JOURNAL ARTICLE

AfriBasins: a new framework in FishBase for the analysis of African fresh and brackish water fish distributions, with a discussion on the Congo basin fauna.

  • Published In: Cybium: International Journal of Ichthyology, 2023, v. 47, n. 3. P. 287 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Musschoot, Tobias; BODEN, Gert; SNOEKS, Jos 3 of 3

Abstract

A new Africa-wide framework for the analysis of fresh and brackish water fish distributions, AfriBasins, is presented. River and lake basins and subbasins are delimited in a standardised way, based on the HydroBasins dataset. To illustrate its potential, this framework is used to analyse the distribution of fish species within the Congo basin. Four large clusters could be recognised: the Upper Congo basin and the closely associated Kasai drainage, which together form the southern Congo basin cluster that shows some affinities with southern Africa; the Lower Congo basin cluster, characterised by many marine and brackish species in its lower part and a largely endemic fauna further upstream; the northern and north-eastern Congo basin cluster, including the Middle Congo River main channel and its right bank tributaries upstream from and including the Ubangi; and the central left bank affluents of the Middle Congo and the north-western Congo basin cluster, with the Sangha showing affinities with the neighbouring Lower Guinean ichthyofaunal province. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Cybium: International Journal of Ichthyology. 2023/07, Vol. 47, Issue 3, p287
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:0399-0974
  • DOI:10.26028/cybium/2023-024
  • Accession Number:165033285
  • Copyright Statement:Copyright of Cybium: International Journal of Ichthyology is the property of Societe Francaise d'Ichtyologie (SFI) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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