Mismatch between IUCN range maps and species interactions data illustrated using the Serengeti food web

A new R package to parse plant species occurrence records into unique collection events efficiently reduces data redundancy

Biodiversity data aggregators, such as Global Biodiversity Information Facility (GBIF) suffer from inflation of the number of occurrence records when data from different databases are merged but not fully reconciled. The ParseGBIF workflow is designed to parse duplicate GBIF species occurrence records into unique collection events (gatherings) and to optimise the quality of the spatial data associated with them. ParseGBIF provides tools to verify and standardize species scientific names according to the World Checklist of Vascular Plants taxonomic backbone, and to parse duplicate records into unique 'collection events', in the process compiling the most informative spatial data, where more than one duplicate is available, and providing crude estimates of taxonomic and spatial data quality. When GBIF occurrence records for a medium-sized vascular plant family, the Myrtaceae, were processed by ParseGBIF, the average number of records useful for spatial analysis increased by 180%. ParseGBIF could therefore be valuable in the evaluation of species' occurrences at the national scale in support for national biodiversity plans, identification of plant areas important for biodiversity, sample bias estimation to inform future sampling efforts, and to forecast species range shifts in response to global climate change.