Predominant paternal inheritance pattern of light-energy processing adaptive traits in red and black spruce hybrids
Bibliographic record
Abstract
Ecophysiological traits related to light-energy processing and freezing tolerance are important adaptive traits in plants. Our goal was to investigate the pattern of inheritance of these traits in hybrids using controlled intra- and inter-specific crosses of red spruce ( Picea rubens Sarg.) (RS) and black spruce ( Picea mariana (Mill.) BSP) (BS). Our initial working hypothesis was that expected hybrid index categories could be a predictor of adaptive traits. Species results of dark-adapted photochemical efficiency (Fv/Fm) and light-adapted light-energy processing traits, quantum yield (YLD), thermal dissipation efficiency (qN), and chlorophyll fluorescence (Fpc), were consistent with previously published open-pollinated, species provenance results. Initially, YLD, qN, and Fpc, showed an additive inheritance pattern, evident by average hybrid index 50 having a mid-parent value. Because of various crosstypes of the hybrid families, parental analysis, testing male, female, and interaction effects, and having three categories (pure RS, pure BS, and hybrid spruce), revealed significant male and nonsignificant female and interactive effects. Underlying the averaged additive results was a significant species-specific paternal inheritance pattern. Crosses with BS males had 13.7% higher YLD (P = 0.001), 15.4% lower qN (P = 0.008), and 43.0% higher Fpc (P = 0.096) than crosses with either RS or hybrid males. Fv/Fm showed a nonadditive or parental species pattern. Parental analysis of Fv/Fm showed significant male, female, and male × female interaction effects, and further analysis supports a largely species-specific and paternally inherited trait. Freezing tolerance revealed a mixed model of inheritance dominated by species effects. Total dry mass was positively correlated with YLD, and negatively correlated with Fv/Fm and qN, suggesting a biological tradeoff. We know of no other studies in trees demonstrating paternal inheritance of ecophysiological processes that affect adaptation and fitness.
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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".