Masting by beech trees predicts the risk of Lyme disease
Bibliographic record
Abstract
BACKGROUND: The incidence of Lyme borreliosis and other tick-borne diseases is increasing in Europe and North America. There is currently much interest in identifying the ecological factors that determine the density of infected ticks as this variable determines the risk of Lyme borreliosis to vertebrate hosts, including humans. Lyme borreliosis is caused by the bacterium Borrelia burgdorferi sensu lato (s.l.) and in western Europe, the hard tick Ixodes ricinus is the most important vector. METHODS: Over a 15-year period (2004-2018), we monitored the monthly abundance of I. ricinus ticks (nymphs and adults) and their B. burgdorferi s.l. infection status at four different elevations on a mountain in western Switzerland. We collected climate variables in the field and from nearby weather stations. We obtained data on beech tree seed production (masting) from the literature, as the abundance of Ixodes nymphs can increase dramatically 2 years after a masting event. We used generalized linear mixed effects models and AIC-based model selection to identify the ecological factors that influence inter-annual variation in the nymphal infection prevalence (NIP) and the density of infected nymphs (DIN). RESULTS: We found that the NIP decreased by 78% over the study period. Inter-annual variation in the NIP was explained by the mean precipitation in the present year, and the duration that the DNA extraction was stored in the freezer prior to pathogen detection. The DIN decreased over the study period at all four elevation sites, and the decrease was significant at the top elevation. Inter-annual variation in the DIN was best explained by elevation site, year, beech tree masting index 2 years prior and the mean relative humidity in the present year. This is the first study in Europe to demonstrate that seed production by deciduous trees influences the density of nymphs infected with B. burgdorferi s.l. and hence the risk of Lyme borreliosis. CONCLUSIONS: Public health officials in Europe should be aware that masting by deciduous trees is an important predictor of the risk of Lyme borreliosis.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".