Complementarity analysis based on overlaying large numbers of species distribution maps is increasingly being employed by conservationists to determine conservation priorities. This method is used because of its efficiency in representing selected species in a minimal number of areas, thus maximizing the number of conserved species in relation to area. As such analyses are mostly based on coarse spatial scales, it is essential to test the efficiency and accuracy of these methods, and to develop supplementary analyses that allow us to translate the result into identification of conservation sites of a manageable size. Here we test the effectiveness of a coarse-scale (continent-wide) analysis using a more detailed (nation-wide) logical inductive model based on point records. We find that, although there are differences in the effectiveness at these scales, most of the areas identified by the fine-scale data are nested within those identified by the coarse approach. We also find that areas identified as important for birds fit well within the current national focal areas for conservation in Uganda.