Taxonomy in the electronic age and an e-monograph of the papaya family (Caricaceae) as an example.

The need for taxonomists to take full advantage of biodiversity informatics has been clear for at least 10 years. Significant progress has been made in providing access to taxonomic resources online, including images of specimens (especially types), original species descriptions, and georeferenced collection data. However, in spite of persuasive calls for e-monography, there are few, if any, completed project, even though monographic research is the only mechanism for reducing synonymous names, which are estimated to comprise 50% of all published names. Caricaceae is an economically important family of flowering plants from Africa and the Neotropics, best known for the fruit crop papaya. There is a large amount of information on the family, especially on chemistry, crop improvement, genomics, and the sex chromosomes of papaya, but up-to-date information on the 230 names and which species they might belong to was not available. A dynamically updated e-monograph of the Caricaceae now brings together all information on this family, including keys, species descriptions, and specimen data relating the 230 names to 34 species and one hybrid. This may be the first taxonomic monograph of a plant family completely published online. The curated information will be continuously updated to improve the monograph's comprehensiveness and utility.

No one-size-fits-all solution to clean GBIF.

Species occurrence records provide the basis for many biodiversity studies. They derive from georeferenced specimens deposited in natural history collections and visual observations, such as those obtained through various mobile applications. Given the rapid increase in availability of such data, the control of quality and accuracy constitutes a particular concern. Automatic filtering is a scalable and reproducible means to identify potentially problematic records and tailor datasets from public databases such as the Global Biodiversity Information Facility (GBIF; http://www.gbif.org), for biodiversity analyses. However, it is unclear how much data may be lost by filtering, whether the same filters should be applied across all taxonomic groups, and what the effect of filtering is on common downstream analyses. Here, we evaluate the effect of 13 recently proposed filters on the inference of species richness patterns and automated conservation assessments for 18 Neotropical taxa, including terrestrial and marine animals, fungi, and plants downloaded from GBIF. We find that a total of 44.3% of the records are potentially problematic, with large variation across taxonomic groups (25-90%). A small fraction of records was identified as erroneous in the strict sense (4.2%), and a much larger proportion as unfit for most downstream analyses (41.7%). Filters of duplicated information, collection year, and basis of record, as well as coordinates in urban areas, or for terrestrial taxa in the sea or marine taxa on land, have the greatest effect. Automated filtering can help in identifying problematic records, but requires customization of which tests and thresholds should be applied to the taxonomic group and geographic area under focus. Our results stress the importance of thorough recording and exploration of the meta-data associated with species records for biodiversity research.