Heterogeneity in male horn growth and longevity in a highly sexually dimorphic ungulate
Bibliographic record
Abstract
In sexually dimorphic ungulates, sexual selection favoring rapid horn growth in males may be counterbalanced by a decrease in longevity if horns are costly to produce and maintain. Alternatively, if early horn growth varied with individual quality, it may be positively correlated with longevity. We studied Alpine ibex Capra ibex in the Gran Paradiso National Park, Italy, to test these alternatives by comparing early horn growth and longevity of 383 males that died from natural causes. After accounting for age at death, total horn length after age 5 was positively correlated with horn growth from two to four years. Individuals with the fastest horn growth as young adults also had the longest horns later in life. Annual horn growth increments between two and six years of age were independent of longevity for ibex whose age at death ranged from 8 to 16 years. Our results suggest that growing long horns does not constrain longevity. Of the variability in horn length, 22% could be explained by individual heterogeneity, suggesting persistent differences in phenotypic quality among males. Research on unhunted populations of sexually dimorphic ungulates documents how natural mortality varies according to horn or antler size, and can help reduce the impact of sport hunting on natural processes.
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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".