The ecology of polyploid establishment and exclusion, with implications for polyploid biogeography
Bibliographic record
Abstract
The relationship between polyploid formation, triploid fitness and plant reproduction has been studied for over a century, and uniparental reproduction has long been recognized to play a crucial role in polyploid establishment. Yet, we lack a synthesized framework of how polyploid establishment is expected to be influenced by different reproductive modes among angiosperms. Here, we provide new perspectives on how uniparental reproduction, pollination ecology, triploid fitness and assortative mating can impact minority cytotype exclusion (MCE) and, thereby, the likelihood of polyploid establishment. We review the current state of knowledge of the reproductive mechanisms that impact polyploid establishment and discuss often overlooked aspects of these processes, such as the influence of pollinator communities on rates of self-pollination. We propose a framework for considering how variation in reproductive strategies and pollinator communities can impact the ability of a polyploid to overcome MCE. Finally, we propose links between patterns of variation in uniparental reproduction across plant communities and observed patterns in the distribution and abundance of polyploids.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".