Does individual personality predict male mating preference for female body size in the Trinidadian guppy?
Bibliographic record
Abstract
Abstract Within populations, individual animals vary considerably in their behaviour, including mate choice and personality. There is mounting interest in the potential covariation between these two behaviours within individuals, such that personality would influence mate choice. We experimentally tested this proposition under controlled laboratory conditions using male Trinidadian guppies (Poecilia reticulata) as a model study system. We assayed repeatedly the mating preference of individual males for females based on their body size. Additionally, we assayed repeatedly two ecologically relevant personality traits in males, namely exploration of a novel environment and boldness under a simulated predation threat. Finally, we analysed whether male mating preference and personality traits were repeatable, and tested whether the personality of individual males was correlated (covaried) with their mating preference scores. Although all but one of the measures of exploration and boldness behaviour were repeatable over time, male mating preference scores were not repeatable. Measures of male exploration and boldness were not inter‐correlated among individuals, suggesting the absence of a behavioural syndrome between exploration and boldness. Unexpectedly, males did not exhibit on average a significant mating preference for larger females over smaller ones; they chose randomly between the paired stimulus females. Overall, we found no compelling evidence for a relationship between individual personality traits and mating preference in male guppies, suggesting that personality does not predict mate choice, at least in our study population and under our experimental conditions. We discuss potential factors, other than male personality and body length, that might maintain inter‐individual variation in male mating preferences in the guppy in the wild.
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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 | 0.000 | 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".