Host mortality, predation and the evolution of parasite virulence
Bibliographic record
Abstract
Abstract One of the most accepted views in the theoretical literature on virulence evolution is that a parasite's virulence will evolve to higher levels when its host's background mortality rate increases. Surprisingly, however, although many sources of background mortality involve predation, there has not yet been any theoretical research that explicitly considers how the dynamics of this important ecological interaction affects virulence evolution. Here, we consider how predation affects virulence evolution by explicitly introducing a predator into a classical susceptible–infected–susceptible epidemiological model. We find that, contrary to previous predictions, different sources of host mortality affect virulence evolution in different ways. Moreover, the way in which virulence evolution is affected depends on how tightly coupled the predator's dynamics are to the host population, and this can result in somewhat counterintuitive results. For example, indirect ecological effects can cause elevated host mortality to result in the evolution of lower parasite virulence, even if this elevated mortality arises from factors unrelated to predation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".