The Evolutionary Enigma of Mixed Mating Systems in Plants: Occurrence, Theoretical Explanations, and Empirical Evidence
Bibliographic record
Abstract
▪ Abstract Mixed mating, in which hermaphrodite plant species reproduce by both self- and cross-fertilization, presents a challenging problem for evolutionary biologists. Theory suggests that inbreeding depression, the main selective factor opposing the evolution of selfing, can be purged with self-fertilization, a process that is expected to yield pure strategies of either outcrossing or selfing. Here we present updated evidence suggesting that mixed mating systems are frequent in seed plants. We outline the floral and pollination mechanisms that can lead to intermediate outcrossing, review the theoretical models that address the stability of intermediate outcrossing, and examine relevant empirical evidence. A comparative analysis of estimated inbreeding coefficients and outcrossing rates suggests that mixed mating often evolves despite strong inbreeding depression. The adaptive significance of mixed mating has yet to be fully explained for any species. Recent theoretical and empirical work suggests that future progress will come from a better integration of studies of floral mechanisms, genetics, and ecology, and recognition of how selective pressures vary in space and time.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".