Infection outcomes under genetic and environmental variation in a host-parasite system: Implications for maintenance of polymorphism and the evolution of virulence
Bibliographic record
Abstract
Virulence (the harm to the host during infection) is the outcome of continuous coevolution between hosts and parasites. This thesis adds to a growing body of work on host-parasite interactions, and describes experiments that study the effects of variation in the genetic and the environmental contexts of infection. All of them focus on interaction between the planktonic freshwater crustacean Daphnia magna and a naturally occurring parasite, the spore-forming bacterium Pasteuria ramosa. I show that elevated minimum temperatures that facilitate parasite growth drive natural epidemics of this parasite. I also demonstrate that the expression of infection traits in P. ramosa is temperature-dependent in a genotype-specific manner [genotype-by-environment (GxE) interactions]. These GxE interactions could maintain polymorphism through environment-dependent selection. Next, I test if GxG interactions for infectivity can be altered by environmental variation (GxGxE interactions), and find that this trait is quite robust to thermal variation. Infectivity is also more important in determining parasite fitness relative to the production of transmission stages, highlighting the importance of considering natural infection routes, an aspect sometimes overlooked in studies of host-parasite systems. Another experiment under different food and temperature regimes showed evidence for environment-dependent virulence-transmission relationships, a fundamental component of virulence evolution models. Lastly, I show that variation in temperature does not increase the cost to the host of resisting infection.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".