Comparison of competitive behaviours between native and invasive ecotypes of garlic mustard under different density conditions, presence and identity of neighbours
Bibliographic record
Abstract
Invasive species in monocultures in introduced habitats experience different competitive conditions compared with their native habitats. Invasive monospecific stands can be composed of highly related individuals, creating high opportunity for kin selection in invaded habitats. We investigated the responses of North American and European ecotypes of the invasive species garlic mustard ( Alliaria petiolata (M. Bieb.) Cavara & Grande) to aspects of the competitive environment including density, presence and identity of conspecific neighbors. Several aboveground morphological and performance traits responded to density independent of the origin of the plants. Belowground, however, North American ecotypes allocated more resources to roots and particularly to the taproot portion of their root system, while petiole elongation was density-dependent with North American ecotypes showing reduced elongation in high density compared to European ecotypes. These results were consistent with the evolution of reduced competitive ability in garlic mustard and indicated better resource storage in the introduced environment. Differential responses to neighbour identity indicated the ability for kin recognition in this species. Thus, a combination of natural and kin selection favouring better resource storage and less intraspecific competition, aided by the ability for kin recognition, may be responsible for the success of garlic mustard as an invasive species in North America.
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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 | 0.000 |
| 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".