The influence of relatedness on parental reproductive success and offspring fitness in Eastern chipmunks breeding in fluctuating environments
Bibliographic record
Abstract
Mate choice and multiple paternity have been widely studied in natural populations, especially in research assessing inbreeding avoidance mechanisms. Ecological factors are expected to affect the costs and benefits of mate choice and multiple paternity, for instance, through their effects on the availability of partners. However, the relative importance and variation of those costs/benefits across fluctuating environmental contexts remains to be established. Here, we used reproduction data collected over 18 years on a wild population of Eastern chipmunks (Tamias striatus) to assess the influence of relatedness among mating partners on their reproductive success and on their offspring fitness in different breeding contexts. In southern Québec, chipmunks live in a pulse resource system where they anticipate masting events of the American beech (Fagus grandifolia) and breed during the summer preceding and/or the spring following a mast. We found that, within a litter, less genetically related sires were assigned more offspring than more closely related ones. This relationship was significant during the summer breeding seasons only, which is characterized by high availability of food and mating partners in the environment. Multiple paternity was also more frequent during summer breeding than during spring breeding. We found no additional effect of parental relatedness on the juvenile survival, longevity, or reproductive success of their offspring. Our results could suggest the presence of context-specific inbreeding avoidance mechanisms by females or differential mortality of offspring at early stages linked to inbreeding depression. Altogether, our findings provide a better understanding of the influence of fluctuating environments on reproduction in small 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 | 0.000 |
| 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".