AmphiBIO, a global database for amphibian ecological traits

Current ecological and evolutionary research are increasingly moving from species- to trait-based approaches because traits provide a stronger link to organism’s function and fitness. Trait databases covering a large number of species are becoming available, but such data remains scarce for certain groups. Amphibians are among the most diverse vertebrate groups on Earth, and constitute an abundant component of major terrestrial and freshwater ecosystems. They are also facing rapid population declines worldwide, which is likely to affect trait composition in local communities, thereby impacting ecosystem processes and services. In this context, we introduce AmphiBIO, a comprehensive database of natural history traits for amphibians worldwide. The database releases information on 17 traits related to ecology, morphology and reproduction features of amphibians. We compiled data from more than 1,500 literature sources, and for more than 6,500 species of all orders (Anura, Caudata and Gymnophiona), 61 families and 531 genera. This database has the potential to allow unprecedented large-scale analyses in ecology, evolution, and conservation of amphibians. Design Type(s) data integration objective • database creation objective • species comparison design Measurement Type(s) ecological traits Technology Type(s) data item extraction from journal article Factor Type(s) Species Sample Characteristic(s) Anura • Caudata • Gymnophiona Design Type(s) data integration objective • database creation objective • species comparison design Measurement Type(s) ecological traits Technology Type(s) data item extraction from journal article Factor Type(s) Species Sample Characteristic(s) Anura • Caudata • Gymnophiona Machine-accessible metadata file describing the reported data (ISA-Tab format)

• Publication year

  2017

• Venue

  Scientific Data

• Publication date

  2017-09-05

• Fields of study

  Biology, Medicine, Environmental Science

• Identifiers
  DOI 10.1038/sdata.2017.123PMID 28872632PMCID 5584397
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• : A Review of the

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