A Tale of Two Morphs: Modeling Pollen Transfer, Magic Traits, and Reproductive Isolation in Parapatry
Bibliographic record
Abstract
The evolution of the flower is commonly thought to have spurred angiosperm diversification. Similarly, particular floral traits might have promoted diversification within specific angiosperm clades. We hypothesize that traits promoting the precise positional transfer of pollen between flowers might promote diversification. In particular, precise pollen transfer might produce partial reproductive isolation that facilitates adaptive divergence between parapatric populations differing in their reproductive-organ positions. We investigate this hypothesis with an individual-based model of pollen transfer dynamics associated with heterostyly, a floral syndrome that depends on precise pollen transfer. Our model shows that precise pollen transfer can cause sexual selection leading to divergence in reproductive-organ positions between populations served by different pollinators, pleiotropically causing an increase in reproductive isolation through a "magic trait" mechanism. Furthermore, this increased reproductive isolation facilitates adaptive divergence between the populations in an unlinked, ecologically selected trait. In a different pollination scenario, however, precise pollen transfer causes a decrease in adaptive divergence by promoting asymmetric gene flow. Our results highlight the idea that magic traits are not "magic" in isolation; in particular, the effect size of magic traits in speciation depends on the external environment, and also on other traits that modify the strength of the magic trait's influence on non-random mating. Overall, we show that the evolutionary consequences of pollen transfer dynamics can depend strongly on the available pollinator fauna and on the morphological fit between flowers and pollinators. Furthermore, our results illustrate the potential importance of even weak reproductive isolating barriers in facilitating adaptive divergence.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".