Abstract
Large comparative datasets of avian functional traits have been used to address a wide range of questions in ecology and evolution. To date, this work has been constrained by the limited availability of skeletal trait datasets that include extensive inter- and intra-specific sampling. We use computer vision to identify and measure bones from photographs of museum skeletal specimens to assemble an extensive dataset of functionally important skeletal elements in birds. The dataset spans 2,057 species of birds (Aves: Passeriformes) and includes measurements of 12 skeletal elements from 14,419 individuals. In addition to the trait values directly measured from photographs, we leverage the multi-dimensional nature of our dataset and known phylogenetic relationships of the species to impute missing data under an evolutionary model. To facilitate use of the dataset, the taxonomy has been reconciled with an existing comprehensive avian phylogeny and an additional dataset of external functional traits for all birds.
Original language | English (US) |
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Article number | 884 |
Journal | Scientific Data |
Volume | 12 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2025 |
ASJC Scopus subject areas
- Statistics and Probability
- Information Systems
- Education
- Computer Science Applications
- Statistics, Probability and Uncertainty
- Library and Information Sciences