The importance of parasite geography and spillover effects for global patterns of host–parasite associations in two invasive species
Bibliographic record
Abstract
Abstract Aim Geographic spread and range expansion of species into novel environments may merge originally separated species assemblages, yet the possible drivers of geographic heterogeneity in host–parasite associations remain poorly understood. Here, we examine global patterns in the parasite assemblages of two rat species and explore the role of parasite acquisition from local pools of host species. Location Global. Methods We compiled a global data set of helminth parasites (n = 241 species) from two rat species (Rattus rattus species complex, R. norvegicus) and, concomitantly, from all other mammal species known to be infected by the same parasites. We used an inverse Bayesian modelling approach to explicitly link species‐level to community‐level infestation probabilities at different geographic scales and alleviate the shortcoming of sampling bias. Results Patterns of species richness and turnover of parasites in the two focal rat species revealed clear biogeographic structure with lowest species richness and most distinct assemblages in Madagascar and highest species richness and least distinct assemblages in the Palaearctic region. Parasite species richness and turnover across regions were correlated for the two focal hosts, although they were associated with distinct assemblages within regions. Infection probability of a focal host with any given parasite was clearly related to infection probability of the local species pool of wildlife hosts with that same parasite. Infection probability of other mammal species infected with these parasite species, in turn, decreased with their taxonomic distance to the genus Rattus. Main conclusions Our study demonstrates the importance of spillover of parasites from local wildlife hosts to invasive rats on global patterns of host–parasite associations. Considering both changes in local pools of host species and the global distributions of parasite and pathogen diversity in consistent model frameworks may therefore advance the forecasting of species‐level infestation patterns and the possible risk of disease emergence from local to global scale.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".