Seasonality of host-seekingIxodes ricinusnymph abundance in relation to climate

There is growing concern about climate change and its impact on human health. Specifically, global warming could increase the probability of emerging infectious diseases, notably because of changes in the geographical and seasonal distributions of disease vectors such as mosquitoes and ticks. For example, the range ofIxodes ricinus, the most common and widespread tick species in Europe, is currently expanding northward and at higher altitudes. However, little is known about the seasonal variation in tick abundance in different climates. Seasonality ofI. ricinusis often based on expert opinions while field surveys are usually limited in time. Our objective was to describe seasonal variations inI. ricinusabundance under different climates. To this end, a seven-year longitudinal study, with monthly collections ofI. ricinushost-seeking nymphs, was carried out in France, in six locations corresponding to different climates. Tick data were log-transformed and grouped between years so as to obtain seasonal variations for a typical year. Daily average temperature was measured during the study period. Seasonal patterns of nymph abundance were established for the six different locations using linear harmonic regression. Model parameters were estimated separately for each location. Seasonal patterns appeared different depending on the climate considered. Western temperate sites showed an early spring peak, a summer minimum and a moderate autumn and winter abundance. More continental sites showed a later peak in spring, and a minimum in winter. The peak occurred in summer for the mountainous site, with an absence of ticks in winter. In all cases except the mountainous site, the timing of the spring peak could be related to the sum of degree days since the beginning of the year. Winter abundance was positively correlated to the corresponding temperature. Our results highlight clear patterns in the different sites corresponding to different climates, which allow further forecast of tick seasonality under changing climate conditions.