Morphometric indices of body condition in birds: a review

Morphometric estimates of body condition are widely used by ornithologists, but which estimates work best is a matter of debate. We review morphometric approaches (body mass, ratio and residual condition indices, predictive regression models, fat scoring, and abdominal profiles) for estimating body condition (defined as fat mass) in birds. We describe the strengths and weaknesses of each approach. Across diverse indices and species (similar to 200 estimates total), the mean r (2) relating condition indices to mass of body fat was 0.55, and 64% of the r (2) values were greater than 0.50. But despite their generally good performance, condition indices sometimes perform poorly (i.e., r (2) is low). The data indicate that: (1) no single index was clearly best, (2) on average body mass alone, fat scores, and predictive multiple regression equations explained slightly more than 50% of the variation in fat content, (3) on average, ratio and residual indices explained slightly less than 50% of the variation in fat content, and (4) body mass alone, a variable that can be easily and reliably measured, is as good or nearly as good an indicator of fat content as any other condition index. We recommend that: (1) morphometric indicators of condition be empirically validated, (2) researchers publish their body composition data in sufficient detail that they can be used in future analyses exploring the relative merits of different condition indices, and (3) multiple regression directly on measured traits be used instead of condition indices whenever the condition index is not empirically validated.