Territory defense as a condition-dependent component of male reproductive success in<i>Drosophila serrata</i>
Bibliographic record
Abstract
Sexual selection arises from both intrasexual competition and mate choice. With respect to the evolution of male traits, there is a vast literature documenting the existence of female choice and male-male competition, and both have been shown to co-occur in many species. Despite numerous studies of these two components of male reproductive success in isolation, few have investigated whether and how they interact to determine total sexual selection. To address this, we investigate male territoriality in Drosophila serrata, a species in which female preference for male sexual pheromones (cuticular hydrocarbons or CHCs) have been extensively studied. We demonstrate that territoriality occurs, that it involves direct male-male aggressive interactions, and that it contributes to variation in male mating success. Results from a phenotypic manipulation also indicate that territorial success is condition-dependent, although a genetic manipulation of condition, involving three generations of full-sib inbreeding, failed to find a significant effect. Finally, selection assays also suggest that territorial success depends on male body size but not on CHCs, whereas the opposite is true for mating success.
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".