The dispersion of insects and mites can be favored by many factors, including the increasing circulation of plant materials. Special attention is needed to the eriophyoid mites, which have a greater potential as introduced species, due to their physical and biological characteristics. Aculus schlechtendali (Nalepa) (Eriophyidae, Apple Rust Mite - ARM) is considered an important apple pest in several countries, being recently reported for the first time in Brazil. This study aimed to carry out a survey of the abundance and distribution of ARM in the Southern region of Brazil, in the cultivars Fuji, Gala and Eva, grown in the states of Rio Grande do Sul (RS), Santa Catarina (SC) and Paraná (PR). In addition, Moran's I autocorrelation was used as an analytical tool to assess the spatial dependence between the sample points. A total of 94 orchards were sampled in 19 municipalities, distributed in the three evaluated states. Regarding cultivars, there were 40 orchards of Fuji cultivar, 43 of Gala and 11 of Eva. At each one, 20 plants were selected, from which four leaves were collected, totaling 80 leaves/orchard. The screening and identification of the mites occurred at the Laboratório de Acarologia at the Universidade do Vale do Taquari – Univates, and the statistical analysis were made using generalized linear mixed models with subsequent paired analysis, using R-software. A total of 1,647 specimens of ARM were found in 66 orchards located in 17 municipalities, with an average number (mean ± standard deviation) of 24 ± 55 mites/orchard, 44 ± 83 in Fuji, 10 ± 19 in Gala and 17 ± 21 in Eva. The average number of mites differed between cultivars and states, with the lowest number in the cultivar Gala and in Rio Grande do Sul. No spatial autocorrelation was observed between the points, indicating that the dispersion of ARM in Southern Brazil has occurred at random, without a predefined pattern that would indicate a possible hotspot. The presence of this species serves as an alert for the apple production industry, regarding the distribution of a species previously not reported in the region. The recognition of the presence, abundance and distribution of this species will help in the monitoring and future management decisions, as well as the understanding of the distribution pattern.