Prey Behavior, Age‐Dependent Vulnerability, and Predation Rates
Bibliographic record
Abstract
Variation in the temporal pattern of vulnerability can provide important insights into predator-prey relationships and the evolution of antipredator behavior. We illustrate these points with a system that has coyotes (Canis latrans) as a predator and two species of congeneric deer (Odocoileus spp.) as prey. The deer employ different antipredator tactics (aggressive defense vs. flight) that result in contrasting patterns of age-dependent vulnerability in their probability of being captured when encountered by coyotes. We use long-term survival data and a simple mathematical model to show that (1) species differences in age-dependent vulnerability are reflected in seasonal predation rates and (2) seasonal variation in prey vulnerability and predator hunt activity, which can be associated with the availability of alternative prey, interact to shape seasonal and annual predation rates for each prey species. Shifting hunt activity from summer to winter, or vice versa, alleviated annual mortality on one species and focused it on the other. Our results indicate that seasonal variation in prey vulnerability and hunt activity interact to influence the impact that a predator has on any particular type of prey. Furthermore, these results indicate that seasonal variation in predation pressure is an important selection pressure shaping prey defenses.
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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 | 0.001 |
| 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".