Opportunities and limitations of large open biodiversity occurrence databases in the context of a Marine Ecosystem Assessment of the Southern Ocean
Bonnet-Lebrun, Anne-Sophie; Sweetlove, Maxime; Griffiths, Huw J. ORCID: https://orcid.org/0000-0003-1764-223X; Sumner, Michael; Provoost, Pieter; Raymond, Ben; Ropert-Coudert, Yan; Van de Putte, Anton P.. 2023 Opportunities and limitations of large open biodiversity occurrence databases in the context of a Marine Ecosystem Assessment of the Southern Ocean. Frontiers in Marine Science, 10, 1150603. 10.3389/fmars.2023.1150603
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Copyright © 2023 Bonnet-Lebrun, Sweetlove, Griffiths, Sumner, Provoost, Raymond, Ropert-Coudert and Van de Putte. fmars-10-1150603.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (3MB) | Preview |
Abstract/Summary
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.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | 10.3389/fmars.2023.1150603 |
ISSN: | 2296-7745 |
Date made live: | 21 Jun 2023 10:40 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/535042 |
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