Geographical and environmental gradients shape phenotypic trait variation and genetic structure in <i><scp>P</scp>opulus trichocarpa</i>
Bibliographic record
Abstract
• Populus trichocarpa is widespread across western North America spanning extensive variation in photoperiod, growing season and climate. We investigated trait variation in P. trichocarpa using over 2000 trees from a common garden at Vancouver, Canada, representing replicate plantings of 461 genotypes originating from 136 provenance localities. • We measured 40 traits encompassing phenological events, biomass accumulation, growth rates, and leaf, isotope and gas exchange-based ecophysiology traits. With replicated plantings and 29,354 single nucleotide polymorphisms (SNPs) from 3518 genes, we estimated both broad-sense trait heritability (H(2)) and overall population genetic structure from principal component analysis. • Populus trichocarpa had high phenotypic variation and moderate/high H(2) for many traits. H(2) ranged from 0.3 to 0.9 in phenology, 0.3 to 0.8 in biomass and 0.1 to 0.8 in ecophysiology traits. Most traits correlated strongly with latitude, maximum daylength and temperature of tree origin, but not necessarily with elevation, precipitation or heat : moisture indices. Trait H(2) values reflected trait correlation strength with geoclimate variables. The population genetic structure had one significant principal component (PC1) which correlated with daylength and showed enrichment for genes relating to circadian rhythm and photoperiod. • Robust relationships between traits, population structure and geoclimate in P. trichocarpa reflect patterns which suggest that range-wide geographical and environment gradients have shaped its genotypic and phenotypic variability.
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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 | 0.001 |
| 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) | 0.001 | 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".