Past and present resource availability affect mating rate but not mate choice in Drosophila melanogaster
Bibliographic record
Abstract
The choices of when, where, and with whom to mate represent some of the most important decisions an individual can make to increase their fitness. Several studies have shown that the resources available to an individual during development can dramatically alter their mating rate later in life, and even the choice of mate. However, an individual’s surroundings and available resources can change rapidly, and it is not clear how quickly the redistribution of resources towards reproduction can change. To address this important question, we measured mating rate and mate choice among Drosophila melanogaster males that were manipulated in terms of both past resources (control vs. starvation) and the resources available during mate choice (food vs. no food). We found that males given access to ample resources prior to mate choice showed higher mating rates than those that were starved, in agreement with previous studies. However, we also found that this effect can be reversed quickly, as starved males given the opportunity to mate in a high-quality environment mated at frequencies equivalent to their fed counterparts. Although past and present resources affected mating rate, they did not affect mate choice, as males mated with high-quality females at high frequencies regardless of their condition and environment. Our results show that both current condition as well as the promise of future resources can dramatically influence individuals’ investment into reproduction and that such mating decisions are extremely plastic and reliant on environmental cues.
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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".