Seasonal Variation in Sex Ratios Provides Developmental Advantages in White-tailed Deer, <em>Odocoileus virginianus</em>
Bibliographic record
Abstract
Since Trivers and Willard first proposed their hypothesis concerning the adaptive advantages of producing a particular offspring sex in relation to maternal condition in 1973, it has been at the forefront of scientific research concerning sex ratios with most subsequent studies focusing on maternal condition as a key contributor to variations in sex ratios. Another factor that could greatly influence sex ratios, although has been only infrequently examined in mammalian species, is birth date. We investigated how birth date influenced offspring sex ratios in White-tailed Deer (Odocoileus virginianus). Since date of birth can greatly influence an individual’s fitness and reproductive success, we suggest that birth date may be an alternative strategy in determining offspring sex ratios. Since it has been shown that the lifetime reproductive fitness of a mother can be increased by producing a particular sex during a particular time, we hypothesized that more male offspring should be born earlier in the season due to their increased reproductive potential from being born at this time. Offspring born earlier will have a head start in development and therefore have greater potential for increased body size and dominance later in life, traits that greatly influence male reproductive success. In this study, we found that maternal condition did not affect offspring sex ratio in a captive population of White-tailed Deer in Michigan; however, birth date did. We found that more males tended to be born during the second and fourth birthing periods, while more females were born during the first, third and fifth periods. In addition, we found that males born earlier in the season had greater mass the following spring than those born later, a trend that was not as dramatic in females. These results lend moderate support to our hypothesis that in White-tailed Deer offspring sex will tend to vary according to timing of birth and relative reproductive advantages gained by a particular sex being born at that time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".