Growth parameters and resistance to Sphaerulina musiva-induced canker are more important than wood density for increasing genetic gain from selection of Populus spp. hybrids for northern climates
Bibliographic record
Abstract
Abstract Key message New genotypes of hybrid poplars from the Aigeiros and Tacamahaca sections have great potential for increasing genetic gain from selection. The most promising traits are associated with productivity and resistance to Sphaerulina musiva -induced canker while wood density can be selected for secondarily. A minimum age of 8 years is reliable to select fast-growing resistant clones in northern climates. Context Productivity, wood density, and disease resistance of hybrid poplar clones are important traits when selecting for cultivation at an industrial scale. Aims We studied 1978 hybrid poplar clones from 63 families, bred from poplars native ( Populus balsamifera and Populus deltoides ) and non-native to Canada from the Aigeiros and Tacamahaca sections, to improve economically important traits for plantations in northern Alberta. Methods Genetic parameters for diameter at breast height (DBH), height, resistance to Sphaerulina musiva -induced canker, and wood density were determined up to age 10. Results A mean annual increment of 16.5 m 3 ha −1 year −1 was achieved at age 10 in the best-performing clones. The potential genetic gain for DBH, height, and canker resistance, 37%, 26%, and ~ 13%, respectively, was achieved when selecting the top 10% of the tested clones. The genetic effect for wood density was weak. The age-age genetic correlations identified age eight as a reliable selection age. Conclusion The new hybrid poplar clones tested exhibited great potential for tree improvement. The next phase of selection should test a reduced number of clones on different site types, identifying stable clones for productivity and resistance, while wood density can be selected for secondarily. In northern regions, a minimum age of 8 years is reliable to select fast-growing resistant clones for commercial deployment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".