Developmental environment mediates male seminal protein investment in <i><scp>D</scp>rosophila melanogaster</i>
Bibliographic record
Abstract
Summary Males of many species fine‐tune their ejaculates in response to sperm competition risk. Resource availability and the number of competitors during development can also strongly influence sperm production. However, despite the key role of seminal proteins in mediating reproductive processes, it is unclear whether seminal protein investment is dependent on the developmental environment. We manipulated the developmental environment of Drosophila melanogaster by rearing flies at low and high density. As expected, this resulted in large and small (i.e. high and low condition) adult phenotypes, respectively. As predicted, large males produced more of two key seminal proteins, sex peptide (SP) and ovulin, and were more successful at obtaining matings with both virgin and previously mated females. However, there was only a weak and non‐significant trend for large males to transfer more absolute quantities of SP at mating, and thus, small males ejaculated proportionally more of their stored accessory gland SP resources. Males transferred more receptivity‐inhibiting SP to large females. Despite this, large females remated more quickly than small females and thus responded to their developmental environment over and above the quantity of SP they received. The results are consistent with two non‐mutually exclusive hypotheses. First, flies might respond to condition‐dependent reproductive opportunities, with (i) small males investing heavily in ejaculates when mating opportunities arise and large males strategically partitioning SP resources and (ii) small females remating at reduced rates because they have higher mating costs or need to replenish sperm less often. Second, flies may be primed by their larval environment to deal with similar adult population densities, with (i) males perceiving high density as signalling increased competition, leading small males to invest proportionally more SP resources at mating and (ii) females perceiving high density as signalling abundant potential mates, leading to a higher sexual receptivity threshold. Thus, by influencing the mating frequencies of both sexes, as well as the quantity of seminal proteins produced by males and received by females, the developmental environment is likely to have far‐reaching and sex‐specific consequences for sexual selection and sexual conflict.
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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) | 0.002 | 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".