Ecological and evolutionary effects of selective harvest of non‐lactating female ungulates
Bibliographic record
Abstract
Summary Female ungulates are often selectively harvested according to their reproductive status. Because ungulate population growth depends heavily on adult female survival, it is crucial to understand the effects of this selective harvest. Recent studies revealed persistent individual differences in female reproductive potential, with a positive correlation of reproductive success over consecutive years. If current reproduction is correlated with lifetime reproductive success, then selective harvest of non‐lactating females should remove individuals of low reproductive potential, with lower impact on population growth than random harvest. If lifetime reproductive success has a genetic basis, selective harvest may also increase the proportion of successful females. We used an individual‐based model to understand the short‐term effects of harvest intensity and hunter selectivity on population dynamics, accounting for both heterogeneity in reproductive potential and orphan survival. We also explored the long‐term effect of harvest as a selective pressure on female heterogeneity. Selective harvest of non‐lactating females reduced survival to primiparity compared to random harvest, because of high harvest rates of pre‐reproductive females. After primiparity, however, females of higher reproductive potential had higher survival under selective than random harvest. Therefore, the overall effect on population dynamics depends on a trade‐off between a high harvest of pre‐reproductive females and a reduced harvest of reproductive females with high reproductive potential. Female heterogeneity and the length of the pre‐reproductive period affected this trade‐off. Over the short term, high heterogeneity in reproductive potential of pre‐reproductive females made selective harvest the most effective strategy to maintain a high population growth rate. With low heterogeneity and little effects of orphaning on juvenile mortality, however, random harvest had a lower impact on population growth than selective harvest. Over the long term, selective female harvest may increase the proportion of successful reproducers in the population. Synthesis and applications . Selective harvests of non‐lactating females appear justified only if female heterogeneity in reproductive potential and/or orphan mortality are very high. Because pre‐reproductive females will be subject to intense harvest, selective harvest may reduce population growth rate compared to random harvest in species with late primiparity, especially if most pre‐reproductive female normally survive to primiparity. When heterogeneity in reproductive potential and orphan mortality are low, random female harvest appears preferable to selective harvest.
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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".