Hybridization between the escaped <i>Rosa rugosa</i> (Rosaceae) and native <i>R</i>. <i>blanda</i> in eastern North America
Bibliographic record
Abstract
Rosa rugosa, a vigorous ornamental shrub introduced from Asia in the 19th century, is now naturalized in coastal northeastern North America, where it occasionally grows in sympatry with the native R. blanda. To document hybridization between these species, evaluate its extent across the area of sympatry, and examine the use of morphology as a field monitoring tool, we sampled 179 individuals of parental species and putative hybrids in 13 pure and 11 mixed populations. We developed allele-specific primers to assay single nucleotide polymorphisms (SNPs) markers from one chloroplast region and four low-copy nuclear introns. Our results revealed frequent bidirectional hybridization and infrequent introgression in sympatric populations of these species. The recurrent presence of F(1) hybrids in mixed populations indicated the weakness of early-acting reproductive barriers. Morphological data were concordant with molecular data and provided additional evidence for the presence of a few backcrosses. Morphological analyses yielded diagnostic characters for identifying hybrids and monitoring the hybrid zone. Such hybridization could ultimately lead to the genetic assimilation of R. blanda in mixed populations and to the formation of invasive hybrid genotypes, a phenomenon that is of economic and ecological concern because of the increasing number of exotic species worldwide.
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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 | 0.001 |
| 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 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".