Ability to demonstrate statistical patterns of distribution by threatened species and by their potential competitors will determine success in forecasting locations at greatest risk, and ability to target management efforts. A self-organizing map algorithm (SOM) was used to derive probabilities of presence of native (Austropotamobius pallipes) and exotic (Orconectes limosus, Pacifastacus leniusculus and Procambarus clarkii) crayfish species with respect to physical and land-cover variables in a large stream system, using a simple presence-absence dataset of species. Crayfish were sampled at 128 sites representing 86 rivers. The probability of occurrence of the native species increased at higher elevations above sea level and lower temperatures; populations appeared to be mostly confined to headwater streams where exotic competitors were unable to withstand the colder conditions. The distribution of exotic species was correlated with anthropogenic factors, such as the degree of urbanization and agricultural land area. Complementary modelling tools, such as GIS and SOMs, can help to maximize the information extracted from available data in the context of biological conservation.