Variation in Platycladus orientalis (Cupressaceae) Reproductive Output and Its Effect on Seed Orchard Crops’ Genetic Diversity
Bibliographic record
Abstract
The genetic efficiency of seed orchards is crucial for determining seed crops’ genetic gain and diversity. Platycladus orientalis is a conifer tree of important ecological value in China. Here, we assessed the reproductive output (fertility) variation for 166 clones in a first-generation P. orientalis seed orchard over five years and across three years for each gender (female: 2017, 2018, and 2020 and male: 2017, 2019, and 2021). Fertility variation and genetic diversity parameters were estimated for each gender-year combination. The reproductive output (fertility) variation differed among years, provinces, clones nested within provinces, and ramets within clones. We observed asymmetry in the gender reproductive output and parental imbalance and determined their profound effects on the genetic diversity of these seed crops. The maleness index revealed the existence of female-biased or male-biased clones. When seeds from multiple individuals and years were blended, we found an increase in the effective number of parents (Np) and in genetic diversity (GD), and a reduced fertility variation (Ψ) in the seed orchard. When we set the effective number of parents (Np) to 30, the GD of the seed orchard could be maintained at more than 95%. Thus, achieving genetic diversity balance in seed production can be accomplished through monitoring the fertility variation of orchards and through the utilization of the thereby generated information for the advanced generation of seed orchards.
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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".