Condition-dependent ejaculate size and composition in a ladybird beetle
Bibliographic record
Abstract
Sexually selected male ejaculate traits are expected to depend on the resource state of males. Theory predicts that males in good condition will produce larger ejaculates, but that ejaculate composition will depend on the relative production costs of ejaculate components and the risk of sperm competition experienced by low- and high-condition males. Under some conditions, when low condition leads to poorer performance in sperm competition, males in low condition may produce ejaculates with higher sperm content relative to their total ejaculate and may even transfer more sperm than high-condition males in an absolute sense. Previous studies in insects have shown that males in good condition transfer larger ejaculates or more sperm, but it has not been clear whether increased sperm content represents a shift in allocation or simply a larger ejaculate, and thus the condition dependence of ejaculate composition has been largely untested. We examined condition dependence in ejaculate by manipulating adult male condition in a ladybird beetle (Adalia bipunctata) in which males transfer three distinct ejaculate components during mating: sperm, non-sperm ejaculate retained within the female reproductive tract, and a spermatophore capsule that females eject and ingest following mating. We found that high condition males indeed transferred larger ejaculates, potentially achieved by an increased rate of ejaculate transfer, and allocated less to sperm compared with low-condition males. Low-condition males transferred ejaculates with absolutely and proportionally more sperm. This study provides the first experimental evidence for a condition-dependent shift in ejaculate composition.
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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 | 0.000 |
| 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".