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

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.1. 野生自由活动动物的身体状况会影响其应激反应、决策行为、满足核心生存需求的能力，并最终影响其适合度（fitness）。然而，生态学中的这一关键属性仍难以量化评估，且亟需比常用单变量替代指标更为整合的测量手段。2. 我们提出了一种系统生物学方法，该方法基于由生理生物标志物（physiological biomarkers）计算得到的马氏距离（Mahalanobis distance），将个体置于从“正常/最优”到“异常/次优”生理状态的梯度轴上。我们此前已验证了该方法在人类衰老研究中的有效性；本文中，我们将展示其在生态学研究中的广泛应用潜力。3. 作为示例，我们使用了滨鸟（shorebirds）的生物标志物数据，结果发现生理状态异常的滨鸟具有更低的最大产热能力，同时炎症评分更高，这对其生态学特征与健康状况具有重要意义。此外，马氏距离捕捉到了单个生物标志物无法检测到的身体状况信号。4. 总体而言，我们在鸟类与人类中的研究结果表明，生理状态异常的个体确实身体状况更差。此外，我们的方法似乎对用于评估身体状况的生物标志物组合并无特殊敏感性。因此，该方法可轻松应用于现有的生态数据集。5. 我们的方法提供了一种通用且高效的身体状况测量手段，有助于解决在处理多项生理指标与状况评估指标间复杂交互作用与相互依赖关系时遇到的困惑。该方法可直接应用于诸多研究主题，例如环境质量对身体状况的影响、健康结局风险、适应性表型可塑性的机制，以及衰老等长期过程背后的作用机制。