To be or not to be? Mating success and survival trade‐offs when switching between alternative reproductive tactics
Bibliographic record
Abstract
Hormones underlie the decision of assuming a territorial or a nonterritorial role, with territorial individuals usually having higher hormonal levels than nonterritorial individuals. As a territorial status is linked to higher mating opportunities, it is unclear why animals do not keep high hormonal levels and one explanation is that this would imply survival costs. We have tested this using males of the territorial damselfly Argia emma in the field. We increased juvenile hormone (JH) levels using methoprene in both territorial and nonterritorial males and predicted that: (i) males will keep (the case of territorial males) or become (the case of nonterritorial males) territorial after hormonal increase, and (ii) there will be an increase in mating success for nonterritorial males only and an impaired survival for both male tactics. Hormonally treated males remained or became territorial but had their survival impaired compared with control groups. Also, hormonally treated, ex-nonterritorial males increased their mating success compared with the other control, nonterritorial males. The reduced survival can be explained proximally by the energy devoted either to the enhanced aggression showed during territory defence or immune function (as detected previously in damselflies). Although nonterritorial males may increase their mating success by switching to a territorial tactic, they are possibly unable to do it naturally as JH is dietary dependent and usually nonterritorial animals are in poorer condition than territorial animals.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".