Your infections are what you eat: How host ecology shapes the helminth parasite communities of lizards
Bibliographic record
Abstract
Understanding how parasite communities are assembled, and the factors that influence their richness, can improve our knowledge of parasite-host interactions and help to predict the spread of infectious diseases. Previous comparative analyses have found significant influences of host ecology and life history, but focused on a few select host taxa. Host diet and habitat use play key roles in the acquisition of parasitic helminths as many are trophically transmitted, making these attributes potentially key indicators of infection risk. Given the paucity of comparative studies with non-piscine, non-avian or non-mammalian hosts, it is critical to examine the degree to which host ecology influences parasite communities in other host taxa in order to identify common drivers. We examined helminth diversity in over 350 species of lizards in relation to their body mass, ecology (diet and habitat use) and life history (clutch size, and ovo- or viviparity) using previously published data. Overall, lizard species with herbivorous diets harboured fewer types of helminths (especially larval stages), with similar results for traits that were ultimately strongly associated with diet (host mass and habitat use). Large hosts tended to be herbivores with few helminth types, whereas species utilizing arboreal habitats typically consumed some animal matter and hosted more helminths. Understanding how host ecology and life history are related to their parasite assemblages has significant implications for the risk of acquiring novel parasites. Our results indicate an overwhelming influence of host diet such that many helminths may be relatively easily acquired by hosts in new ranges, or through dietary shifts.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".