A species-level trait dataset of bats in Europe and beyond

Author:

Froidevaux Jérémy S. P.ORCID,Toshkova NiaORCID,Barbaro LucORCID,Benítez-López AnaORCID,Kerbiriou Christian,Le Viol Isabelle,Pacifici Michela,Santini Luca,Stawski Clare,Russo DaniloORCID,Dekker Jasja,Alberdi AnttonORCID,Amorim FranciscoORCID,Ancillotto Leonardo,Barré Kévin,Bas Yves,Cantú-Salazar LisetteORCID,Dechmann Dina K. N.,Devaux Tiphaine,Eldegard Katrine,Fereidouni Sasan,Furmankiewicz Joanna,Hamidovic DanielaORCID,Hill Davina L.ORCID,Ibáñez CarlosORCID,Julien Jean-François,Juste Javier,Kaňuch Peter,Korine Carmi,Laforge Alexis,Legras Gaëlle,Leroux CamilleORCID,Lesiński Grzegorz,Mariton LéaORCID,Marmet Julie,Mata Vanessa A.,Mifsud Clare M.,Nistreanu VictoriaORCID,Novella-Fernandez Roberto,Rebelo Hugo,Roche Niamh,Roemer Charlotte,Ruczyński Ireneusz,Sørås Rune,Uhrin Marcel,Vella Adriana,Voigt Christian C.,Razgour Orly

Abstract

AbstractKnowledge of species’ functional traits is essential for understanding biodiversity patterns, predicting the impacts of global environmental changes, and assessing the efficiency of conservation measures. Bats are major components of mammalian diversity and occupy a variety of ecological niches and geographic distributions. However, an extensive compilation of their functional traits and ecological attributes is still missing. Here we present EuroBaTrait 1.0, the most comprehensive and up-to-date trait dataset covering 47 European bat species. The dataset includes data on 118 traits including genetic composition, physiology, morphology, acoustic signature, climatic associations, foraging habitat, roost type, diet, spatial behaviour, life history, pathogens, phenology, and distribution. We compiled the bat trait data obtained from three main sources: (i) a systematic literature and dataset search, (ii) unpublished data from European bat experts, and (iii) observations from large-scale monitoring programs. EuroBaTrait is designed to provide an important data source for comparative and trait-based analyses at the species or community level. The dataset also exposes knowledge gaps in species, geographic and trait coverage, highlighting priorities for future data collection.

Funder

RCUK | Natural Environment Research Council

Leverhulme Trust

Région Bretagne: SAD grant number 19041

Bulgarian National Science Fund

Publisher

Springer Science and Business Media LLC

Subject

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

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