Abstract

We developed a predictive model to estimate body fat stores in a population of North American porcupines, Erethizon dorsatum (L., 1758). We trapped porcupines in the autumn of 2004 and spring of 2005. After collecting morphometric measurements on each animal, we used a plethysmograph to perform bioelectrical impedance analysis (BIA). We euthanized the subjects, measured two components of body composition (body fat, body water) via direct chemical analysis, and calculated lean dry mass to compare with BIA data. With regression we found the best predictive models for total body water, total body fat, percent body fat, and lean dry mass. We also estimated body condition for each animal using six different condition indices and compared the ability of the condition indices and our regression model to predict total body fat. Our model for total body fat accounted for 84% of the variation in fat measured by direct chemical analysis, and our model for percent body fat accounted for 78% of the variation. Two condition indices were significantly related to total body fat in porcupines and explained 45%–49% of the variation in observed body fat. We recommend BIA as a useful technique for estimating body fat stores in field studies of free-ranging porcupines and suggest abandonment of the use of condition indices as analogues of body fat stores in animal studies unless the indices can first be validated.

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