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Animals have evolved with the natural patterns of light and darkness that define day and night. Thus, circadian rhythms in hormonal systems orchestrate rest and activity patterns and allow animals to maximize fitness1,2,3. For instance, the circadian rhythm in glucocorticoid hormones, with a peak at the onset of daily activity, primes vertebrates to behave appropriately across the 24-h period via effects on glucose metabolism and responsiveness to environmental stressors4. Similarly, the pineal hormone melatonin, which is released in response to darkness, is integrally involved in governing patterns of circadian rhythmicity and also has antioxidant properties5,6. Entrainment of many aspects of circadian rhythmicity, such as melatonin release, is affected by the photoreception of levels of light in the environment. Thus, the introduction of artificial light into the environment to support human activity, recreation, and infrastructure has the potential to have wide-reaching effects on the behavior, physiology and fitness of free-ranging animals7,8. Indeed, diverse effects of exposure to artificial light at night (ALAN) have been documented9,10, and ALAN has been highlighted as a priority for global change research in the 21st century10.
Measuring the effects of ALAN on free-ranging animals poses non-trivial challenges for a number of reasons. First, mobile animals moving through the environment constantly experience different levels of light. Thus, how does one quantify the level of light that individual animals are exposed to? Even if levels of light on the territory of the animal can be quantified, the animal may employ avoidance strategies that affect patterns of exposure, thus demanding simultaneous tracking of animal location and light levels. Indeed, in most field studies, the mean and variation in light exposure levels are unknown11. Second, exposure to ALAN is often correlated with exposure to other anthropogenic disturbance factors, such as noise pollution, chemical exposure, and habitat degradation. For instance, animals occupying habitats along the margins of roadways will be exposed to light from street lamps, noise from vehicular traffic, and air pollution from vehicular emissions. How then does one effectively isolate the effects of ALAN from the effects of confounding variables? Rigorous field experiments that enable good measurements of both light exposure levels and response variables are essential to evaluating the severity of the biological effects of ALAN, and to developing effective mitigation strategies11.
This article describes an experimental approach that, although not without its limitations (see discussion section), helps assuage, if not eliminate the difficulties identified above. The approach entails experimentally manipulating ALAN levels inside the nest boxes of a free-living, diurnal bird species, the great tit (Parus major), using a system of light-emitting diode (LED) lights and an infrared (IR) camera installed within nest boxes. The setup enables simultaneous acquisition of video recordings, including audio, which allows researchers to assess effects on behaviors and vocalizations. Great tits utilize nest boxes for breeding, and sleep in the nest boxes between November and March. Females also sleep inside the nest boxes during the breeding season12. The system has also been used to a lesser extent to study effects of ALAN on blue tits (Cyanistes caeruleus). The first difficulty, involving knowing light levels encountered by the animal, is mitigated in that, given that an individual is willing to enter the nest box (or is already in the nest box in the case of immobile nestlings), light levels can be precisely determined by the researcher. The second difficulty, involving correlations to confounding variables, can be controlled by using nest boxes in similar environments, and/or measuring the levels of confounding variables near nest boxes. In addition, in cavity-nesting birds, adopting an experimental approach is powerful because nest boxes or natural cavities can shield nestlings and adults from ALAN13, which may explain why some correlative studies find little effect of ALAN (or anthropogenic noise)14, whereas experimental studies more often find clear effects (see below). Moreover, a repeated measures experimental design can be adopted in which individuals serve as their own control, which further increases statistical power, and the probability of detecting meaningful biological effects. The sections below: (1) explain the details of the design and implementation of the system, (2) summarize the important results that have been thus far derived using the system, and (3) propose future research directions that could be pursued, both in tits and other animals.