From valleys to peaks: how climate and environment drive Alpine populations of Ixodes ricinus.
4 affiliations
- 1Department of Veterinary Sciences, University of Turin, Grugliasco, Italy. [email protected].
- 2Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d'Aosta, Turin, Italy.
- 3Department of Veterinary Sciences, University of Turin, Grugliasco, Italy.
- 4Biostatistics, Epidemiology, and Public Health Unit (UBEP), University of Padua, Padua, Italy.
Abstract
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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BibTeX
@article{bellato2026from,
title = {{From valleys to peaks: how climate and environment drive Alpine populations of Ixodes ricinus.}},
author = {Alessandro Bellato and Aitor Garcia-Vozmediano and Laura Tomassone and Annibale Biggeri and Dolores Catelan},
journal = {Parasites \& vectors},
year = {2026},
month = aug,
doi = {10.1186/s13071-026-07590-z},
url = {https://europepmc.org/article/MED/42968154},
note = {CC BY},
}
RIS
TY - JOUR
TI - From valleys to peaks: how climate and environment drive Alpine populations of Ixodes ricinus.
AU - Alessandro Bellato
AU - Aitor Garcia-Vozmediano
AU - Laura Tomassone
AU - Annibale Biggeri
AU - Dolores Catelan
PY - 2026
DA - 2026/08/04
JO - Parasites & vectors
DO - 10.1186/s13071-026-07590-z
UR - https://europepmc.org/article/MED/42968154
AB - 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.
SN - 1756-3305
ER -