Trait-based approaches are becoming extremely common in ecological modeling and the availability of traits databases is increasing. However, data availability is often biased towards particular regions and taxa, with many taxa (e.g., bats) often under-represented. Here, we present the AfroBaT dataset, a compilation of trait data on 320 African bat species containing 76,914 values for 86 traits focusing on morphology, reproduction, life-history, trophic ecology, and species distributions. All data were gathered from published literature following the ecological trait-data standard procedure. Missing data for both numerical and categorical traits were imputed with a machine learning approach including species phylogeny. Trophic ecology traits showed the highest coverage in the literature (72% of the species averaged over all traits), while reproductive traits the lowest. Our data imputation improved the coverage of AfroBaT especially for reproductive traits, going from 27% to 58% of the species covered. AfroBaT has a range of potential applications in macroecology and community ecology, and the availability of open-access data on African bats will enable collaboration and data-sharing among researchers.

A dataset on African bats’ functional traits / Cosentino, Francesca; Castiello, Giorgia; Maiorano, Luigi. - In: SCIENTIFIC DATA. - ISSN 2052-4463. - 10:1(2023). [10.1038/s41597-023-02472-w]

A dataset on African bats’ functional traits

Francesca Cosentino
Primo
;
Giorgia Castiello
Secondo
;
Luigi Maiorano
Ultimo
2023

Abstract

Trait-based approaches are becoming extremely common in ecological modeling and the availability of traits databases is increasing. However, data availability is often biased towards particular regions and taxa, with many taxa (e.g., bats) often under-represented. Here, we present the AfroBaT dataset, a compilation of trait data on 320 African bat species containing 76,914 values for 86 traits focusing on morphology, reproduction, life-history, trophic ecology, and species distributions. All data were gathered from published literature following the ecological trait-data standard procedure. Missing data for both numerical and categorical traits were imputed with a machine learning approach including species phylogeny. Trophic ecology traits showed the highest coverage in the literature (72% of the species averaged over all traits), while reproductive traits the lowest. Our data imputation improved the coverage of AfroBaT especially for reproductive traits, going from 27% to 58% of the species covered. AfroBaT has a range of potential applications in macroecology and community ecology, and the availability of open-access data on African bats will enable collaboration and data-sharing among researchers.
2023
trait-ecology; chiroptera; ecological modeling
01 Pubblicazione su rivista::01a Articolo in rivista
A dataset on African bats’ functional traits / Cosentino, Francesca; Castiello, Giorgia; Maiorano, Luigi. - In: SCIENTIFIC DATA. - ISSN 2052-4463. - 10:1(2023). [10.1038/s41597-023-02472-w]
File allegati a questo prodotto
File Dimensione Formato  
Cosentino_Dataset_2023.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 1.34 MB
Formato Adobe PDF
1.34 MB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1690184
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact