A global database for metacommunity ecology, integrating species, traits, environment and space

Jeliazkov, A, Mijatovic, D, Chantepie, S ORCID: https://orcid.org/0000-0001-9958-8913, Andrew, N, Arlettaz, R, Meyer, CFJ ORCID: https://orcid.org/0000-0001-9958-8913 and et, al 2020, 'A global database for metacommunity ecology, integrating species, traits, environment and space' , Scientific Data, 7 (1) , p. 6.

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Abstract

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; “CESTES”. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.

Item Type: Article
Schools: Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Journal or Publication Title: Scientific Data
Publisher: Springer Nature
ISSN: 2052-4463
Related URLs:
Funders: German Centre for Integrative Biodiversity Research (iDiv), German Research Foundation, Fédération d’Ile-de-France pour la Recherche en Environnement, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Swiss National Science Foundation
Depositing User: Dr Christoph Meyer
Date Deposited: 09 Jan 2020 11:09
Last Modified: 22 Jan 2020 08:45
URI: http://usir.salford.ac.uk/id/eprint/56184

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