Meteorological, climatic variables, and habitat heterogeneity predict the Ixodes ricinus nymph activity in France
Résumé
Context: Ixodes ricinus ticks (Acari: Ixodidae) are the most important vector for Lyme borreliosis in Europe, including France. The life cycles and key ecological processes of I. ricinus, suchas mortality, development rate, and questing behavior, are sensitive to weather and environmental conditions. Therefore, variations in these conditions contribute to the regulation of the dynamics of tick abundance, phenology of questing activity, and eventually, human-tick exposure risks throughout the year.
Objective: This study aimed to determine the effects of environmental factors on questing activity of I. ricinus nymphs across diverse climatic types in France over a long-term period.
Methods: Questing nymph activity was observed using a repeated removal sampling design with a cloth-dragging technique in 11 sampling sites from 7 tick observatories from 2014 to 2021 at approximately 1-month intervals. The environment of each sampling site were described by meteorological (temperature, relative humidity, daytime duration), bioclimatic (annual temperature, precipitation), topography (elevation), and habitat characteristics (forest fragmentation, soil pH, land cover types). Highly correlated variables were summarized using a Principal Component Analysis (PCA). Subsequently, a multivariate mixed-effects
negative binomial regression model was used to assess the effect of environmental factors on the nymph activities.
Results: A total of 631 sampling campaigns were involved in this study. Three phenological patterns were observed, potentially following a climatic gradient. The first 2 dimensions of the PCA described the land cover (Dimension 1) and the topographical/bioclimatic (Dimension 2), respectively. The mixed-effects negative binomial regression revealed that observed nymph counts were driven by different interval-average meteorological variables, including one-month average temperature, previous-season average temperature, and half-year average minimum relative humidity. The interaction effects indicated that the phenology in
colder climates peaked differently from that of warmer climates. Also, the land cover characteristics that support the highest baseline abundance were moderate forest fragmentation with transition borders with agricultural areas.
Conclusion: Finally, our model could potentially be used to predict seasonal human-tick exposure risks in France that could contribute to mitigating Lyme borreliosis risks.
