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EuroBaTrait : Base de données sur les traits des chauves-souris en Europe et Projet ARBEEB (...)

Par Jérémy Froidevaux (chargé de recherche au CREA Mont-Blanc, Chamonix)

EuroBaTrait1.0: 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 We compiled the bat trait data obtained from three main sources: (i) a systematic literature and dataset search, (ii) unpublished data from European bat experts, and (iii) observations from large-scale monitoring programs.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.

Pour en savoir plus sur ce datapaper: Froidevaux, J.S.P., Toshkova, N., Barbaro, L. et al. A species-level trait dataset of bats in Europe and beyond. Scientific Data, 10, 253 (2023).

Jérémy nous a aussi présenté son projet ARBEEB en cours dont en voilà un court résumé en anglais":

"Traditional methods for monitoring bumblebees (e.g. visual counting, sweep netting) and associated ecosystem services such as pollination are laborious, thus limiting our ability to monitor over large spatial scales and long temporal periods. Thanks to recent technological and methodological advancements, the use of acoustic sensors with artificial intelligence (AI) offers exciting developments for future monitoring programmes of bumblebees but have not been fully explored yet. The primary aim of this work was to create and develop a new tool for surveying European bumblebee species in a cost-effective and non-invasive way. The objectives were twofold: (i) create an open-access reference library of buzzing sounds from common bumblebee species occurring in the United Kingdom and France, and (ii) develop, train and test AI algorithms for automatically recognizing bumblebee species and behaviour from their buzzes using acoustic sensors. I will present the key results of this work as well as the bioacoustic tool that is under development. Finally, I will discuss whether and how acoustic monitoring of bumblebees has the potential to be transformative for bee ecology and conservation.".

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