Strategies for a successful plant invasion: the reproduction of <i>Phragmites australis</i> in north‐eastern North America
Bibliographic record
Abstract
Summary Knowing the relative contribution of vegetative propagation and sexual reproduction to the dispersal and establishment of exotic plants is crucial for devising efficient control strategies. This is particularly true for the common reed ( Phragmites australis ), one of the most invasive species in North America. For the first time, we combined in situ field observations and genetic evidence, based on two genotyping techniques, that is microsatellite markers ( SSR ) and genotyping by sequencing ( GBS ), to determine the propagation strategies of this invader at its northern distribution limit in North America and especially in roadside ditches. Field observations revealed that, in a region where the common reed is already abundant, both seeds and plant fragments contributed to the establishment of new populations. Newly established individuals originated mostly (84%) from seeds rather than fragments, but a larger proportion of individuals originating from fragments survived the second year compared to seedlings. High genetic diversity among marsh and roadside common reed stands indicated the prime role of sexual reproduction for dispersal. The vast majority of genotypes were found in only one stand; such high genetic variability can only be explained by sexual reproduction. Half the surveyed stands comprised a single clone, suggesting that local expansion mainly occurred vegetatively. As the small proportion of SSR genotypes initially thought to be common between distant stands proved to be distinct (as revealed by GBS data), it is likely that all the stands examined were initially founded by genetically distinct individuals. Synthesis . Our study suggests that long‐distance dispersal by seeds is important for the common reed, in marshes and roadsides, while both seeds and plant fragments contribute to short‐distance dispersal along roads, at least in regions where the species is already abundant. The success of this invader in North America seems to be attributable to a reproduction strategy combining the advantages of sexuality with those of vegetative propagation. Moreover, this study shows that the GBS approach strongly reduces uncertainties associated with the use of a limited number of markers. This approach is especially valuable for ecologists dealing with an ever‐increasing number of invaders, of which few have identified microsatellite markers.
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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 | 0.001 | 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".