KnowBR: mapping geographical variation of biodiversity survey effort

Paper presents new R package to automatically analyse raw species occurrence data to assess, map and identify survey efforts

Data resources used via GBIF : 137,809 species occurrences
Anthidium manicatum
European wool carder bee (Anthidium manicatum) by Kyle Bland. Photo via iNaturalist (CC BY-NC 4.0)

The apparent lack of occurrence of a given species does not necessarily reflect its actual absence, but could also be explained by insufficient survey effort. Such unknown bias can lead to unreliable results in downstream analyses, if unaddressed.

A paper by Spanish researchers in Ecological Indicators presents KnowBR—a novel software that assesses survey completeness across a territory of interest. Taking unfiltered georeferenced data from a source of primary biodiversity information, KnowBR calculates the completeness of a geographical unit–a cell or a polygon, as defined by the user–based on slopes of species accumulation curves. This curve describes the relationship between number of species and the total number of records (a surrogate survey effort).

To demonstrate the tool, the authors used a download of all bees (superfamily Apoidea) from GBIF.org to assess survey completeness at a one degree resolution. Their analysis revealed both general scarceness and bias of data, showing that only 18 per cent of terrestrial cells have georeferenced data for bees and that only nine per cent of species have more than 10 records. The accumulation curve slopes were below 0.01 (i.e. one species per 100 records) in less than one per cent of cells. The tool identified the highest number of well-surveyed cells in western North America, central and northern Europe, as well as Australia.

Link to original article

Lobo JM, Hortal J, Yela JL, Millán A, Sánchez-Fernández D, García-Roselló E, González-Dacosta J, Heine J, González-Vilas L and Guisande C (2018) KnowBR: An application to map the geographical variation of survey effort and identify well-surveyed areas from biodiversity databases. Ecological Indicators. Elsevier BV 91: 241–248. Available at: https://doi.org/10.1016/j.ecolind.2018.03.077.

  • {{'resourceSearch.filters.countriesOfResearcher' | translate}}:
  • Spain
  • {{'resourceSearch.filters.topics' | translate}}:
  • Data management
  • {{'resourceSearch.filters.audiences' | translate}}:
  • Data users
  • GBIF network
  • {{'resourceSearch.filters.purposes' | translate}}:
  • Data analysis