Community disassembly and disease: realistic—but not randomized—biodiversity losses enhance parasite transmission
Bibliographic record
Abstract
Debates over the relationship between biodiversity and disease dynamics underscore the need for a more mechanistic understanding of how changes in host community composition influence parasite transmission. Focusing on interactions between larval amphibians and trematode parasites, we experimentally contrasted the effects of host richness and species composition to identify the individual and joint contributions of both parameters on the infection levels of three trematode species. By combining experimental approaches with field surveys from 147 ponds, we further evaluated how richness effects differed between randomized and realistic patterns of species loss (i.e. community disassembly). Our results indicated that community-level changes in infection levels were owing to host species composition, rather than richness. However, when composition patterns mirrored empirical observations along a natural assembly gradient, each added host species reduced infection success by 12-55%. No such effects occurred when assemblages were randomized. Mechanistically, these patterns were due to non-random host species assembly/disassembly: while highly competent species predominated in low diversity systems, less susceptible hosts became progressively more common as richness increased. These findings highlight the potential for combining information on host traits and assembly patterns to forecast diversity-mediated changes in multi-host disease systems.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".