ArticleData in brief2024
Freshwater fish scale database.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Scales of the ray finned fishes can be used for multiple purposes. Beside others by their specific structure and elemental composition they are usable for age determination and food-web researches. Additionally, just their presence, absence, shape, location, or numbers could provide a reliable taxonomic information. The fish scales show remarkable size variation also, which characteristics provide reliable information about the environmental needs of freshwater fish. But till now this information was not interpretable and comparable in the absence of a sufficiently large and detailed database. In this study we provide a database which can facilitate the further complex comparative studies. Our dataset consists of 2954 scale photos characterising 193 freshwater fish species. All photos have a uniquely identification code showing exactly which species the scale belongs to. In addition to the photos, our database includes a table showing the exact taxonomic classification of the studied species, the average body profile-index, and the relative scale size, as well as the ecological (flow and feeding habitat preferences) and life strategic characteristics (feeding and breeding guild memberships) of each species. The sampled species have diverse origin, covering five biogeographical regions. An average of five adults from each species were selected for sampling. Three-to-four scales were collected from the anterior part of the body between the dorsal fin and the lateral line. The removed scales were cleaned and prepared to microscope slides, and after this process they were photographed or scanned. Our database can be used for both research and educational purposes. A large number of scale photos assigned of species can be an opportunity to create an automatic species identification system. Moreover, the subjectivity in morphometric measurements can be eliminated by analysing the database with artificial intelligence.
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