Skeletal traits for thousands of bird species v1.0
Data files
Apr 23, 2025 version files 4.99 MB
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Complete_Trait_Dataset_v1.csv
2.15 MB
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README.md
10.55 KB
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Skelevision_Only_Dataset_v1.csv
1.31 MB
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Skelevision_species_complete_v1.csv
1.52 MB
Nov 05, 2025 version files 4.98 MB
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Complete_Trait_Dataset_v1.csv
2.15 MB
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README.md
10.57 KB
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Skelevision_Only_Dataset_v1.csv
1.31 MB
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Skelevision_species_complete_v1.1.csv
1.51 MB
Abstract
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 3) a species-mean dataset based on a model of trait evolution that includes estimates of the species mean, species-level standard error, variance, and 95% confidence interval of the trait estimates.
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. (2024) and includes estimates of uncertainty associated with each estimated species mean trait value.
References
Weeks, B.C., Z., Zhou, B.K. O'Brien, R. Darling, M. Dean, T. Dias, G. Hassena, M. Zhang, and D.F. Fouhey. 2023. A deep neural network for high-throughput measurement of functional traits on museum skeletal specimens. Methods in Ecology and Evolution 14(2): 347-359), and implemented as described in Weeks et al. 2024.
Weeks, B.C., Z. Zhou, C.M. Probst, J.S. Berv, B.K. O'Brien, B.W. Benz, H.R. Skeen, M. Ziebell, L. Bodt, and D.F. Fouhey. Skeletal trait measurements for thousands of bird species. bioRxiv.
Files and variables
File: Skelevision_Only_Dataset_v1.csv
Description: For skeletal elements that occur in pairs within an individual the measurements presented are either the means of two high quality measures of the element (e.g. if both sclerotic rings were confidently measured, the data for sclerotic ring is the mean of these to measures) or are the single high quality measure made on that specimen. See Weeks et al. (2023) and Weeks et al. (2024) for more detail.
Variables
- ID: Natural history museum institutional code followed by the specimen catalog number for each row of data.
- species: Species binomial for the specimen, following the Birdlife V3 taxonomy.
- tarsus: Length of the tibiotarsus in millimeters.
- ulna: Length of the ulna in millimeters.
- cv.skull.1: Length of the distance from the tip of the bill to the back of the skull in millimeters.
- second_digit: Length of the 2nd Digit 1st Phalanx in millimeters.
- sclerotic_ring: The longest distance across the outer diameter of the sclerotic ring in millimeters.
- metatarsus: Length of the tarsometatarsus in millimeters.
- cv.keel.1: Length of the keel in millimeters.
- humerus: Length of the humerus in millimeters.
- cv.furcula.1: Length of the longest linear dimension of the furcula in millimeters.
- femur: Length of the femur in millimeters.
- carpometacarpus: Length of the carpometacarpus in millimeters.
- radius: Length of the radius in millimeters.
File: Complete_Trait_Dataset_v1.csv
Description: A specimen-level dataset not missing any data. The dataset includes both measures directly made with Skelevision and imputed using evolutionary models if direct measurements were not confidently made. For skeletal elements that occur in pairs within an individual the measurements presented are either the means of two high quality measures of the element (e.g. if both sclerotic rings were confidently measured, the data for sclerotic ring is the mean of these to measures) or are the single high quality measure made on that specimen. See Weeks et al. (2023) and Weeks et al. (2024) for more detail.
Variables
- ID: Natural history museum institutional code followed by the specimen catalog number for each row of data.
- species: Species binomial for the specimen, following the Birdlife V3 taxonomy.
- tarsus: Length of the tibiotarsus in millimeters.
- ulna: Length of the ulna in millimeters.
- cv.skull.1: Length of the distance from the tip of the bill to the back of the skull in millimeters.
- second_digit: Length of the 2nd Digit 1st Phalanx in millimeters.
- sclerotic_ring: The longest distance across the outer diameter of the sclerotic ring in millimeters.
- metatarsus: Length of the tarsometatarsus in millimeters.
- cv.keel.1: Length of the keel in millimeters.
- humerus: Length of the humerus in millimeters.
- cv.furcula.1: Length of the longest linear dimension of the furcula in millimeters.
- femur: Length of the femur in millimeters.
- carpometacarpus: Length of the carpometacarpus in millimeters.
- radius: Length of the radius in millimeters.
File: Skelevision_species_complete_v1.1.csv
Description: This is a complete species-level dataset that presents mean values for each trait for each species, derived from fitted evolutionary models of trait evolution as outlined in Weeks et al. (2024) along with several estimates of uncertainty.
Variables
- Species: Species binomial for the specimen, following the Birdlife V3 taxonomy.
- Tarsus: Length of the tibiotarsus in millimeters.
- Ulna: Length of the ulna in millimeters.
- Skull: Length of the distance from the tip of the bill to the back of the skull in millimeters.
- Second_Digit: Length of the 2nd Digit 1st Phalanx in millimeters.
- Sclerotic_Ring: The longest distance across the outer diameter of the sclerotic ring in millimeters.
- Metatarsus: Length of the tarsometatarsus in millimeters.
- Keel: Length of the keel in millimeters.
- Humerus: Length of the humerus in millimeters.
- Furcula: Length of the longest linear dimension of the furcula in millimeters.
- Femur: Length of the femur in millimeters.
- Carpometacarpus: Length of the carpometacarpus in millimeters.
- Radius: Length of the radius in millimeters.
- Tarsus_SE: Estimated standard error in millimeters of the tibiotarsus length.
- Ulna_SE: Estimated standard error in millimeters of the ulna length.
- Skull_SE: Estimated standard error in millimeters of the skull length.
- Second_Digit_SE: Estimated standard error in millimeters of the second digit length.
- Sclerotic_Ring_SE: Estimated standard error in millimeters of the sclerotic ring diameter.
- Metatarsus_SE: Estimated standard error in millimeters of the metatarsus length.
- Keel_SE: Estimated standard error in millimeters of the keel length.
- Humerus_SE: Estimated standard error in millimeters of the humerus length.
- Furcula_SE: Estimated standard error in millimeters of the furcula length.
- Femur_SE: Estimated standard error in millimeters of the femur length.
- Carpometacarpus_SE: Estimated standard error in millimeters of the carpometacarpus length.
- Radius_SE: Estimated standard error in millimeters of the radius length.
- Tarsus_VAR: Estimated variance in millimeters^2 of the tibiotarsus length.
- Ulna_VAR: Estimated variance in millimeters^2 of the ulna length.
- Skull_VAR: Estimated variance in millimeters^2 of the skull length.
- Second_Digit_VAR: Estimated variance in millimeters^2 of the second digit length.
- Sclerotic_Ring_VAR: Estimated variance in millimeters^2 of the sclerotic ring diameter.
- Metatarsus_VAR: Estimated variance in millimeters^2 of the metatarsus length.
- Keel_VAR: Estimated variance in millimeters^2 of the keel length.
- Humerus_VAR: Estimated variance in millimeters^2 of the humerus length.
- Furcula_VAR: Estimated variance in millimeters^2 of the furcula length.
- Femur_VAR: Estimated variance in millimeters^2 of the femur length.
- Carpometacarpus_VAR: Estimated variance in millimeters^2 of the carpometacarpus length.
- Radius_VAR: Estimated variance in millimeters^2 of the radius length.
- Tarsus_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of tibiotarsus length.
- Tarsus_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of tibiotarsus length.
- Ulna_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of ulna length.
- Ulna_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of ulna length.
- Skull_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of skull length.
- Skull_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of skull length.
- Second_Digit_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of second digit length.
- Second_Digit_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of second digit length.
- Sclerotic_Ring_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of sclerotic ring diameter.
- Sclerotic_Ring_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of sclerotic ring diameter.
- Metatarsus_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of metatarsus length.
- Metatarsus_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of metatarsus length.
- Keel_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of keel length.
- Keel_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of keel length.
- Humerus_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of humerus length.
- Humerus_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of humerus length.
- Furcula_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of furcula length.
- Furcula_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of furcula length.
- Femur_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of femur length.
- Femur_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of femur length.
- Carpometacarpus_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of carpometacarpus length.
- Carpometacarpus_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of carpometacarpus length.
- Radius_LowerCI: Estimated lower bound in millimeters of the 95% confidence interval of radius length.
- Radius_UpperCI: Estimated upper bound in millimeters of the 95% confidence interval of radius length.
Code/software
The datasets are saved as comma separated values (.csv files) and can be viewed in any software that can open this file type.
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. (2024).
References:
Goolsby, E.W., J. Bruggeman, and C. Ané. 2017. Rphylopars: fast multivariate phylogenetic comparative methods for missing data and within-species variation. Methods in Ecology and Evolution 8(1): 22-27.
Weeks, B.C., Z. Zhou, B.K. O'Brien, R. Darling, M. Dean, T. Dias, G. Hassena, M. Zhang, and D.F. Fouhey. 2023. A deep neural network for high-throughput measurement of functional traits on museum skeletal specimens. Methods in Ecology and Evolution. 14(2): 347-359.
Weeks, B.C., Z. Zhou, C.M. Probst, J.S. Berve, B.K. O'Brien, B.W. Benz, H.R. Skeen, M. Ziebell, L. Bodt, and D.F. Fouhey. 2024. Skeletal trait measurements for thousands of bird species. bioRxiv. https://doi.org/10.1101/2024.12.19.629481
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.
- Weeks, Brian C.; Zhou, Zhizhuo; Probst, Charlotte M. et al. (2024). Skeletal trait measurements for thousands of bird species [Preprint]. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2024.12.19.629481
- Weeks, Brian C.; Zhou, Zhizhuo; O'Brien, Bruce K. et al. (2022). A deep neural network for high‐throughput measurement of functional traits on museum skeletal specimens. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210x.13864