Evidence of multiple paternity and mate selection for inbreeding avoidance in wild eastern chipmunks
Bibliographic record
Abstract
Mate selection for inbreeding avoidance is documented in several taxa. In mammals, most conclusive evidence comes from captive experiments that control for the availability of mates and for the level of genetic relatedness between mating partners. However, the importance of mate selection for inbreeding avoidance as a determinant of siring success in the wild has rarely been addressed. We followed the reproduction of a wild population of eastern chipmunks (Tamias striatus) during five breeding seasons between 2006 and 2009. Using molecular tools and parentage assignment methods, we found that multiple paternity (among polytocous litters) varied from 25% in an early-spring breeding season when less than a quarter of females in the population were reproductively active to 100% across three summer breeding seasons and one spring breeding season when more than 85% of females were reproductively active. Genetically related parents were common in this population and produced less heterozygous offspring. Furthermore, litters with multiple sires showed a higher average relatedness among partners than litters with only a single sire. In multiply sired litters, however, males that were more closely related to their partners sired fewer offspring. Our results corroborate findings from captive experiments and suggest that selection for inbreeding avoidance can be an important determinant of reproductive success in wild mammals.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".