Optimal sampling interval for characterisation of the circadian rhythm of body temperature in homeothermic animals using periodogram and cosinor analysis

Abstract

Core body temperature (<i>T</i> _c) is a critical aspect of homeostasis in birds and mammals and is increasingly used as a biomarker of the fitness of an animal to its environment. Periodogram and cosinor analysis can be used to estimate the characteristics of the circadian rhythm of <i>T</i> _c from data obtained on loggers that have limited memory capacity and battery life. The sampling interval can be manipulated to maximise the recording period, but the impact of sampling interval on the output of periodogram or cosinor analysis is unknown. Some basic guidelines are available from signal analysis theory, but those guidelines have never been tested on <i>T</i> _c data. We obtained data at 1-, 5- or 10-min intervals from nine avian or mammalian species, and re-sampled those data to simulate logging at up to 240-min intervals. The period of the rhythm was first analysed using the Lomb-Scargle periodogram, and the mesor, amplitude, acrophase and adjusted coefficient of determination (<i>R</i> ²) from the original and the re-sampled data were obtained using cosinor analysis. Sampling intervals longer than 60 min did not affect the average mesor, amplitude, acrophase or adjusted <i>R</i> ², but did impact the estimation of the period of the rhythm. In most species, the period was not detectable when intervals longer than 120 min were used. In all individual profiles, a 30-min sampling interval modified the values of the mesor and amplitude by less than 0.1°C, and the adjusted <i>R</i> ² by less than 0.1. At a 30-min interval, the acrophase was accurate to within 15 min for all species except mice. The adjusted <i>R</i> ² increased as sampling frequency decreased. In most cases, a 30-min sampling interval provides a reliable estimate of the circadian <i>T</i> _c rhythm using periodogram and cosinor analysis. Our findings will help biologists to select sampling intervals to fit their research goals.