Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA.
Integr Comp Biol. 2020 Jul 1;60(1):113-125. doi: 10.1093/icb/icaa009.
Quantifying how whole organisms respond to challenges in the external and internal environment ("stressors") is difficult. To date, physiological ecologists have mostly used measures of glucocorticoids (GCs) to assess the impact of stressors on animals. This is of course too simplistic as Hans Seyle himself characterized the response of organisms to "noxious stimuli" using multiple physiological responses. Possible solutions include increasing the number of biomarkers to more accurately characterize the "stress state" of animal or just measuring different biomarkers to more accurately characterize the degree of acute or chronic stressors an animal is experiencing. We focus on the latter and discuss how heart rate (HR) and heart rate variability (HRV) may be better predictors of the degree of activation of the sympathetic-adrenal-medullary system and complement or even replace measures of GCs as indicators of animal health, welfare, fitness, or their level of exposure to stressors. The miniaturization of biological sensor technology ("bio-sensors" or "bio-loggers") presents an opportunity to reassess measures of stress state and develop new approaches. We describe some modern approaches to gathering these HR and HRV data in free-living animals with the aim that heart dynamics will be more integrated with measures of GCs as bio-markers of stress state and predictors of fitness in free-living animals.
量化整个生物体如何对外界和内部环境中的挑战（“应激源”）做出反应是很困难的。迄今为止，生理生态学家主要使用糖皮质激素 (GCs) 的测量值来评估应激源对动物的影响。这当然过于简单化了，因为汉斯·塞利 (Hans Seyle) 本人用多种生理反应来描述生物体对“有害刺激”的反应。可能的解决方案包括增加生物标志物的数量，以更准确地描述动物的“应激状态”，或者只是测量不同的生物标志物，以更准确地描述动物所经历的急性或慢性应激源的程度。我们专注于后者，并讨论心率 (HR) 和心率变异性 (HRV) 如何更好地预测交感肾上腺髓质系统的激活程度，并作为动物健康、福利、适应度或其暴露于应激源程度的指标，补充甚至替代 GCs 的测量值。生物传感器技术的微型化（“生物传感器”或“生物记录器”）提供了重新评估应激状态测量和开发新方法的机会。我们描述了一些现代方法来收集这些自由生活动物的 HR 和 HRV 数据，目的是使心脏动力学与 GCs 等生物标志物更紧密地结合，作为自由生活动物应激状态和适应度的预测指标。
