Sexual segregation in ungulates: a comparative test of three hypotheses
Bibliographic record
Abstract
In most social ungulate species, males are larger than females and the sexes live in separate groups outside the breeding season. It is important for our understanding of the evolution of sociality to find out why sexual segregation is so widespread not only in ungulates but also in other mammals. Sexual body size dimorphism was proposed as a central factor in the evolution of sexual segregation in ungulates. We tested three hypotheses put forward to explain sexual segregation: the predation-risk, the forage-selection, and the activity budget hypothesis. We included in our analyses ungulate species ranging from non-dimorphic to extremely dimorphic in body size. We observed oryx, zebra, bighorn sheep and ibex in the field and relied on literature data for 31 additional species. The predation-risk hypothesis predicts that females will use relatively predator-safe habitats, while males are predicted to use habitats with higher predation risk but better food quality. Out of 24 studies on different species of ungulates, females and their offspring chose poorer quality but safer habitat in only eight cases. The forage-selection hypothesis predicts that females would select habitat based on food quality, while males should prefer high forage biomass. In fact, females selected higher quality food in only six out of 18 studies where males and females segregated, in eight studies there was no difference in forage quality and in four studies males were in better quality habitat. The activity budget hypothesis predicts that with increasing dimorphism in body size males and females will increasingly differ in the time spent in different activities. Differences in activity budgets would make it difficult for males and females to stay in mixed-sex groups due to increased costs of synchrony to maintain group cohesion. The predictions of the activity budget hypothesis were confirmed in most cases (22 out of 23 studies). The heavier males were compared to females, the more time females spent foraging compared to males. The bigger the dimorphism in body mass, the more males spent time walking compared to females. Lactating females spent more time foraging than did non-lactating females or males. Whether species were mainly bulk or intermediate feeders did not affect sexual differences in time spent foraging. We conclude that sexual differences in activity budgets are most likely driving sexual segregation and that sexual differences in predation risk or forage selection are additive factors.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".