Lazy males? Bioenergetic differences in energy acquisition and metabolism help to explain sexual size dimorphism in percids
Bibliographic record
Abstract
1. Differences in energy use between genders is a probable mechanism underlying sexual size dimorphism (SSD), but testing this hypothesis in the field has proven difficult. We evaluated this mechanism as an explanation for SSD in two North American percid species--walleye Sander vitreus and yellow perch Perca flavescens. 2. Data from 47 walleye and 67 yellow perch populations indicated that SSD is associated with the onset of maturation: typically, males of both species matured smaller and earlier and attained a smaller asymptotic size than females. Males also demonstrated equal (perch) or longer (walleye) reproductive life spans compared with females. 3. To examine whether reduced post-maturation growth in males was due to lower energy acquisition or higher reproductive costs we applied a contaminant mass-balance model combined with a bioenergetics model to estimate metabolic costs and food consumption of each sex. Mature males exhibited lower food consumption, metabolic costs and food conversion efficiencies compared with females. 4. We propose that slower growth in males at the onset of maturity is a result of decreased feeding activity to reduce predation risk. Our finding that SSD in percids is associated with the onset of maturity is supported by laboratory-based observations reported elsewhere, showing that changes in growth rate, consumption and food conversion efficiency were elicited by oestrogen (positive effects) or androgen (negative effects) exposure in P. flavescens and P. fluviatilis. 5. Researchers applying bioenergetic models for comparative studies across populations should use caution in applying bioenergetic models in the absence of information on population sex ratio and potential differences between the sexes in energetic parameters.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".