Early life adversity shapes life history trade-offs between growth and reproduction in free-ranging rhesus macaques
Bibliographic record
Abstract
Life history theory predicts that organisms allocate resources across physiological processes to maximize fitness. Under this framework, early life adversity (ELA)-which often limits energetic capital-could shape investment in growth and reproduction, as well as trade-offs between them, ultimately contributing to variation in evolutionary fitness. Using long-term demographic, behavioral, and physiological data for 2,100 females from a non-human primate population, we tested whether naturally-occurring ELA influences investment in the competing physiological demands of growth and reproduction. By analyzing ELA, growth, and reproduction in the same individuals, we also assessed whether adversity intensifies trade-offs between life history domains. We found that ELA influenced life history patterns, and was associated with modified growth, delayed reproductive maturity, and small adult body size. Different types of ELA sometimes had distinct reproductive outcomes-e.g., large group size was linked to faster reproductive rates, while low maternal rank predicted slower ones. Adversity also amplified trade-offs between growth and reproduction: small body size was a stronger predictor of delayed and reduced reproductive output in females exposed to ELA, compared to those not exposed. Finally, we examined how traits modified by ELA related to lifetime reproductive success. Across the population, starting reproduction earlier and maintaining a moderate reproductive rate conferred the greatest number of offspring surviving to reproductive maturity. These findings suggest that ELA impacts key life history traits as well as relationships between them, and can constrain individuals from adopting the most optimal reproductive strategy. Significance Statement: Early life adversity (ELA) can have lasting effects on evolutionary fitness (e.g., the number of surviving offspring an animal produces); however, the paths connecting ELA to fitness-for example by influencing growth, reproductive timing or rate, or trade-offs between these processes-remain unclear. Leveraging long-term behavioral, physiological, and demographic data from 2,100 female rhesus macaques, we found that ELA-exposed females exhibited growth and reproductive schedules associated with less-optimal lifetime fitness outcomes. Further, ELA intensified trade-offs between growth and reproduction, suggesting that affected individuals face steeper energetic constraints. Our findings highlight the long-lasting impacts of ELA on traits of evolutionary and biomedical importance in a non-human primate model with relevance to humans.
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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 | 0.000 | 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) | 0.001 | 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".