Northward expansion of the thermal limit for the tick Ixodes ricinus over the past 40 years

Background The sheep tick Ixodes ricinus is the vector associated with the highest incidence of vector-borne disease in humans in Europe. Several studies have been published about the effect of future climate change on the potential distribution of I. ricinus, despite a limited understanding of how climate change has resulted in distribution changes to date. The objective of the present study was to assess whether temperature changes have already influenced the northern distribution limit of I. ricinus in Europe. To this end, we estimated a thermal threshold for the presence of the species and then used this estimated threshold to hindcast the geographical location of the thermal limit over the past 40 years. Methods We used a public dataset of I. ricinus abundance at the northern edge of its European distribution for 2016–2017 and temperature data obtained from the ERA5Land dataset to identify a thermal threshold for I. ricinus distribution. We first modelled nymphal tick abundance as a function of cumulative annual degree days (ADD) > 0 °C stratified by biogeographical regions using observations for 2016–2017. We then identified the thermal limit for each biogeographical region as the minimum DD > 0 °C value where the predicted nymph abundance is greater than zero and projected it onto ERA5Land temperature data for the period 1979–2020. Results Hindcasting the identified thermal limit suggested that I. ricinus has expanded its range by approximately 400 km in the Boreal biogeographical region between 1979 and 2020. This finding helps explain numerous observations of I. ricinus in areas presumed to be newly colonised. Conclusions Our findings suggest a substantial northward expansion of I. ricinus over the past four decades. Our approach appears promising for understanding species distribution changes driven by recent climate change, acknowledging that multiple other factors affect tick distribution and abundance at the local scale, such as host distribution and microhabitat. Our results underline the relevance of long-term time series data and the risk associated with short time series for observing changes in distribution