Predators reduce <i><scp>B</scp>atrachochytrium dendrobatidis</i> infection loads in their prey
Bibliographic record
Abstract
Summary Disease ecologists and wildlife managers are increasingly interested in understanding how predators regulate infection in prey populations. The healthy herds hypothesis suggests that predators may decrease infection prevalence by decreasing overall population size, reducing density‐dependent transmission and culling infected individuals from a population. While this model incorporates density‐mediated indirect interactions ( DMII s), it does not incorporate the potential role of trait‐mediated indirect interactions ( TMII s). Using wood frog tadpoles ( L ithobates sylvatica ), we examined whether predator cues could alter the prevalence and intensity of infection by the fungal pathogen Batrachochytrium dendrobatidis [Bd] and whether both stressors could alter the host's life history traits. Exposure to predator cues caused tadpoles to have reduced Bd infection loads, potentially as a result of stress‐induced immunoenhancement. Tadpoles exposed to Bd had faster development than tadpoles not exposed to Bd, but they did not differ in survival or growth. This suggests that, in this life stage of this species, Bd infection does not have fitness costs. These data suggest that the trait‐mediated effects of predators on infection may alter epidemiological outcomes of Bd exposure.
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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 | 0.001 |
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".