Quality not Quantity: Seedlings of the Invasive Hybrid Cattail Typha x glauca Outcompete the more Abundant Seedlings of their Maternal Parent T. angustifolia
Bibliographic record
Abstract
Abstract Numerous invasive plant taxa are hybrids that outcompete their parent species, thus exhibiting heterosis. Invasive hybrids can also have an advantage if the genotypes of one or both parent species are replaced by hybrid genotypes (genetic swamping), which can remove or reduce the parental competitors. A vast cattail hybrid zone in North America comprises T. latifolia, T. angustifolia, and their hybrid T. x glauca. Genetic swamping may be reducing the abundance of the maternal parent, T. angustifolia across the hybrid zone, although competition could also be important for hybrid success. We tested two non-mutually exclusive hypotheses: 1) Genetic swamping means that T. angustifolia is producing a high proportion of hybrid offspring, and 2) T. × glauca seedlings outcompete T. angustifolia seedlings. We collected fruit from 14 maternal T. angustifolia plants across 12 sites in Ontario, Canada, and grew seedlings from each plant both singly (without competition) and in groups (with competition). We used genetic data to assign a subset of seedlings to taxon and found that most seedlings (78%) were T. angustifolia, which does not support our hypothesis of genetic swamping. However, a significantly higher proportion of seedlings were hybrids in the competitive (29%) versus the non-competitive (14%) environment, which supports our hypothesis that T. x glauca seedlings outcompete T. angustifolia seedlings. Typha hybrids dominate wetlands across a substantial area in North America, and our data suggest that strong competitive ability is more important than genetic swamping for the establishment of these successful invaders.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".