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Quality assurance of diatom counts in Europe: towards harmonized datasets
Kahlert, M.; Ács, E.; Almeida, S.F.P.; Blanco, S.; Dreßler, M.; Ector, L.; Karjalainen, S.M.; Liess, A.; Mertens, A.; van der Wal, J.; Vilbaste, S.; Werner, P. (2016). Quality assurance of diatom counts in Europe: towards harmonized datasets. Hydrobiologia 772(1): 1-14. http://dx.doi.org/10.1007/s10750-016-2651-8
In: Hydrobiologia. Springer: The Hague. ISSN 0018-8158; e-ISSN 1573-5117, meer
Peer reviewed article  
Beschikbaar in  Auteurs 
Author keywords
    Bioindicator; Identification exercise; Intercalibration; Inter-laboratory comparison; Ring test; European Water Framework Directive
Auteurs  Top 
  • Kahlert, M.
  • Ács, E.
  • Almeida, S.F.P.
  • Blanco, S.
  • Dreßler, M.
  • Ector, L.
  • Karjalainen, S.M.
  • Liess, A.
  • Mertens, A.
  • van der Wal, J.
  • Vilbaste, S.
  • Werner, P.
Abstract
    Investigations on organism ecology, biodiversity and biogeography often use large compiled datasets to extract information on species ecological preferences, which then can be used in environmental assessment. Freshwater benthic diatoms are commonly used in this context. However, it is important that the taxonomic information of the separate diatom datasets is compatible. At present, inconsistencies between diatom datasets, mainly due to differences and uncertainties in diatom identification, may misinform diatom taxon-specific ecological preferences, geographical distribution and water quality assessment. It is our opinion that these inconsistencies in diatom datasets can be reduced with quality assurance (QA), such as identification exercises. However, the results of these exercises must be well documented and well communicated; otherwise, gained knowledge may not spread inter-regionally or internationally. As a first step to reach greater consistency in QA/harmonization studies, this article (1) presents and compares information of existing diatom identification and counting QA from published and grey (non-peer reviewed) European literature to identify advantages and drawbacks of each approach; (2) summarizes taxa that can easily be misidentified according to European identification exercises; and (3) suggests a consistent design of identification exercises for diatom dataset QA.
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