a 2-year period in one loblolly pine (Pinus taeda L.) and four slash pine (Pinus elliottii Engelm. var. elliottii) full-sib families propagated as rooting cuttings. In 2002, basal area growth started in March and stopped in October for both species, while in 2003, initiation and cessation occurred 2 weeks earlier for all families. In both years, peaks in basal area increment occurred in short (23 week) periods in the early spring for all families, followed by linear basal area growth until cessation. While there were significant size differences among taxa (species and families) at age 6 and 7 years, genetic differences in basal area growth rate were only expressed during short, discrete time periods primarily in the spring and fall. Basal area growth rate increased during periods when water soil availability increased (up to 300 mm), but an excess in water availability in the soil had a negative impact on growth. Within-family individual-tree broad-sense heritabilities ranged from 0.01 to 0.37 for all traits. In general, heritabilities were higher for growth traits than for phenological traits for all families. Both the strength and direction of correlation estimates of phenological traits with growth rate varied across families and years.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".