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Fishspotting: freshwater fish species presence in European river basins – RivFISH database

Title: Fishspotting: freshwater fish species presence in European river basins – RivFISH database
Authors: Mameri Daniel; Duarte Gonçalo; Cabo João; Figueira Rui; Segurado Pedro; Santos José Maria; Ferreira Maria Teresa; Branco Paulo
Source: Knowledge and Management of Aquatic Ecosystems, Vol 0, Iss 426, p 7 (2025)
Publisher Information: EDP Sciences
Publication Year: 2025
Collection: Directory of Open Access Journals: DOAJ Articles
Subject Terms: biodiversity assessments; river basins; species presence; synonyms; interoperability; Aquaculture. Fisheries. Angling; SH1-691
Description: Biodiversity assessments at the river basin level represent a crucial step in drawing conservation strategies for freshwater biota. As river basins are independent functional units, it is fundamental to ensure that spatial information on species presence is fitted to the basins where they effectively occur. To maximize quality and fitness for data usage, scientific names recorded during fish sampling, which may be outdated (synonyms), need to be associated with currently accepted species names. The RivFISH database shows the presence of all native freshwater-dependent fish species in 1554 European river basins, linking data from both synonyms and accepted scientific species names. Spatial data was compiled from a total of 68 references and confronted with the accepted names lists from FishBase, thus ensuring the correspondence of the recorded species name with its current accepted names and river basin presence. RivFISH is composed of six normalized tables reflecting the association between species taxonomy, presence in each river basin, and IUCN risk category, and one denormalized table including all fields for user convenience. Overall, RivFISH includes a total of 707 scientific species names, 667 of which are currently accepted, and aims to facilitate large-scale studies in Europe and promote the interoperability with conservation-related datasets.
Document Type: article in journal/newspaper
Language: English
Relation: https://www.kmae-journal.org/articles/kmae/full_html/2025/01/kmae250001/kmae250001.html; https://doaj.org/toc/1961-9502; https://doaj.org/article/c7ae816460334ee4b361ea480bf8c65b
DOI: 10.1051/kmae/2025002
Availability: https://doi.org/10.1051/kmae/2025002; https://doaj.org/article/c7ae816460334ee4b361ea480bf8c65b
Accession Number: edsbas.E8D36E5F
Database: BASE