Why Does Size Matter? A Test of the Benefits of Female Mate Choice in a Teleost Fish Based on Morphological and Physiological Indicators of Male Quality
Bibliographic record
Abstract
In female mate choice, a female chooses a reproductive partner based on direct or indirect benefits to the female. While sexual selection theory regarding female mate choice is well developed, there are few mechanistic studies of the process by which females evaluate reproductive partners. Using paternal-care-providing smallmouth bass (Micropterus dolomieu) as a model, the purpose of this study was to determine the relationship between female mate choice and the morphological and physiological status of chosen males. This was accomplished by locating nests within 1 d of spawning and categorizing brood size (indicator of female mate choice). This was followed by capture of parental males, which were blood sampled (for nutritional analyses), digitally photographed (for morphometric analyses), and released. Principal components analysis (PCA) of morphometric measurements described 72.7% of the variance associated with body morphology and generated three principal components (PCs) indicative of fusiform body shape, increased posterior size, and body stoutness. PCA of nutritional indicators described 75.4% of the variance associated with physiological metrics and generated two PCs indicative of plasma mineral content (Ca(++) and Mg(+)) and energetic condition (total protein, triglyceride, and cholesterol). Male total length and body stoutness were the only significant predictors of female mate choice. Interestingly, no nutritional indicators were predictive of female mate choice, and there were no direct relationships between morphological variables and nutritional physiology indicators. Further research is needed to elucidate the mechanistic relationships between morphology and nutritional physiology (especially in relation to the parental-care period) of individual fish to determine the basis of female mate preference.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".