Abstract The state of Maranhão, located in northeastern Brazil, comprises three biomes: Amazonian, Caatinga, and the Cerrado. To date, 99 ant species have been recorded in the literature from the state. In the present work, we provide for the first time a profile of the ant fauna in the state based on data from the historical literature and Brazilian institutional collections. The updated records on ant diversity for the state of Maranhão revealed a total of 279 species, belonging to 71 genera and 10 subfamilies. In total, 180 species are recorded for the first time in the state, of which four species recorded for the first time in Brazil. In summary, apart from documenting the ant fauna of the region, these results provide a basis for further studies and may contribute to future conservation efforts for the biomes present in this complex landscape.
Abstract Taxonomists' efforts throughout history provide significant amount of data that give support for establishing the specific identity of several groups of biological systems. In addition to identifying species, taxonomic research offers a wide range of biological information that can be used in other disciplines, e.g. evolution, ecology, integrated pest management. However, most of this information remains unappreciated due to certain aspects: (1) the advent of analytical tools have led to a shift in interest and investment in researches, focusing mainly in molecular studies; (2) the erroneous concept that the extensive data offered by taxonomic studies can be replaced by other datasets, separating it from its hypothesis-driven and investigative nature; (3) the final products found in taxonomic works are commonly restricted to a small group of researchers, due to its low accessibility and specific language. Considering this last aspect, web-based tools can be valuable to simplify the dissemination of the taxonomic product. Semantic annotation provide a condition in which species descriptions can be readily available and be far more extensive, enabling rapid exchange of countless data related to biological systems.