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A dataset of road-killed vertebrates collected via citizen science from 2014-2020.
Heigl, Florian; Teufelbauer, Norbert; Resch, Stefan; Schweiger, Silke; Stückler, Susanne; Dörler, Daniel.
Afiliación
  • Heigl F; Institute of Zoology, University of Natural Resources and Life Sciences Vienna, Gregor-Mendel-Straße 33, 1180, Vienna, Austria. florian.heigl@boku.ac.at.
  • Teufelbauer N; BirdLife Österreich, Museumsplatz 1/10/7-8, 1070, Wien, Austria.
  • Resch S; apodemus-Privates Institut für Wildtierbiologie OG, Marktstrasse 51, 8967, Haus im Ennstal, Austria.
  • Schweiger S; First Zoological Department, Herpetological Collection, Natural History Museum Vienna, Burgring 7, 1010, Vienna, Austria.
  • Stückler S; First Zoological Department, Herpetological Collection, Natural History Museum Vienna, Burgring 7, 1010, Vienna, Austria.
  • Dörler D; Institute of Zoology, University of Natural Resources and Life Sciences Vienna, Gregor-Mendel-Straße 33, 1180, Vienna, Austria.
Sci Data ; 9(1): 504, 2022 08 17.
Article en En | MEDLINE | ID: mdl-35977947
Data on road-killed animals is essential for assessing the impact of roads on biodiversity. In most European countries data on road-killed huntable wildlife exists, but data on other vertebrate species (e.g. amphibians, reptiles, small mammals) is scarce. Therefore, we conducted a citizen science project on road-killed vertebrates as a useful supplement to data on huntable wildlife collected by public authorities. The dataset contains 15198 reports with 17163 individual road-killed vertebrates collected by 912 participants. The reports were made in 44 countries, but the majority of data was reported in Austria. We implemented a data validation routine which led to three quality levels. Reports in quality level 1 are published via GBIF, reports in quality level 2 via Zenodo and reports in quality level 3 were deleted. The dataset is relevant for the scientific community studying impacts of roads on fauna as well as for those who are responsible for road planning and implementing mitigation measures.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ciencia Ciudadana Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ciencia Ciudadana Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article