1. The body condition of free-ranging animals affects their response to stress, decisions, ability to fulfil vital needs and, ultimately, fitness. However, this key attribute in ecology remains difficult to assess, and there is a clear need for more integrative measures than the common univariate proxies. 2. We propose a systems biology approach that positions individuals along a gradient from a ‘normal/optimal’ to ‘abnormal/suboptimal’ physiological state based on Mahalanobis distance computed from physiological biomarkers. We previously demonstrated the validity of this approach for studying ageing in humans; here, we illustrate its broad potential for ecological studies. 3. As an example, we used biomarker data on shorebirds and found that birds with an abnormal condition had a lower maximal thermogenic capacity and higher scores of inflammation, with important implications for their ecology and health. Moreover, Mahalanobis distance captured a signal of condition not detected by the individual biomarkers. 4. Overall, our results on birds and humans show that individuals with abnormal physiologies are indeed in worse condition. Moreover, our approach appears not to be particularly sensitive to which set of biomarkers is used to assess condition. Consequently, it could be applied easily to existing ecological data sets. 5. Our approach provides a general, powerful way to measure condition that helps resolve confusion as to how to deal with complex interactions and interdependence among multiple physiological and condition measures. It can be applied directly to topics such as the effect of environmental quality on body condition, risks of health outcomes, mechanisms of adaptive phenotypic plasticity, and mechanisms behind long-term processes such as senescence.
The data package contains one dataset:
- This datasets contains data measured over ~1 on shorebirds (Calidris canutus) caught in the wild and kept in captivity. Specifically, the dataset includes 11 physiological biomarkers, two mass measurements, one performance measure (maximal thermogenic capacity), one health variable (foot inflammation) and information about treatment and measurment times for 31 birds. See Milot et al (accompagning paper) and references therein (Vézina et al. 2006; 2011; Buehler et al. 2008) for details about the experimental setup. The data is in excel format and ready for input in R. A sheet also describe each variable.