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ABSTRACT Seasonal changes in sleep/wake cycles and behaviors related to reproduction often co‐occur with seasonal fluctuations in sex hormones. Experimental studies have established that fluctuations in circulating testosterone mediate circadian rhythms. However, most studies are performed under constant lighting conditions and fail to investigate the effects of testosterone on the phenotypic output of circadian rhythms, that is, chronotype (daily activity patterns under light:dark cycles). Here, we experimentally elevated testosterone with implants during short nonbreeding daylengths in male house sparrows (Passer domesticus) to test if observed seasonal changes in chronotype are directly in response to photoperiod or to testosterone. We fitted individuals with accelerometers to track activity across treatment periods. Birds experienced three treatments periods: short day photoperiods before manipulation (SD), followed by testosterone implants while still on short days (SD + T). Implants were then removed. After a decrease in cloacal protuberance size, an indicator of low testosterone levels, birds were then photostimulated on long days (LD). Blood samples were collected at night, when testosterone peaks, to compare testosterone levels to daily onset/offset activity for experimental periods. Our results indicate that experimentally elevated testosterone under short nonbreeding photoperiods significantly advanced daily onset of activity and total daily activity relative to daylength. This suggests that testosterone, independent of photoperiod, is responsible for seasonal shifts in chronotypes and daily activity rhythms. These findings suggest that sex steroid hormone actions regulate timing of daily behaviors, likely coordinating expression of reproductive behaviors to appropriate times of the day. 

Abstract Bio-loggers are widely used for studying the movement and behavior of animals. However, some sensors provide more data than is practical to store given experiment or bio-logger design constraints. One approach for overcoming this limitation is to utilize data collection strategies, such as non-continuous recording or data summarization that may record data more efficiently, but need to be validated for correctness. In this paper we address two fundamental questions—how can researchers determine suitable parameters and behaviors for bio-logger sensors, and how do they validate their choices? We present a methodology that uses software-based simulation of bio-loggers to validate various data collection strategies using recorded data and synchronized, annotated video. The use of simulation allows for fast and repeatable tests, which facilitates the validation of data collection methods as well as the configuration of bio-loggers in preparation for experiments. We demonstrate this methodology using accelerometer loggers for recording the activity of the small songbirdJunco hyemalis hyemalis.