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This study demonstrates the use of cranial measurements for species identification in birds, suggesting decision tree models enhance accuracy.
Most studies on birds rely on external characteristics, such as plumage, for species identification. However, in many cases, skeletal remains may be the only features available for bird species identification. Our study was designed to understand whether skeletal measurements, specifically cranial measurements, could be used for avian species identification. We hypothesized that like for other taxa (e.g., mammals) skull measurements would be instructive for species identification. We gathered museum specimens representing 12 avian species belonging to three orders: Strigiformes (N=63 individual specimens, 5 species), Accipitriformes (N=26, 5 species), and Passeriformes (N=39, 2 species) collected in Saskatchewan, Canada and measured 15 skull characteristics to aid in species identification. We constructed separate decision tree models for each Order and these models correctly classified between 93-100% of the training data and between 83-100% of the testing data. Our findings support the idea that cranial measurements can be used as a cost effective and accurate tool to identify several closely related species from one geographic location when more reliable identifying features, such as plumage, are not available.
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Walker et al. (2025) studied this question.
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