Report of the Task Group on GBIF Data Fitness for Use in Distribution Modelling


The Task Group on Data Fitness for Use in Distribution Modelling was established by the GBIF Secretariat to help improve the usefulness of GBIF-mediated data for the distribution modelling research community.

The task group has consulted experts, gathered opinions and present their insights on the current situation, challenges and recommendations in this report. The report draws on survey results from the distribution modelling research community and the group’s own views as well as input gathered at ‘Frontiers of Biodiversity Informatics and Modelling Species Distributions’. The November 2015 event, hosted by the Center for Biodiversity and Conservation at the American Museum of Natural History, represented the public face of a three-day working meeting for the task group, held at both AMNH and the City College of New York, City University of New York.

The Secretariat invites the expert community to share their specific use cases and experiences in working with GBIF-mediated data using the template available on this page. Completed templates may be sent to

Read bios of task group members and the group's terms of reference


The main recommendations of the task group are:

  • should serve indicators of precision, quality, and uncertainty of data that can be calculated practically, and preferably “on the fly”, as well as summaries and metrics of completeness of inventories, at scales and for regions defined by the user. The summaries should display maps and graphs of completeness by region, time-period and taxa.
  • The implementation of the GBIF information resource should go beyond unique identifiers of queries (DOIs for downloads, including the capability to re-run queries,, and to include identifiers of the individual data that make up the queried data.
  • should include applications or functionalities enabling users to annotate errors or problems, and communicate those changes directly to providers, as it may be practical and appropriate. This point may need to be discussed with providers.
  • A procedure enabling users to make accessible versions of their databases that have been improved and annotated should be supported, but this functionality should not lose the vital tie back to the original data records and the actual data provider.
  • GBIF should partner with and/or support initiatives to train and guide users on the proper use of the data; such initiatives should incorporate actual expert uses in ENM/SDM to assure that current best practices are followed.


Robert P. Anderson, City University of New York, USA
Miguel Araújo, Museo Nacional de Ciencias Naturales, Spain
Antoine Guisan, University of Lausanne, Switzerland
Jorge M. Lobo, Museo Nacional de Ciencias Naturales, Spain
Enrique Martínez-Meyer, Universidad Nacional Autónoma de México, Mexico
A. Townsend Peterson, University of Kansas, USA
Jorge Soberón, University of Kansas, USA


GBIF Secretariat