Size is not everything: Nuanced effects of female multiple mating and annual litter number on testes size in terrestrial mammals
Bibliographic record
Abstract
Abstract Sperm production represents a costly reproductive investment by males. High reproductive competition within the female reproductive tract may select for higher sperm counts or quality resulting in selection for larger testes size. In species where females mate multiply or have more offspring per litter (litter size), or more litters per year (litter rate), male reproductive competition may select for larger relative testes size (i.e., scaled by body mass). Given that different mating systems vary in the alternative forms of reproductive investment available to males, sperm production levels may vary with social system. Here, we examined the relationship between testes size and mating systems, litter size, and litter rate while considering male lifespan and investment in paternal care in 224 terrestrial mammalian species in 15 orders. Relative testes size was larger in species where females mated with multiple males. Furthermore, in species with multiple mating females, species with higher litter rates had larger testes compared to species with fewer litters per year. In contrast, in monogamous species, species that had multiple litters per year had smaller relative testes sizes compared to species with fewer litters per year. Neither longevity nor paternal care influenced testes size. Our results elucidate the effect of female reproductive strategies on relative testes size is nuanced and varies between mating systems. Our findings suggest that the interplay between male reproductive investment and female reproductive investment may be different within similar social mating systems.
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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) | 0.001 | 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".