Maps of ticks (Acari: Argasidae, Ixodidae) for Austria and South Tyrol, Italy.

A first compilation of georeferenced tick locations in Austria and South Tyrol, Italy, is presented here. This allows the tick fauna to be examined in the various climatic regions of the European Alps. The dataset comprises 424 tick locations of Austria and 48 tick locations of South Tyrol, which were digitized from literature and visualized in the form of geographical maps. The tick fauna of Austria includes two species of Argasidae in the genera Argas and Carios and 15 species of Ixodidae in the genera Dermacentor, Haemaphysalis, and Ixodes, altogether 17 tick species. In addition, two species of Ixodidae in the genera Hyalomma (each spring imported by migratory birds) and Rhipicephalus (occasionally imported by dogs returning from abroad with their owners) are included in the tick atlas. Of these, the georeferenced locations of 18 tick species are depicted in maps. The occurrence of the one remaining tick species, Ixodes inopinatus, is given at the level of the federal states. The first Austrian distribution map of the long-legged bat tick Ixodes vespertilionis, which was reported from 21 caves, deserves special mention. The most common and widespread tick species is Ixodes ricinus, with records in all nine federal states of Austria, followed by Ixodes canisuga, Ixodes hexagonus, and I. vespertilionis in six federal states each. Haemaphysalis concinna and Dermacentor reticulatus are only endemic in the eastern plains, while Dermacentor marginatus only occurs in the west, in the Tyrolean Alpine valleys. Eight tick species were reported from South Tyrol, Italy. There, the most frequently flagged tick from the vegetation is also I. ricinus, while D. marginatus and Haemaphysalis punctata are often collected from sheep. The locations are shown together with those from North and East Tyrol on a separate Tyrol map. The tick atlas in Austria and South Tyrol as well as the underlying digital dataset in the supplement contribute to the closing of data gaps in global distribution maps of ticks and improve the data basis for new species distribution models.