Complex patterns of hybridization between exotic and native North American poplar species
Bibliographic record
Abstract
PREMISE OF THE STUDY: Poplars and their hybrids are seen as important candidates for bioenergy initiatives. However, many concerns have been raised about large-scale plantations of new poplar cultivars. The deployment of such plants with novel traits brings the risk of potential spread of novel genome regions (including exotic genes, transgenes, or other heritable modifications) into natural populations of related species. The possibility of introgression is especially high in poplars because reproductive barriers between species are weak. Knowledge of the frequency of hybridization between cultivated trees and natural populations is one important step in the risk-assessment process. • METHODS: We studied the rate of spontaneous hybridization from two sexually mature poplar plantations into adjacent natural populations of Populus deltoides and P. balsamifera. The two plantations, both in eastern Canada, contain many different complex hybrid clones with components from exotic species, mostly P. nigra, P. trichocarpa, and P. maximowiczii. We analyzed 12 species-specific single nucleotide polymorphisms from six different genes in 5373 offspring sampled from the natural populations. • RESULTS: Contributions from all three exotics were found in the offspring, confirming low reproductive barriers among poplar species in these sections. The frequency of hybrid offspring varied among pollen donors, recipient populations, and years. • CONCLUSIONS: The remarkably high rate of hybridization that was found in the smallest natural population sampled suggests that small peripheral populations carry a higher risk of introgression. These results could be used as a starting point for developing regulatory guidelines for the introduction of plants with novel traits.
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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 | 0.001 |
| 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".