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Great Basin Naturalist

Abstract

Three condition models for wintering Northern Pintails (Anas acuta) were tested for their ability to predict fat mass, logarithm of fat mass, or a condition index (CI) incorporating fat mass. Equations generated to predict fat mass and the logarithm of fat mass accounted for more than 69% of the variation in these dependent variables. Log transformations of body mass, wing length, and total length explained at least 60% of the variation in CI. All models performed better on an independent data set. Mean prediction error was minimal (≤8% of measured variables) and negative for all models. Regression models apply to live and dead pintails and thus represent tools that have utility in a wide variety of studies on pintail condition.

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