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

Jérémy S.P. Froidevaux, Nia Toshkova, Luc Barbaro, Ana Benítez-López, Christian Kerbiriou, Isabelle Le Viol, Michela Pacifici, Luca Santini, Clare Stawski, Danilo Russo, Jasja Dekker, Antton Alberdi, Francisco Amorim, Leonardo Ancillotto, Kévin Barré, Yves Bas, Lisette Cantú-Salazar, Dina K.N. Dechmann, Tiphaine Devaux, Katrine EldegardSasan Fereidouni, Joanna Furmankiewicz, Daniela Hamidovic, Davina L. Hill, Carlos Ibáñez, Jean François Julien, Javier Juste, Peter Kaňuch, Carmi Korine, Alexis Laforge, Gaëlle Legras, Camille Leroux, Grzegorz Lesiński, Léa Mariton, Julie Marmet, Vanessa A. Mata, Clare M. Mifsud, Victoria Nistreanu, Roberto Novella-Fernandez, Hugo Rebelo, Niamh Roche, Charlotte Roemer, Ireneusz Ruczyński, Rune Sørås, Marcel Uhrin, Adriana Vella, Christian C. Voigt, Orly Razgour

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Knowledge 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 We compiled the bat trait data obtained from three main sources: (i) a systematic literature and dataset search, (ii) unpublished data from European bat experts, and (iii) observations from large-scale monitoring programs.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.

Original languageEnglish
Article number253
JournalScientific data
Volume10
Issue number1
DOIs
StatePublished - 1 Dec 2023

ASJC Scopus subject areas

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

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