DOI: 10.5061/dryad.7wm37pw4h
title: Data from: Longer wing bones in warmer climates suggest a role of thermoregulation in bird wing evolution

description: The tendency for animals in warmer climates to be longer-limbed (Allen’s
 Rule) is widely attributed to the demands of thermoregulation. The role
 played by thermoregulation in structuring bird wings, however, has been
 overshadowed by the selective demands placed on wings by
 flight. Using computer vision, we measure wing bone length from
 photographs of museum skeletal specimens for 1,520 species of passerine
 birds. We then model the relationship between wing bone length and
 temperature, accounting for allometry, the demands of flight efficiency
 and maneuverability, and a range of ecological and environmental
 variables.  We find that wing bones are longer in warmer
 climates. Our models, largely as a result of allometric effects, explain
 nearly all the variation in wing bone length in our data, with a marginal
 R2 = 0.80 and a conditional R2 &gt; 0.99.  Thus, across 1,520
 species of birds, higher temperatures are associated with longer wing
 bones, as predicted by Allen’s Rule. The vascularized musculature along
 these bones is maximally uncovered when birds actively hold their wings
 away from their bodies to aid in cooling or during flight. Conversely, the
 musculature along the wing bones is insulated by feathering when at rest,
 such that wings play a minor role in heat exchange when individuals are
 less active and may need to retain heat. While our analyses do not
 directly establish the mechanistic basis underlying the pattern we
 recover, given the asymmetry in the role of wings in thermoregulation, we
 interpret the positive relationship between temperature and wing bone
 length to reflect increased demand for heat dissipation in warmer
 climates. Our findings highlight the role of thermoregulation in shaping
 even the most critical features of vertebrate anatomy.
description: The data were collected by photographing museum skeletal
 specimens and then segmenting, identifying, and measuring the wing bones
 using Skelevision (Weeks et al., 2023). 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.
description: # Longer wing bones in warmer climates suggest a role of thermoregulation
 in bird wing evolution
 [https://doi.org/10.5061/dryad.7wm37pw4h](https://doi.org/10.5061/dryad.7wm37pw4h) ## Description of the data and file structure These data were produced using computer vision to analyze photographs of museum skeletal specimens.  ### Files and variables #### File: DataS2-Bird\_Phylogeny\_8-17-21.tre **Description:**  This is a consensus phylogeny produced using 1,000 samples from the posterior distribution of the Jetz et al. 2012 phylogeny based on the Hackett et al. 2008 backbone tree following the procedure outlined in Rubolini et al. 2015.   References: Jetz et al. 2012. The global diversity of birds in space and time. Nature 491: 444-448. Hackett et al. 2008. A phylogenomic study of birds reveals their evolutionary history. Science 320(5884): 1763-1768. Rubolini et al. 2015. Using the BirdTree.org website to obtain robust phylogenies for avian comparative studies: A primer. Current Zoology 61(6): 959-965. #### File: DataS1-SpecimenData\_8-9-24.csv **Description:** Data for 7,366 skeletal specimens spanning 1,520 species of passerine birds.  Throughout, any missing values are indicated with an "NA". ##### Variables * Institution: The collection in which each specimen is accessioned. All specimens came from the University of Michigan Museum of Zoology (UMMZ) collection * Specimen.Number: The UMMZ catalog number for each species * Family: The family-level classification of the specimen following the UMMZ taxonomy * Genus: The genus-level classification of the specimen following the UMMZ taxonomy * Species: The species name of the specimen following the UMMZ taxonomy * humerus.1: The length of one humerus bone in the image of the specimen, estimated by Skelevision (in millimeters) * humerus.1.bprob: The "bprob" associated with the identification of the bone that is measured in humerus.1 (see Weeks et al. 2022 for a description of bprob). * humerus.2: The length of a second humerus bone in the image of the specimen, estimated by Skelevision (in millimeters) * humerus.2.bprob: The "bprob" associated with the identification of the bone that is measured in humerus.2 (see Weeks et al. 2022 for a description of bprob). * ulna.1: The length of one ulna bone in the image of the specimen, estimated by Skelevision (in millimeters) * ulna.1.bprob: The "bprob" associated with the identification of the bone that is measured in ulna.1 (see Weeks et al. 2022 for a description of bprob). * ulna.2: The length of a second ulna bone in the image of the specimen, estimated by Skelevision (in millimeters) * ulna.2.bprob: The "bprob" associated with the identification of the bone that is measured in ulna.2 (see Weeks et al. 2022 for a description of bprob). * Birdtree.Tip.Label: The genus and species identity of the specimen following the Birdtree taxonomy * Relaxed.Wing.Chord: The length from the carpal joint to the tip of the longest primary in millimeters for the species to which the specimen belongs (from Tobias et al. 2022) * Trophic.Niche: The primary trophic niche of the species (from Tobias et al. 2022) * Mass: Mass in grams of the species to which the specimen belongs (from Tobias et al. 2022) * Latitude.Centroid: The central latitude of the species' range (from Tobias et al. 2022) * Hand-wing.Index: An index of wing elongation for the species to which the specimen belongs (from Tobias et al. 2022) * Secondary.Length: The length from the carpal joint to the tip of the first secondary feather for the species to which the specimen belongs (from Tobias et al. 2022) * Migration: A categorical index of migration for the species to which the specimen belongs, 1=resident, 2=short-distance/partial migrant, 3=long distance migrant (from Tobias et al. 2022) * BirdLife: The genus and species name following the birdlife international taxonomy * Average.Annual.Temperature: The mean annual temperature, averaged from 1970-2000, averaged across all grid cells within the breeding and resident ranges of the species to which the specimen belongs (temperature data from WorldClim v. 2.1) * Maximum.Temp: The mean maximum temperature of the warmest month from 1970-2000, averaged across all grid cells within the breeding and resident ranges of the species to which the specimen belongs (temperature data from WorldClim v. 2.1) * Average.Temperature.Warmest.Quarter: The mean temperature of the warmest quarter from 1970-2000, averaged across all grid cells within the breeding and resident ranges of the species to which the specimen belongs (temperature data from WorldClim v. 2.1) * Average.Precipitation: The mean precipitation from 1970-2000, averaged across all grid cells in the breeding and resident ranges of the species to which the specimen belongs * Humerus: The mean humerus measurement for the specimen in millimeters, averaging across measures of both humerus measurements if two measurements exist with a high brop for the specimen * Ulna: The mean ulna measurement for the specimen in millimeters, averaging across measures of both ulna measurements if two measurements exist with a high brop for the specimen * Wing.Bone.Length: The sum of the Humerus and Ulna measurements for the specimen ## Code/software The script is written in R (version 4.4.2) and requires the R packages "ape" (version 5.8) and "MCMCglmm" (version 2.36).  References: R Core Team. 2024. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available from: [https://www.R-project.org](https://www.R-project.org). Paradis, E. and K. Schliep. 2019. ape 5.0: an environment for modern phylogenetic and evolutionary analyses in R. Bioinformatics 35: 526-528. Hadfield, J.D. 2010. MCMC Methods for multi-response generalized linear mixed models: the MCMCglmm R package. Journal of Statistical Software 33(2): 1-22. ## Access information Data was derived from the following sources: * Weeks et al. 2024. Skeletal trait measurements for thousands of bird species. bioRxiv. doi: [https://doi.org/10.1101/2024.12.19.629481](https://doi.org/10.1101/2024.12.19.629481) * Tobias et al. 2022. AVONET: morphological, ecological and geographical data for all birds. Ecology Letters 25(3): 581-597. [https://doi.org/10.1111/ele.13898](https://doi.org/10.1111/ele.13898) * Jetz et al. 2012. The global diversity of birds in space and time. Nature 491: 444-448. [https://doi.org/10.1038/nature11631](https://doi.org/10.1038/nature11631)