Interspecies reproductive interactions and the evolution of plant and animal mating systems. A commentary on Clo et al. (2025)
Bibliographic record
Abstract
The selective forces that influence mating-system evolution are most often considered using a within-species context. Reproductive interactions, however, also can involve related species and can influence the evolutionary trajectories of diverse mating-related traits and the genetic composition of interacting species. The ecological conditions associated with selection for reproductive assurance in plants and animals also are conditions that are likely to result in interspecies reproductive interactions. In this commentary, I explore a variety of factors that link mating-system evolution and interspecies reproductive interactions, including genetic introgression by hybridization, extinction-by-fusion ("genetic swamping"), evolutionary rescue, pre-zygotic reproductive interference between species, and persistent incomplete assortative mating between species and in hybrid zones. A particular focus aims to make the case that reproductive interference holds the potential to foster the evolution of selfing syndrome traits as a form of reproductive character displacement rather than purely as adaptations for reproductive assurance per se. Although interactions among individuals within-species remain central to understanding mating-system evolution, a variety of interspecific factors are also likely to contribute to realized patterns of mating in both plant and animal taxa, especially under conditions of conspecific mate limitation that impose selection for reproductive assurance.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.037 | 0.028 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".