Abstract
Biological timing (including circadian and interval timing) has mainly focused on rigorously controlled laboratory experiments. There are relatively few studies looking into interval timing behaviors in the wild, which could be understandable due to the complexity of the experimental design but are definitely needed in order to comprehend the adaptive value of such behavior. In this opinion paper we review some of the literature regarding timing observations under field conditions, including reports from birds and mammals, and propose a call-to-action to think about the need of a more naturalistic interpretation of time production and perception, as well as the advantage of designing more ‘natural’ settings in the laboratory.
Several years ago, when talking about biological timing, Dr. Warren Meck mentioned his appreciation for, besides laboratory experiments, different forms of interval timing behavior in nature. This mention inspired us to write this opinion article, with the aim to highlight the benefits of understanding biological timing by evaluating behavioral patterns under natural conditions in the field. Biological timing comprises diverse time-related mechanisms that encompass several orders of magnitude, from microsecond processing to seasonal rhythms (Golombek et al., 2014). While there is a large array of data showing circadian (∼24-h range) and infradian (>24-h range, such as reproductive or hibernation cycles) timing in natural environments (e.g., Agostino et al., 2020; Beale et al., 2013; Berberich et al., 2019; Daan et al., 2011; Florant et al., 2000; Izawa, 2012; Nagano et al., 2019; Tachinardi et al., 2017; Tomotani et al., 2012; Wyse et al., 2018), most interval timing experiments are performed under controlled conditions in the laboratory. This is understandable because of the difficulty of studying short-time behavior outside controlled conditions. However, results from circadian studies indicate that biological timing may differ in laboratory versus field conditions. For example, mice with a functional deletion of the mPer2 gene (Per2Brdm1 mice), known to display circadian abnormal behavior and multiple physiological disturbances in the laboratory, did not have any major negative effects on fitness when tested over two years in the field (Daan et al., 2011). Similar results (i.e., no significant deleterious effects) were observed for chipmunks (Tamias striatus) with lesions in the suprachiasmatic nuclei – the master circadian oscillator in mammals – and subsequently released in their natural habitats (DeCoursey et al., 2000). Moreover, some rodent species show a complete switch from nocturnality in the laboratory to diurnality in the field (reviewed in Hut et al., 2012).
The few studies of interval timing in the field (for exhaustive reviews, see Ng et al., 2020 and Vasconcelos et al., 2017) have focused on natural behaviors such as foraging, escaping predators or communication (e.g., vocalization). Different mechanisms and models for optimal foraging strategies have been proposed (Stephens & Krebs, 2019). For example, optimal foraging for provisioning is achieved by minimizing travel distance and time through selecting the food resources nearest to the nest, and by selecting the most energy-efficient food and strategy, making interval timing of major importance for this behavior. In this sense, foraging time depends on the individual efficiency in searching, accessing or capturing and handling food (Fargallo et al., 2020; Ydenberg, 2007). Foraging is also related to time–place learning (Thorpe & Wilkie, 2006), where animals change their foraging site according to predictable temporal patterns. Furthermore, many aspects of escaping predators depend on interval timing (e.g., evasive moves are unsuccessful if they occur too early or too late; Hills, 2003). Finally, competitive interactions involving reproduction may also rely on interval timing for some species when communication is involved (MacDonald & Meck, 2005).
In particular, birds are among the most studied animals for optimal foraging in natural environments. This is because these small vertebrates have relatively high metabolic rates, requiring elevated quantities of food on a regular basis. A small bird may need to eat its body weight in food per day. These high rates of foraging are coupled with the fact that most birds forage only during daylight hours (Bateson, 2003). For example, it has been observed that various species of finches in the Mohave Desert move to different foraging sites each day and revisit each location according to its replenishing interval (Cody, 1971). A similar behavior has been described in pied wagtails (Motacilla alba; Davies & Houston, 1981). Moreover, Davies (1977) reported a particularly interesting field experiment in which flycatchers (Muscicapa striata) use a rule that involves estimating the average intercapture interval and moving on to a new perch if no food had appeared when they had waited 1.5 times this interval. By using a laboratory analog of this field experiment, Brunner et al. (1992) showed that European starlings waited for a specific proportion of the fixed interval before abandoning the patch. By using a version of the peak procedure that includes omission of reward, these authors evaluated how the patch departure of starlings was affected by the value of the fixed-interval schedule in the patch. They examined six different values of the fixed interval, ranging between 0.8 and 25.6 sec. The giving-in time at which birds stopped attempting to obtain food from a patch increased linearly with the fixed interval, with a slope of 1.49. That is, despite apparently knowing accurately when food should have been delivered, the birds still chose to wait 1.49 times the usual interfood interval before giving in. Birds also displayed the scalar property of interval timing (Gibbon, 1977; Gibbon et al., 1984) in their time estimates (Brunner et al., 1992). A more recent study in hummingbirds in the wild evidenced that animals remember when and where rewards occur and that they update this memory throughout the day (Henderson et al., 2006). The study consisted of the refill of artificial flowers with a sucrose solution at intervals of either 10 or 20 min after the bird emptied it. Free-living hummingbirds revisited the 10-min flowers significantly sooner than they visited 20-min flowers. That is, birds learned that the refill rates differed among the flowers. Hummingbirds were also able to update this learned information across numerous foraging bouts throughout the day. This work demonstrated that free-living animals remember not only the locations of multiple rewards but also when they visited each of those locations.
In some animals, such as birds and rodents, early experiments using motor timing tasks reported that their performance was associated with the production of relatively stereotyped chains of action due to the interaction with the environment (Falk, 1971; Richelle & Lejeune, 1980; Wilson & Keller, 1953). In this sense, it was recently shown that rats improve their timing accuracy when the environment provides cues that animals can incorporate into their motor routines. These physical features of the environment provide signals that facilitate the execution of simple sequences or routines adapted to the temporal challenge faced by the animal (Safaie et al., 2020).
In the range of long-interval timing (i.e., between the seconds-to-minutes range of short-interval timing and the 24-h range of circadian timing; Crystal, 2006) there are several examples of animals adjusting their feeding behavior to predictable changes in the environment. For instance, Daan and Koene (1981) demonstrated that oystercatchers (Haematopus ostralegus) are able to anticipate short (circa 4-h), medium (circa 5-h) and long (circa 6-h) tidal rhythms to match foraging bouts with the time mussel beds become exposed. Further evidence is the work of Rijnsdorp et al. (1981), who evaluated flight-hunting behavior in free-living kestrels (Falco tinnunculus). These birds increased their visits to a previously visited field around the time prey (in this case, a mouse) was regularly released by the experimenters. What is more, Clayton and Dickinson (1998) added more evidence to the knowledge that food-storing birds remember the spatial location and contents of their caches. Authors proved that scrub jays (Aphelocoma coerulescens) remembered three types of information: (1) what items (peanuts and worms) were cached: (2) where each type of item was stored (left or right sides); and (3) when (4 h or 124 h ago) the worms were cached. This study with scrub jays demonstrated memory of where and when (similar to the conclusions of Henderson et al., 2006) in a lab setting, and their protocol blends the information of what would happen in nature to their lab experiment.
Birds, in particular, are the most vocal group of animals, other than humans and a few other primates. Bird calls serve diverse functions, such as reproduction and territoriality, signaling about food, maintaining social cohesion, etc. Our last collaboration with Dr. Warren Meck in 2019 evaluated daily and seasonal fluctuation in Tawny Owl (Strix aluco) vocalization timing under a natural environment. This work was the result of Dr. Guy Peryer’s (University of East Anglia, UK) inspiration and recollection of recordings from Tawny Owl that had consistent patterns in calls in the region of 15–30-s intervals. We reported that male Tawny Owls present a periodic vocalization pattern in the seconds-to-minutes range that is subject to both daily (early vs late night) and seasonal (spring vs summer) rhythmicity. For example, the time interval between each two-call repetition event was around 18 s in the early night and around 26 s in the late night. These data indicate that time of day regulates the timing between calls (Agostino et al., 2020). These diurnal and seasonal changes in vocalization had been previously described for several vocal species, including songbirds (Derégnaucourt et al., 2012; Jansen et al., 2005; Wang et al., 2012); however, this was the first description of such changes in non-oscine birds.
In the case of livestock animals, such as ruminants, the study of time spent foraging in their own habitats may have important economic advantages. Indeed, evaluation of grazing behavior in natural grasslands is regarded as an important issue when establishing management goals because the behavior of these animals on pastures provides clues that help to take suitable decisions. Thus, monitoring time spent grazing and ruminating are key variables used as indicators of management efficiency and welfare in several animals such as beef cattle. Ruminants commonly have grazing times between 450 and 600 min/day in temperate pastures, with times that may exceed 760 min/day on subtropical and tropical pastures (Hodgson, 1982). Moreover, in temperate climate conditions, grazing activity occurs predominantly during daylight hours (Linnane et al., 2001) and major grazing events occur near sunrise and sunset, with the latter having greater intensity and longer duration (Gibb et al., 1998). The influence of day-length may change the foraging patterns of animals. In this sense, having different grazing peaks during different seasons demonstrates the ability of animals to adapt their digestive activity to variations in daylight, reserving most rumination and rest activities for periods of darkness. In subtropical and tropical climates, animals can conduct a significant portion of grazing during non-daylight hours together with rumination and resting. This information is useful, for example, to reduce the use of feeding supplements. When the use of supplementary sources of feeding is necessary, offering food between grazing peaks allows for a reduction in supplement administration and also for feeding optimization (Jochims et al., 2020).
Finally, studies in humans have linked visual foraging time with new insights into the mechanism of visual attention in multiple-target search. This adaptation of optimal foraging theory (Stephens & Krebs, 2019) provides important knowledge into searching behavior in the real world, since multiple-target search is characteristic of many daily tasks, such as separating the quarters out of a pile of coins or searching for abnormalities in an X-ray. While classic single-target search in the laboratory occurs over the course of a few hundred to a few thousand milliseconds, real-world multiple-target search involves prolonged search tasks with a higher level of knowledge and decision-making, with a duration that may last seconds to minutes (Ehinger & Wolfe, 2017). Thus, this kind of search presents cognitive challenges, as subjects must decide when to stop looking for additional targets, which several times results in high miss rates (Cain et al., 2012). In a laboratory experiment with ‘naturalistic’ settings, Ehinger and Wolfe (2016) described that, in the case of complex tasks like the search for objects in natural scenes, subjects follow a rate-optimizing strategy and use both their prior knowledge and search history in the image to decide when to quit searching. Consistent with optimal foraging theory, observers generally move to a new display when the instantaneous collection rate falls below the average rate for the environment.
Therefore, organisms have the capacity to adjust their behavior to temporal regularities in the environment. Even more, the interaction among these different temporal systems – such as the circadian influence in ultradian or infradian rhythms (Laje et al., 2018) – in natural settings may present evolutionary advantages. Temporal mechanisms in nature are certainly interdependent; in this sense, laboratory settings that do not take into account such interactions might fall short when trying to understand the adaptive value of multifrequency timing processes.
In conclusion, although studies of interval timing in nature are scarce, they are important not only to evaluate behaviors that complement and validate laboratory results but also to inspire future research conducted in the laboratory. This bidirectional dialogue between laboratory and field studies is essential to increase the comprehensive coverage of biological timing. From this perspective, it is important to think how we can achieve laboratory experiments with high ecological validity. Some examples include the use of more ecologically relevant stimuli, tasks that would represent real-world problems, or response requirements within the behavioral repertoire of the experimental subjects. With developing technologies, there are virtual-reality systems that can be used even with mice to approximate the real-world scenarios. On the other hand, there are wearable technologies such as eye trackers and actimeters which would allow researchers to move their research outside of the laboratory. Thus, evaluating timing behavior in the field may provide very useful insights into its role in the generation of adaptive behavior, while the study of interval timing under laboratory conditions is essential to investigate the mechanisms underlying the internal clock. The importance of this kind of studies in more naturalistic settings has been proved for evaluating other temporal systems, such as the importance of circadian clocks on behavioral timing. Combining both approaches may yield a more complete understanding of timing behavior. Field observations can and should inspire laboratory experiments which, in turn, could be validated and complemented with additional ecological research. Moreover, devising specific natural experiments to understand interval timing in the field might provide a unique framework for the interdisciplinary collaboration between ecologists and psychologists, which we are sure Dr. Warren Meck would have profoundly appreciated.
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