Predation risks suppress lifetime fitness in a wild mammal
Bibliographic record
Abstract
Prey often reduce predation risk at the cost of lower resource intake. The cumulative effects of such tradeoffs can alter resource allocation, demography and evolutionary processes. We show how the accumulation of risk effects reduces the growth rate of wild North American porcupines Erethizon dorsatum , and simulate three evolutionary responses related to lifetime reproductive success. Individual porcupines experiencing predation risk from fishers Pekania pennanti grew slower and gave birth to fewer offspring. Simulations show that predation risk alone can lead to population declines, and that a female can replace herself by investing more energy into reproduction or adult survival; females that only invest energy in juvenile survival cannot. We show that the accumulation of predation risk can reduce lifetime reproductive success in natural ecosystems. Estimating the contribution of predation risk, and how evolutionary responses can mediate consequences associated with predation risk, is necessary to understand the evolution of predator–prey systems.
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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) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".