Using bat flight trajectories recorded using GPS loggers, we classified intensive and extensive modes during nightly movement and quantified spatio-temporal features of these two navigational modes in R. f. nippon. Based on the foraging behavior of this species (fly-catcher style), these two modes are supposed to correspond to foraging and commuting, respectively. Strictly speaking, the intensive mode might include a resting mode. However, it is difficult to extract the resting mode from the positional data of the foraging bats even by using high-resolution GPS bio-logging due to their movement characteristics during perch-hunting (The details are presented below). As a result, we found that R. f. nippon alternated foraging within a time frame of a few minutes, which is quite similar to the Area Restricted Search (ARS) behavior observed in the movement patterns of animals such as some mammals, birds, and insects [27–29]. These characteristics of foraging and commuting behavior should be investigated considering sex differences in future studies. Although the sample size in the present study was small, we are confident that it will provide very valuable knowledge in order to advance the understanding of foraging ecology of this bat species in the wild.
Habitat use
In a previous study conducted in the UK using radio telemetry, R. ferrumequinum preferred to fly over pastures and in forests [20, 30], whereas the bats in western Europe preferred residential areas and meadow orchards [21]. On the other hand, we found that the main habitat of our bats used in both of the foraging and commuting modes were forested areas, and the bats seemed to prefer flying within forest (see Fig. 3). Several factors may cause this habitat usage for the bats in our study area. First, forests are suitable for the flycatcher feeding style due to the abundance of tree branches. Second, Rhinolophus species generally have lower wing loading, which results in slow flight and good maneuverability [31]; flying within forests allows bats to avoid harsh weather conditions. Third, forests are a major source of flying insects, which are consumed by insectivorous bats. The landscape in this study was largely covered by forests than those in previous studies, and pastures, meadows, orchards (categorized into grassland in this study) and residential areas were rarely used by the bats. We need to consider that, depending on the interaction with the landscape, this bat species has such various habitat preferences.
In the forest, the bats often commuted along a forest road (Fig. 4), which was wide enough for cars to pass on one side (Additional file 1). Some previous studies using direct visual observation or infrared camera recordings also demonstrated that bats fly along fixed routes, so-called flyways, when commuting to foraging sites [32–34], such a route-following behavior is one of the various large-scale navigation strategies of bats [35]. Furthremore, the ultrasound detection range of bats is shorter than the ranges of visual sensory systems employed by other animals such as birds. The continuous echoes from the ground and from the left/right tree lines may be used as clues to help create a local space map for echolocating bats.
Case study
We recorded two cases of unrepeated commuting and foraging (bats A1 and B). For bat A1, the time of foraging mode during one trip was relatively short and flight speed was clearly higher compared to those of other trips, even by the same individual (see Table 1). Note that, bat A1 might have flown at a higher ground speed than the others due to the wind effect: bat A1 encountered approximately 2 m/s wind from the south, bat A2 1 m/s wind from the west and bats C, D, and E 3–4 m/s wind from the north (Japan Meteorological Agency, www.data.jma.go.jp). Compared to other trajectories, it seems that bat A1 flew for purposes other than foraging, i.e., social behavior. Previous studies have reported that many insectivorous bat species, such as Myotis and Plecotus species, travel considerable distances and swarm at underground sites in late summer and autumn in temperate regions [36–38] for mating [39, 40] and/or to assess potential hibernation sites. Although there is no evidence of swarming behavior by Rhinolophus species so far, it is possible that bat A1 has traveled a long distance because of an unknown social behavior during the mating season.
In contrast, bat B stayed continuously at a single site near the roost for over 4 h early in the night (Fig. 1C) (note that we visited this site and found that this was an area next to a pond, with a relatively low tree density). The positions of bat B had a Gaussian distribution in both the north-south and east-west directions (Additional file 2), with a greater variation along the north-south axis compared to the variation from our error-measurement when the logger was placed in a single location within the forest (Additional file 3, see Methods for details). This result suggests that these data were not the result of GPS logging error but rather a result of bat movements within the stay site near their roost. Note that, the bat’s position located discretely by GPS during the foraging mode should not appear to move because the fly-catching greater horseshoe bats fly back to their perching positions before attacking their prey [15]. Therefore, it is thought to be difficult to discriminate foraging or resting from the foraging-mode trajectory data. In the case of bat B, the stay period was enormously longer than the other stays identified in this study. This bat might repeatedly change the hunting perches in the nearby area in the long-time foraging.
Ethical considerations
As bio-logging studies of wild echolocating bats have recently flourished, data quality is likely to be prioritized under a trade-off between logger size and battery life, resulting in the use of data logger weighted more than 10% of the body mass [41, 42]. In this study, we limited the logger weight to be relatively small, i.e., less than 10% of the bat’s body mass, although the logger weight is recommended to be less than 3–5% of the body mass for the flying animals such as birds [43] and bats [44]. A previous study showed that no significant differences were observed between the behavior of echolocating bats (M. myotis and M. vivesi) carrying loggers with 15% of their body weight and non-tagged individuals [13]. The results of the present study showed that bats flew long distances at almost the same speed as reported by previous studies using radio telemetry [45, 46], suggesting that the influence of the data logger weight on bat flight performance was negligible. Nevertheless, the data logger needs to be smaller in the future in order to minimize the effect of the extra loading.
We also should consider how the stress caused by handling and logger attachment affects the bat’s movement, as it might behave or move differently than usual and/or might lose body weight. The results showed that the time when the tagged bats emerged from their roost in the present study was almost the same as in a previous study [15]. In addition, the bodyweight of the attached bats when recapturing after a couple of days did not obviously decrease compared to the first capture (see Methods for details), which is consist of the range of the bodyweight fluctuation observed in this bat species on a daily basis among the reared individuals in our laboratory. These observations suggest that the extra loading due to the logger had little effect on the habitat use of the horseshoe bats. Furthermore, we recaptured a female that was investigated in the previous year during its pregnancy and we could not find any damages. In the present investigation, we caught and attached loggers to a total of 24 bats. We only recaptured 8 bats (33% recapture rate) and succeeded in recovering the data from 5 individuals. In previous studies, the recapture rate of the greater horseshoe bats which were tagged with small metal rings (several few milli-meters) was around 40% [15, 47]. Therefore, the low recapture rate in this study is unlikely due to the extra loading from the GPS data logger alone. However, at present, the effect of logger attachment on the recovery rate of individuals as well as local populations has not been quantitatively assessed. Therefore, detailed investigations of the effects of logger attachment on the bats’ behavior and health are needed.