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There is a big volume of occurrence records available in biodiversity databases, but researchers should guarantee its quality before use it in scientific studies. A problem that might compromise the quality of occurrence data is species misidentification. We address this issue by presenting naturaList, a R package designed to classify species occurrence data according to identification reliability.

naturaList allows to classify species occurrences up to six levels of confidence in species identification, and to filter occurrence data accordingly. The highest level of confidence is assigned to records identified by a specialist, whose name must be provided by the user. The other five levels of confidence are derived from the occurrence data. We demonstrate naturaList functions using occurrences of Alsophila setosa, a tree fern species from Atlantic Forest, as example. We classified and filtered data in grid cells in order to maintain only the highest-level records in each cell. Then we selected only those records classified in the two highest levels of confidence.

From 323 occurrences of Alsophila setosa displaying geographic coordinates, 69 (21%) were identified by a specialist. After filtering the highest-level records inside grid cells, 102 records remained. From these grid cell filtered data, 38 occurrences (37%) were classified into the highest confidence level. Three records were removed using an interactive map module, due to falling in sea sites or outside the native range size of the species. Since we selected only records classified in the two highest levels of confidence, the final dataset contained 94 occurrence records.

naturaList guarantees the …