From valleys to peaks: how climate and environment drive Alpine populations of Ixodes ricinus
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Updated: Nov 3, 2026

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
Published on: August 25, 2018
Alessandro Bellato1, Aitor Garcia-Vozmediano2, Laura Tomassone3
1Department of Veterinary Sciences, University of Turin, Grugliasco, Italy. alessandro.bellato@unito.it.
Background:
Ixodes ricinus is the most widespread tick in Europe and an important vector of pathogens affecting humans and animals. Human cases of tick-borne diseases are rising, reflecting the expansion of I. ricinus to higher latitudes and altitudes and the increasing recreational use of Alpine environments. Land-use change, growing wildlife populations, and farmland abandonment are creating new suitable habitats, while climate warming is reducing winter severity at elevation. In the northwestern Italian Alps, I. ricinus is now regularly detected above 1600 m. This study investigated environmental and climatic predictors of nymph presence and density in a recently colonized Alpine valley.
Methods:
From 2016 to 2019, nymph presence and density were measured six times per year across 44 sites covering an elevation gradient and diverse habitats. Habitat features, wildlife signs, remote-sensing indices, and meteorological variables were recorded or derived. Generalized linear mixed models were used to assess associations with nymph density. A machine-learning Bayesian algorithm was then applied to identify the most influential predictors, accounting for high-dimensionality and collinearity of the predictors set.
Results:
Altitude, habitat type, and wildlife presence were associated with nymph presence and density, but their predictive value disappeared in the Bayesian model once climatic and weather variables were included. Global solar irradiation, ground-level relative humidity, soil dryness, and lagged indicators of unfavourable conditions (windy and cold days) consistently predicted nymph density. Terrain descriptors and NDVI-based variables performed poorly, likely due to snow cover and the short warm season typical of Alpine systems.
Conclusions:
Short-term weather and fine-scale climatic variables explained variation in nymph density more effectively than broader environmental descriptors within the Bayesian framework, suggesting that colonisation in this Alpine area remains contingent on favourable environmental conditions rather than reflecting fully stable establishment.
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