Does high biodiversity reduce the risk of Lyme disease invasion?
Bibliographic record
Abstract
BACKGROUND: It has been suggested that increasing biodiversity, specifically host diversity, reduces pathogen and parasite transmission amongst wildlife (causing a "dilution effect"), whereby transmission amongst efficient reservoir hosts, (e.g. Peromyscus spp. mice for the agent of Lyme disease Borrelia burgdorferi) is reduced by the presence of other less efficient host species. If so, then increasing biodiversity should inhibit pathogen and parasite invasion. METHODS: We investigated this hypothesis by studying invasion of B. burgdorferi and its tick vector Ixodes scapularis in 71 field sites in southeastern Canada. Indices of trapped rodent host diversity, and of biodiversity of the wider community, were investigated as variables explaining the numbers of I. scapularis collected and B. burgdorferi infection in these ticks. A wide range of alternative environmental explanatory variables were also considered. RESULTS: The observation of low I. scapularis abundance and low B. burgdorferi infection prevalence in sites where I. scapularis were detected was consistent with early-stage invasion of the vector. There were significant associations between the abundance of ticks and season, year of study and ambient temperature. Abundance of host-seeking larvae was significantly associated with deer density, and abundance of host-seeking larvae and nymphs were positively associated with litter layer depth. Larval host infestations were lower where the relative proportion of non-Peromyscus spp. was high. Infestations of hosts with nymphs were lower when host species richness was higher, but overall nymphal abundance increased with species richness because Peromyscus spp. mouse abundance and host species richness were positively correlated. Nymphal infestations of hosts were lower where tree species richness was higher. B. burgdorferi infection prevalence in ticks varied significantly with an index of rates of migratory bird-borne vector and pathogen invasion. CONCLUSIONS: I. scapularis abundance and B. burgdorferi prevalence varied with explanatory variables in patterns consistent with the known biology of these species in general, and in the study region in particular. The evidence for a negative effect of host biodiversity on I. scapularis invasion was mixed. However, some evidence suggests that community biodiversity beyond just host diversity may have direct or indirect inhibitory effects on parasite invasion that warrant further study.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".