Opportunities and limitations of large open biodiversity occurrence databases in the context of a Marine Ecosystem Assessment of the Southern Ocean

• Published in: Frontiers in Marine Science
• Main Authors: Anne-Sophie Bonnet-Lebrun, Maxime Sweetlove, Huw J. Griffiths, Michael Sumner, Pieter Provoost, Ben Raymond, Yan Ropert-Coudert, Anton P. Van de Putte
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Media S.A. 2023
• Subjects: OBIS; GBIF; sampling bias; biodiversity data; spatial bias; temporal bias; Science; Q; General. Including nature conservation; geographical distribution; QH1-199.5; Southern Ocean
• Online Access: https://doi.org/10.3389/fmars.2023.1150603; https://doaj.org/article/6966830010c540e7a4a115cc38b91840

The Southern Ocean is a productive and biodiverse region, but it is also threatened by anthropogenic pressures. Protecting the Southern Ocean should start with well-informed Marine Ecosystem Assessments of the Southern Ocean (MEASO) being performed, a process that will require biodiversity data. In this context, open geospatial biodiversity databases such as OBIS and GBIF provide good avenues, through aggregated geo-referenced taxon locations. However, like most aggregated databases, these might suffer from sampling biases, which may hinder their usability for a MEASO. Here, we assess the quality and distribution of OBIS and GBIF data in the context of a MEASO. We found strong spatial, temporal and taxonomic biases in these data, with several biases likely emerging from the remoteness and inaccessibility of the Southern Ocean (e.g., lack of data in the dark and ice-covered winter, most data describing charismatic or well-known taxa, and most data along ship routes between research stations and neighboring continents). Our identification of sampling biases helps us provide practical recommendations for future data collection, mobilization, and analyses.