Sharkipedia: a curated open access database of shark and ray life history traits and abundance time-series

Christopher G. Mull, Nathan Pacoureau, Sebastián A. Pardo, Luz Saldaña Ruiz, Emiliano García-Rodríguez, Brittany Finucci, Max Haack, Alastair Harry, Aaron B. Judah, Wade VanderWright, Jamie S. Yin, Holly K. Kindsvater, Nicholas K. Dulvy

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

15 Citas (Scopus)

Resumen

A curated database of shark and ray biological data is increasingly necessary both to support fisheries management and conservation efforts, and to test the generality of hypotheses of vertebrate macroecology and macroevolution. Sharks and rays are one of the most charismatic, evolutionary distinct, and threatened lineages of vertebrates, comprising around 1,250 species. To accelerate shark and ray conservation and science, we developed Sharkipedia as a curated open-source database and research initiative to make all published biological traits and population trends accessible to everyone. Sharkipedia hosts information on 58 life history traits from 274 sources, for 170 species, from 39 families, and 12 orders related to length (n = 9 traits), age (8), growth (12), reproduction (19), demography (5), and allometric relationships (5), as well as 871 population time-series from 202 species. Sharkipedia relies on the backbone taxonomy of the IUCN Red List and the bibliography of Shark-References. Sharkipedia has profound potential to support the rapidly growing data demands of fisheries management, international trade regulation as well as anchoring vertebrate macroecology and macroevolution.

Idioma originalEnglish
Número de artículo559
PublicaciónScientific data
Volumen9
N.º1
DOI
EstadoPublished - dic. 2022
Publicado de forma externa

Nota bibliográfica

Funding Information:
We thank H. Yan for additional data-mining of shark trends, C.L. Rigby for time-series checking, B. D’Alberto for traits data-mining, for M-J. Juan-Jordá for interpretation of stock assessments, and J. Pollerspöck for assisting with relational references. CM acknowledges support from M.A. MacNeil. This work was supported by both a Small Project Grant to CGM and HKK and a Project Grant to NKD from the Shark Conservation Fund, a philanthropic collaborative that pools expertise and resources to meet the threats facing the world’s sharks and rays. The Shark Conservation Fund is a project of Rockefeller Philanthropy Advisors. Further support was provided by a sponsorship from the Save Our Seas Foundation to CGM. Additional funding was provided by the US National Science Foundation grant DEB-1556779 to HKK, and the Department of Fish and Wildlife Conservation at Virginia Tech. NKD was supported by the Discovery and Accelerator grants from Natural Science and Engineering Research Council and the Canada Research Chair program.

Publisher Copyright:
© 2022, The Author(s).

ASJC Scopus Subject Areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

PubMed: MeSH publication types

  • Dataset
  • Journal Article

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