The evolution of parasite virulence in the presence of resistance-conferring defensive symbionts
Bibliographic record
Abstract
Defensive symbionts-organisms that confer protection to their hosts against natural enemies such as parasites, predators, or herbivores-are found throughout the natural world. Theoretical and empirical studies have shown that defensive symbionts can both interfere with ecological interactions between hosts and exploiters, as well as drive exploiter evolution. Defensive symbionts are also potential candidates for biocontrol agents to help manage infectious diseases or agricultural pests. The impact of defensive symbionts on parasite ecology and evolution has therefore recently received increased empirical and theoretical attention. In this theoretical study, we investigate the impact that a defensive symbiont which protects hosts from infection (conferred resistance) has on the evolution of parasite virulence. We also explore how the extent of protection conferred by the defensive symbiont coevolves with parasite virulence, and how symbiont and parasite evolution affect the ecology of the host population in both the short- and long-term. We show that, while costly resistance-conferring defensive symbionts always select for increased parasite virulence, the overall long-term ecological effect on the host population may still be positive due to reductions in disease prevalence. This contrasts with tolerance-conferring symbionts (which protect against virulence), where the long-term ecological effects on the host population are always negative. We also show when the defensive symbiont can successfully eliminate the parasite. Resistance-conferring defensive symbionts therefore offer more promise as evolutionarily robust biocontrols than those that only confer tolerance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".