Early growth trajectories affect sexual responsiveness
Bibliographic record
Abstract
The trajectory of an animal's growth in early development has been shown to have long-term effects on a range of life-history traits. Although it is known that individual differences in behaviour may also be related to certain life-history traits, the linkage between early growth or development and individual variation in behaviour has received little attention. We used brief temperature manipulations, independent of food availability, to stimulate compensatory growth in juvenile three-spined sticklebacks Gasterosteus aculeatus. Here, we examine how these manipulated growth trajectories affected the sexual responsiveness of the male fish at the time of sexual maturation, explore associations between reproductive behaviour and investment and lifespan and test whether the perceived time stress (until the onset of the breeding season) influenced such trade-offs. We found a negative impact of growth rate on sexual responsiveness: fish induced (by temperature manipulation) to grow slowest prior to the breeding season were consistently quickest to respond to the presence of a gravid female. This speed of sexual responsiveness was also positively correlated with the rate of development of sexual ornaments and time taken to build a nest. However, after controlling for effects of growth rate, those males that had the greatest sexual responsiveness to females had the shortest lifespan. Moreover, the time available to compensate in size before the onset of the breeding season (time stress) affected the magnitude of these effects. Our results demonstrate that developmental perturbations in early life can influence mating behaviour, with long-term effects on longevity.
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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".