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Recommendations for the standardisation of open taxonomic nomenclature for image-based identifications
Horton, T.; Marsh, L.; Bett, B.J.; Gates, A.R.; Jones, D.O.B.; Benoist, N.M.A.; Pfeifer, S.; Simon-Lledó, E.; Durden, J.M.; Vandepitte, L.; Appeltans, W. (2021). Recommendations for the standardisation of open taxonomic nomenclature for image-based identifications. Front. Mar. Sci. 8: 620702. https://hdl.handle.net/10.3389/fmars.2021.620702
In: Frontiers in Marine Science. Frontiers Media: Lausanne. e-ISSN 2296-7745, more
Peer reviewed article  
Available in  Authors 
Keyword
    Marine/Coastal
Author keywords
    image-based analysis; taxonomy; identification; nomenclature;standardisation; biodiversity informatics; taxonomic databases
Project Top | Authors 
  • Flemish contribution to LifeWatch.eu, more
Authors  Top 
  • Horton, T., more
  • Marsh, L.
  • Bett, B.J., more
  • Gates, A.R.
  • Jones, D.O.B.
  • Benoist, N.M.A.
  • Pfeifer, S.
  • Simon-Lledó, E.
  • Durden, J.M.
  • Vandepitte, L., more
  • Appeltans, W., more
Abstract
    This paper recommends best practice for the use of open nomenclature (ON) signs applicable to image-based faunal analyses. It is one of numerous initiatives to improve biodiversity data input to improve the reliability of biological datasets and their utility in informing policy and management. Image-based faunal analyses are increasingly common but have limitations in the level of taxonomic precision that can be achieved, which varies among groups and imaging methods. This is particularly critical for deepsea studies owing to the difficulties in reaching confident species-level identifications of unknown taxa. ON signs indicate a standard level of identification and improve clarity, precision and comparability of biodiversity data. Here we provide examples of recommended usage of these terms for input to online databases and preparation of morphospecies catalogues. Because the processes of identification differ when working with physical specimens and with images of the taxa, we build upon previously provided recommendations for specific use with image-based identifications.
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