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

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.
This work was funded by the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (funded by the German Research Foundation; DFG FZT 118). We thank Jitendra Gaikwad for his precious help with the technical aspects of the database storage and management through the iDiv Biodiversity Portal (https://idata.idiv.de/, https://doi.org/10.25829/idiv.286-21-2695) and the iDiv IT Support for their help in the CESTES website development (https://icestes.github.io/). The datasets provided by A. Jeliazkov were collected with financial support from the Fédération d’Ile-de-France pour la Recherche en Environnement (FIRE FR-3020). The dataset provided by R. Carvalho and F.L. Tejerina-Garro had financial support from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq No. 471283/2006-1) granted to FLTG. The datasets provided by R. van Klink, J.-Y. Humbert, R. Arlettaz and M.H.M. Menz were collected with financial support from the Swiss National Science Foundation (grants 31003A_125398/2 and 31003A_149656) awarded to RA.