Multi-trophic interactions and migration behaviour determine the ecology and evolution of parasite infection in monarch butterflies
Bibliographic record
Abstract
Monarch caterpillars are specialist feeders on milkweeds, from which they sequester toxic cardenolides, protecting them against predators. Their bright colours advertise toxicity. North American monarchs make an annual migration; millions of them travel from the USA and Canada to overwinter in central Mexico. They are an ideal system to study the effects of multitrophic interactions and migration behaviour on the ecology and evolution of infectious disease. Monarchs are commonly infected with a protozoan parasite. Our studies have shown that milkweed chemicals reduce parasite growth, transmission, and virulence and are used by monarchs to reduce infection in their offspring, although this may also select for more virulent parasites. Studies have also shown that seasonal migration is an important determinant of parasite prevalence through migratory culling, when the most heavily infected individuals are weeded out during the autumn migration, and migratory escape, when they escape contaminated environments, reducing infection probability. Conservation efforts have increased the planting of non-native medicinal milkweeds in North America, and monarchs have increasingly formed sedentary populations, reducing migration rates. This has increased parasite prevalence in non-migratory populations. Integrating studies on multitrophic interactions and migration behaviour are necessary to determine their long-term effects on parasite dynamics and host and parasite evolution in monarchs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".