Influences of habitat and arthropod density on parasitism in two co-occurring host taxa
Bibliographic record
Abstract
Habitat attributes are known to influence infectious diseases such as those caused by parasites, but most studies have only considered single host and (or) parasite taxa, making it difficult to assess which features may be of general importance and to predict how alterations could affect disease dynamics. We examined infection with trematode (flatworm) parasites in two commonly co-occurring host taxa (larval amphibians and larval odonates (dragonflies and damselflies)) to investigate links with landscape-level features, including agricultural activity. We also assessed pond community composition with respect to the abundance and richness of aquatic arthropods known to prey upon tadpoles and (or) free-swimming trematode infectious stages. Larval amphibians from agricultural sites were most likely to be parasitized but had lower infection intensities, and infected hosts were positively associated with increasing distance to the nearest forest habitat, but negatively with road distance. The opposite was observed for larval odonate infection status; however, probability and intensity of parasitism in both host taxa was negatively associated with greater predatory arthropod abundance, consistent with the “dilution effect” of biodiversity on infectious diseases. Our approach demonstrates the importance of considering multiple host taxa when studying habitat links to diseases, and future studies incorporating even greater diversity will be needed.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".