Temporal variation in cuckoldry and paternity in two sunfish species (Lepomis spp.) with alternative reproductive tactics
Bibliographic record
Abstract
Male alternative reproductive tactics have been described in many mating systems. In fishes, these tactics typically involve a territorial male that defends a spawning site or nest and a parasitic male that uses sneaking or female mimicry to steal fertilizations from the territorial male. In this paper, we use molecular genetic markers to examine the success of males that adopt alternative reproductive tactics in two sunfishes, comprising the bluegill ( Lepomis macrochirus Rafinesque, 1819) and the pumpkinseed ( Lepomis gibbosus (L., 1758)). In sunfishes, the tactics are referred to as parental (territorial male) and cuckolder (parasitic male). We show that cuckoldry rates peak in the second trimester of the breeding season in bluegill, whereas cuckoldry rates are lowest during this period in pumpkinseed. We also show that paternity of parental male bluegill is positively correlated with body condition, but not body length or mass. No relationship between these phenotypic variables and paternity in pumpkinseed was found. We discuss the patterns of cuckoldry in relation to differences between the species in mating opportunities, parental male defence ability, and cuckolder density. Finally, we discuss how the paternity data can be used to differentiate between two mechanisms underlying the expression of alternative reproductive tactics, comprising the condition strategy and alternative strategies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".