Abstract
Motivation
Human activities have been reshaping the natural world for tens of thousands of years, leading to the extinction of hundreds of bird species. Past research has provided evidence of extinction selectivity towards certain groups of species, but trait information is lacking for the majority of clades, especially for prehistoric extinctions identified only through subfossil remains. This incomplete knowledge potentially obscures the structure of natural communities, undermining our ability to infer changes in biodiversity across space and time, including trends in functional and phylogenetic diversity. Biases in currently available trait data also limit our ability to identify drivers and processes of extinction. Here we present AVOTREX, an open-access database of species traits for all birds known to have gone extinct in the last 130,000 years. This database provides detailed morphological information for 610 extinct species, along with a pipeline to build phylogenetic trees that include these extinct species.
Main types of variables contained
For each extinct bird species, we provide information on the taxonomy, geographic location, and period of extinction. We also present data on island endemicity, flight ability and body mass, as well as standard measurements of external (matching the AVONET database of extant birds) and skeletal morphology from museum specimens where available. To ensure comprehensive morphological data coverage, we estimate all missing morphological measurements using a data imputation technique based on machine learning. Finally, we provide an R package to graft all extinct species onto a global phylogeny of extant species (BirdTree).
Spatial location and grain
Global.
Time period and grain
All known globally extinct bird species from 130,000 years ago up until 2024.
Major taxa and level of measurement
Birds (Class Aves), species level.
Software format
spreadsheets (.csv) stored in Dryad
Human activities have been reshaping the natural world for tens of thousands of years, leading to the extinction of hundreds of bird species. Past research has provided evidence of extinction selectivity towards certain groups of species, but trait information is lacking for the majority of clades, especially for prehistoric extinctions identified only through subfossil remains. This incomplete knowledge potentially obscures the structure of natural communities, undermining our ability to infer changes in biodiversity across space and time, including trends in functional and phylogenetic diversity. Biases in currently available trait data also limit our ability to identify drivers and processes of extinction. Here we present AVOTREX, an open-access database of species traits for all birds known to have gone extinct in the last 130,000 years. This database provides detailed morphological information for 610 extinct species, along with a pipeline to build phylogenetic trees that include these extinct species.
Main types of variables contained
For each extinct bird species, we provide information on the taxonomy, geographic location, and period of extinction. We also present data on island endemicity, flight ability and body mass, as well as standard measurements of external (matching the AVONET database of extant birds) and skeletal morphology from museum specimens where available. To ensure comprehensive morphological data coverage, we estimate all missing morphological measurements using a data imputation technique based on machine learning. Finally, we provide an R package to graft all extinct species onto a global phylogeny of extant species (BirdTree).
Spatial location and grain
Global.
Time period and grain
All known globally extinct bird species from 130,000 years ago up until 2024.
Major taxa and level of measurement
Birds (Class Aves), species level.
Software format
spreadsheets (.csv) stored in Dryad
Original language | English |
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Article number | e13927 |
Number of pages | 11 |
Journal | Global Ecology and Biogeography |
Early online date | 24 Oct 2024 |
DOIs | |
Publication status | E-pub ahead of print - 24 Oct 2024 |