A novel integrative method for measuring body condition in ecological studies based on physiological dysregulation

Abstract: The body condition of free-ranging animals affects their ability to fulfil their vital needs, their response to stress, their decisions, and ultimately their fitness, with important evolutionary consequences. It is thus a key attribute that ecologists commonly aim to measure, but remains poorly defined and difficult to measure. As recently suggested, ideally a measure of condition should reflect the capacity of an organism to maintain the functionality of cellular processes. We propose a method that provides a holistic assessment of condition, allowing us to position individuals along a gradient from a ‘normal/optimal’ to ‘abnormal/suboptimal’ physiological state. To do so, we make use of the joint probability distribution of multiple physiological biomarkers by computing Mahalanobis multivariate distance over a set of biomarkers. We illustrate the potential of this method by applying it to physiological data collected on a migratory bird, the red knot, during a yearlong experiment. In this experiment, metabolism, immunity, inflammation and other physiological functions were measured on captive birds caught in the wild. We found that birds with a greater Mahalanobis distance had a lower maximal thermogenic capacity and higher scores of inflammation. Moreover, all biomarkers except one (haematocrit) showed no significant relationship with the same response variables, indicating that Mahalanobis distance captured a signal on condition that was not detected in individual biomarkers. Mahalanobis distance provides a powerful way to measure condition that accounts for its multivariate nature as well as for the integration of physiological functions into complex regulatory networks. As we discuss, this approach should also prove useful to study a variety of questions in ecophysiology and evolutionary ecology, such as the relationship between physiological dysregulation and environmental quality, the risk of outcomes such as infections or the mechanisms of adaptive phenotypic plasticity or those behind long-term processes like senescence