The exotic invasive plant Vincetoxicum rossicum is a strong competitor even outside its current realized climatic temperature range
Bibliographic record
Abstract
Dog-strangling vine (Vincetoxicum rossicum) is an exotic plant originating from Central and Eastern Europe that is becoming increasingly invasive in southern Ontario, Canada. Once established, it successfully displaces local native plant species but mechanisms behind this plant’s high competitive ability are not fully understood. It is unknown whether cooler temperatures will limit the range expansion of V. rossicum, which has demonstrated high tolerance for other environmental variables such as light and soil moisture. Furthermore, if V. rossicum can establish outside its current climatic limit it is unknown whether competition with native species can significantly contribute to reduce fitness and slow down invasion. We conducted an experiment to test the potential of V. rossicum to spread into northern areas of Ontario using a set of growth chambers to simulate southern and northern Ontario climatic temperature regimes. We also tested plant-plant competition by growing V. rossicum in pots with a highly abundant native species, Solidago canadensis, and comparing growth responses to plants grown alone. We found that the fitness of V. rossicum was not affected by the cooler climate despite a delay in reproductive phenology. Growing V. rossicum with S. canadensis caused a significant reduction in seedpod biomass of V. rossicum. However, we did not detect a temperature x competition interaction in spite of evidence for adaptation of S. canadensis to cooler temperature conditions. We conclude that the spread of V. rossicum north within the tested range is unlikely to be limited by climatic temperature but competition with an abundant native species may contribute to slow it down.
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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 | 0.000 | 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) | 0.001 | 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".