Skeletal traits for thousands of bird species v1.0

The dataset spans 2,057 species of birds (Aves: Passeriformes) and includes linear 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. The traits included in the dataset are: the lengths of the tibiotarsus, humerus, tarsometatarsus, ulna, radius, keel, carpometacarpus, 2nd digit 1st phalanx, furcula, and femur; the maximum outer diameter of the sclerotic ring, and the length from the back of the skull to the tip of the bill (treating the rhamphotheca as part of the bill when it remains present on the specimen). These data are presented in three ways: 1) a dataset that only includes trait estimates for elements that were confidently identified and measured, 2) a complete specimen-level dataset that includes imputed trait values for all missing data, and ..., These data were collected from museum skeletal specimens. To measure traits, images were taken of skeletal specimens and then Skelevision, a computer vision method, was used to segment out the bones in the images, identify them, and measure them; this method is described in detail in Weeks et al. (2023). In addition to presenting the data that were generated using Skelevision, we generated a 100% complete dataset by imputing all missing values in the dataset using Rphylopars (Goolsby et al. 2017), which is a method for fitting multivariate phylogenetic models and estimating missing values in comparative data.  We also present species-level means along with associated estimates of uncertainty derived from the Rphylopars model. We validated the Skelevision estimates by comparing them to handmade measurements, and we assessed the trait imputation accuracy by withholding data and imputing the withheld values. The validation procedure and results are outlined in detail in Weeks et al. (..., , # Skeletal Traits for Thousands of Bird Species v1.0

[https://doi.org/10.5061/dryad.v41ns1s4c](https://doi.org/10.5061/dryad.v41ns1s4c)

## Description of the data and file structure

The data presented here were generated using photographs of museum skeletal specimens. These data were used to generate three versions of the dataset:

1\) Skelevision Only Dataset v1. This version of the dataset only includes traits that were confidently measured using the Skelevision computer vision pipeline, described in detail in Weeks et al. (2023), and implemented as described in Weeks et al. (2024).

2\) Complete Trait Dataset v1. This version of the dataset includes a complete specimen-level dataset. It was generated by imputing all missing trait values using evolutionary models as described and validated in Weeks et al. (2024).

3\) Skelevision species complete v1.1. This version of the dataset presents species mean trait values generated using evolutionary models, as outlined in Weeks et al. (20..., , **Changes after Apr 23, 2025:**  In our initial Skelevision_species_complete_v1.csv file, values were reported in log space.  To increase accessibility, on November 5, 2025, we updated this dataset with a new version - Skelevision_species_complete_v1.1.csv - in which trait means, standard errors, and 95% confidence intervals are all reported in their original measurement units (mm for trait means, standard errors, and 95% confidence intervals, and mm^2 for variance).  

Trait means are back-transformed estimates from a log-scale phylogenetic model (i.e. geometric means). Standard errors and variance on the original scale were obtained via the delta method and 95% confidence intervals were computed on the log scale and then back-transformed.