Alternative male reproductive tactics drive asymmetrical hybridization between sunfishes ( <i>Lepomis</i> spp.)
Bibliographic record
Abstract
The potential role of alternative reproductive tactics in circumventing premating isolating mechanisms and driving hybridization between species has long been recognized, but to date there is little empirical support from natural systems. Hybridization occurs between bluegill (Lepomis macrochirus) and pumpkinseed sunfish (Lepomis gibbosus) and it is known to be asymmetrical (male bluegill × female pumpkinseed). Here, we test whether this pattern is driven by a recognition failure by pumpkinseed females or by an alternative cuckolder reproductive tactic in bluegill males. Using genetic parentage data, we found that bluegill cuckolders fathered 24.9% of the larvae in bluegill nests, but no evidence that pumpkinseed females spawned in bluegill nests. Pumpkinseed cuckolders fathered 8.7% of the larvae in pumpkinseed nests, whereas bluegill cuckolders fathered 13.6% of the larvae in those nests. Bluegill cuckolders thus frequently spawn in pumpkinseed nests and are responsible for the asymmetrical hybridization between the species. We discuss the evolutionary consequences of interactions between bluegill and pumpkinseed and the role of alternative reproductive tactics in adaptation and introgression.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".