Using morphometrics to sex adult and juvenile Soras ( Porzana carolina )

Abstract

Determining the sex and age of individuals can be an essential element of conservation management, wildlife monitoring, and demographic analysis. For many members of the family Rallidae, distinguishing between males and females is challenging, even when the bird is in the hand. The Sora ( Porzana carolina ), a secretive rail that occupies freshwater wetlands throughout the United States and Canada, represents a species that is challenging to sex in the field. Morphometric measurements can help sex birds of an array of species, including rails. However, no comprehensive morphometric model has been fully validated for sexing Soras. We used DNA analysis to confirm the sex of Soras captured in the field and logistic regression models to determine which morphological features were the best predictors of sex. Measurements from 108 Soras (31 hatch year females (HY-F), 29 hatch year males (HY-M), 22 after hatch year females (AHY-F), and 26 after hatch year males (AHY-M) were used to create our logistic regression model. Color definition and connectivity of the auricular patch to eye or nape was used as an additional characteristic in adult birds. Our top-ranked model was further validated using a sample of 72 individuals exhibiting intermediate traits that would be particularly challenging to distinguish in the field. Our top performing model incorporated culmen length and tarsometatarsus length as the features most predictive of sex and had an overall accuracy of 85%. If higher accuracy is desired, an inconclusive band, which eliminates birds of low model score, i.e., scores indicative of inconclusive sex (below + or - 1.2), can be used. The accuracy of remaining birds (75% of sample) will be increased to 95%. Our model shows that simple measurements of culmen and tarsometatarsus is useful in discriminating the sex of a large percentage of live-caught Soras. This morphometric model will facilitate further demographic studies of this species and may be useful in designing morphometric studies of other species in the family Rallidae.

Keywords

• logistic regression
• non-invasive sexing
• sex-linked morphology
• sexual dimorphism
• sora
• rallidae