Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat
Bibliographic record
Abstract
Many organisms produce offspring with sex-ratios that deviate from equal numbers of males and females, and numerous adaptive explanations have been proposed. In some species, offspring sex-ratio varies across the reproductive season, again with several explanations as to why this might be adaptive. However, patterns for birds and mammals are inconsistent, and multiple factors are likely involved. Long-term studies on a variety of species may help untangle the complexity. I analyzed a long-term data set on the variation in offspring sex-ratio of the big brown bat, Eptesicus fuscus, a temperate-zone, insectivorous species. Sex ratio varied seasonally, but only in some years. Births early in the season were significantly female biased in years in which parturition occurred relatively early, but not in years with late parturition. Survival of female pups increased with earlier median birth date for the colony, and early-born females were more likely to survive and reproduce as one-year olds, compared to later-born pups. I argue that, due to the unusual timing of reproductive activities in male and female bats that hibernate, producing female offspring early in the year increases their probability of reproducing as one year olds, but this is not the case for male offspring. Thus, mothers that can give birth early in the year, benefit most by producing a female pup. The relative benefit of producing female or male offspring varies depending on the length of the growing season and thus the time available for female pups to reach sexual maturity. This suggests that not only does sex-ratio vary seasonally and among years, depending on the condition of the mother and the environment, but also likely varies geographically due to differences in season length.
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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 | 0.001 | 0.001 |
| 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".