Maternal weight, offspring competitive ability, and the evolution of communal breeding
Bibliographic record
Abstract
Despite the widespread occurrence of communal breeding in animal societies, the fitness consequences for mothers are poorly understood. One factor that may have an important influence on the net benefits mothers gain from breeding communally is the competitive ability of their offspring, as mothers are likely to gain substantial advantages from producing young who can outcompete the offspring of other females for access to resources. Here, we investigate the factors that influence offspring competition in the communally breeding banded mongoose (Mungos mungo). We show that heavy offspring are more likely to win competitive interactions with their littermates. Heavy offspring also receive more care and are more likely to survive to independence in large communal litters where competition is most intense. Our results also indicate that offspring weight at emergence is positively correlated with the weight of the mother at conception. As a consequence, the offspring of heavy mothers are likely to enjoy marked competitive advantages during early life. Together, our findings strongly suggest that the competitive ability of offspring will influence the costs and benefits that females experience while breeding communally and highlights the need for closer examination of the factors that influence offspring competitive ability and the influence this may have on the evolution of communal breeding.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".