Conor Taff

Wild animals often experience unpredictable challenges that demand rapid and flexible responses. The glucocorticoid mediated stress response is one of the major systems that allows vertebrates to rapidly adjust their physiology and behavior. Given its role in responding to challenges, evolutionary physiologists have focused on the consequences of between-individual and, more recently, within-individual variation in the acute glucocorticoid response. Although sophisticated approaches are available to partition this variation statistically, empirical studies of physiological flexibility are severely limited by the logistical challenges of measuring the same animal multiple times during a single acute response or across multiple instances of acute responses. Empiricists have largely adopted the strategy of standardizing sampling as much as possible to allow for comparison between individuals, but this standardization also makes it very difficult to detect certain types of variation in the functional shape of acute response curves. Data simulation is a powerful approach when empirical data are limited, but has not been adopted to date in studies of physiological flexibility. In this paper, I describe the simcoRt package, which includes functions that can generate realistic acute glucocorticoid response data with user specified characteristics. Simulated animals can be sampled continuously through an acute response and across as many separate responses as desired, while varying key parameters (e.g., the degree of correlation between the speed and scope of a response). Using this simulation, I explore several possible scenarios to highlight areas where simulation might either provide new insight into physiological flexibility directly or aid in designing empirical studies that are better able to test the hypotheses of interest.