Challenges in Creating an American Kestrel Body Condition Index Based on Size-Adjusted Mass

Document Type

Article

Publication Date

12-1-2011

DOI

http://dx.doi.org/10.3356/JRR-10-81.1

Abstract

Size-adjusted mass is a common body condition index (BCI) used to indicate nonstructural energy reserves (fat and protein). BCIs are calculated from ratios of mass divided by a morphometric(s) or residuals of a regression between mass and a morphometric(s). The morphometrics used in BCIs must accurately represent structural size to reliably index energy reserves and, ideally, BCIs should be validated with comparisons to true fat and protein reserves. Many studies of American Kestrels (Falco sparverius) have included BCIs in ecological analyses; unfortunately, few studies have reported how well morphometrics represented structural size or provided validation of BCIs relative to independent measures of energy reserves. We evaluated relationships between several morphometrics and mass to better understand which morphometrics may best represent structural size for two kestrel populations: captive birds at McGill University in Montreal, Canada, and free-living kestrels in southwestern Idaho, U.S.A. We also compared BCIs based on different morphometrics with subjective (visual) fat scores. Our data showed few strong (r > 0.5) correlations between morphometrics and few strong correlations between each morphometric and mass. Moreover, correlations between morphometrics and mass depended on sex and location. Similarly, not all BCIs had statistically significant, positive correlations with subjective fat scores and correlations varied between sexes, suggesting that the reliability of each BCI differed between males and females. The morphometrics that best represent structural size most likely differ between males and females, and information from both sexes should not be combined to create one size measure for kestrels. Unless BCIs for specific American Kestrel subpopulations are validated, mass and additional qualitative information, such as fat scores, may be the most appropriate indicators of fat and protein stores.

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