The positive correlation between maternal size and offspring size: fitting pieces of a life‐history puzzle
Bibliographic record
Abstract
The evolution of investment per offspring (I) is often viewed through the lens of the classic theory, in which variation among individuals in a population is not expected. A substantial departure from this prediction arises in the form of correlations between maternal body size and I, which are observed within populations in virtually all taxonomic groups. Based on the generality of this observation, we suggest it is caused by a common underlying mechanism. We pursue a unifying explanation for this pattern by reviewing all theoretical models that attempt to explain it. We assess the generality of the mechanism upon which each model is based, and the extent to which data support its predictions. Two classes of adaptive models are identified: models that assume that the correlation arises from maternal influences on the relationship between I and offspring fitness [w(I)], and those that assume that maternal size influences the relationship between I and maternal fitness [W(I)]. The weight of evidence suggests that maternal influences on w(I) are probably not very general, and even for taxa where maternal influences on w(I) are likely, experiments fail to support model predictions. Models that assume that W(I) varies with maternal size appear to offer more generality, but the current challenge is to identify a specific and general mechanism upon which W(I) varies predictably with maternal size. Recent theory suggests the exciting possibility that a yet unknown mechanism modifies the offspring size-number trade-off function in a manner that is predictable with respect to maternal size, such that W(I) varies with size. We identify two promising avenues of inquiry. First, the trade-off might be modified by energetic costs that are associated with the initiation of reproduction ('overhead costs') and that scale with I, and future work could investigate what specific overhead costs are generally associated with reproduction and whether these costs scale with I. Second, the trade-off might be modified by virtue of condition-dependent offspring provisioning coupled with metabolic factors, and future work could investigate the proximate cause of, and generality of, condition-dependent offspring provisioning. Finally, drawing on the existing literature, we suggest that maternal size per se is not causatively related to variation in I, and the mechanism involved in the correlation is instead linked to maternal nutritional status or maternal condition, which is usually correlated with maternal size. Using manipulative experiments to elucidate why females with high nutritional status typically produce large offspring might help explain what specific mechanism underlies the maternal-size correlation.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".