Pollination interactions promoting plant invasions.
Bibliographic record
Abstract
Most plant species rely on, or benefit from, animal pollination. Therefore, pollination interactions are expected to play a key role in the reproduction and invasion success of non-native plants in their new areas. Understanding this role will allow us to better predict certain plant invasions. Also, it will allow us to explore the potential of invasion management measures based on disrupting or avoiding pollination interactions. In this chapter we review the available information on reproductive systems and their degree of dependence on animal-mediated pollination of non-native plant species. We review the characteristics of resident pollinators feeding on non-native plants and the different environmental setups that allow or impede non-native plants to reproduce in their new areas. Finally, we explore the scarce literature on invasion management measures based on disrupting pollination interactions and discuss their potentiality. Evidence so far shows that animal pollination does not usually act as an effective barrier to invasion. Most introduced plants are able to receive suitable pollination service from resident pollinators, while others are able to minimize their reliance on pollinators through different mechanisms (e.g. selfing or asexual reproduction). The environmental settings where the introduction occurs (for instance, the presence of neighbours with similar or dissimilar flower morphologies), can play an important role on the success or failure of non-native plants overcoming reproductive barriers. Although it seems that most introduced plants do not face pollination barriers, we consider that, for certain species, the disruption or avoidance of pollination interactions as control or prevention measures deserve further exploration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".