Social foraging is very common in the animal kingdom. Numerous studies have documented collective foraging in various species and many reported the attraction of various species to foraging conspecifics. It is nonetheless difficult to quantify the benefits and costs of collective foraging, especially in the wild. We examined the benefits and costs of social foraging using on- board microphones mounted on freely foraging Molossus nigricans bats. This allowed us to quantify the bats’ attacks on prey and to assess their success as a function of conspecific density. We found that the bats spent most of their time foraging at low conspecific densities, during which their attacks were most successful in terms of prey items captured per time unit. Notably, their capture rate dropped when conspecific density became either too high or too low. Our findings thus demonstrate a clear social foraging trade- off in which the presence of a few conspecifics probably improves foraging success, whereas the presence of too many impairs it.

Harten et.al. use GPS tracking and captive manipulations to demonstrate that wild Egyptian fruit bats map the temporal availability of food sources and the time since their last visit to a tree, then plan their foraging accordingly as well as according to their nutritional requirements.

The rate of sensory update is one of the most important parameters of any sensory system. The acquisition rate of most sensory systems is fixed and has been optimized by evolution to the needs of the animal. Echolocating bats have the ability to adjust their sensory update rate which is determined by the intervals between emissions- the inter-pulse intervals (IPI). The IPI is routinely adjusted, but the exact factors driving its regulation are unknown. We use onboard audio recordings to determine how four species of echolocating bats with different foraging strategies regulate their sensory update rate during commute flights. We reveal strong correlations between the IPI and various echolocation and movement parameters. Specifically, the update rate increases when the signals’ peak-energy frequency and intensity increases while the update rate decreases when flight speed and altitude increases. We suggest that bats control their information update rate according to the behavioral mode they are engaged in, while always maintaining sensory continuity. Specifically, we suggest that bats apply two modes of attention during commute flights. Our data moreover suggests that bats emit echolocation signals at accurate intervals without the need for external feedback.

In this study, we demonstrate how urban-dwelling bats can be used to reconstruct Urban Heat Islands (UHI). We term this approach biologically-assisted sampling (BAS). We used Egyptian fruit bats to map the spatial air temperature (Tair) profile. To demonstrate the feasibility of using biologically-assisted sampled data set, we run mixed effects and Geographically Weighted Regression (GWR) models to estimate the impact of urban environment on Tair distribution. Our results suggest that vegetation is a very important mitigating factor in Tair. In the winter, we found an average Tair difference of 2–5 ◦C between densely urban and nearby vegetative/open areas. A distinct UHI spot was identified in the winter, centered on the Ayalon highway. These differences were lower during the summer night, probably due to a pronounced cooling sea breeze effect along the coastline. Our preliminary results also indicate that BAS sampling provide a 3D view of the UHI phenomenon: the change in Tair above the dense urban area was smaller than above the vegetative area. Since the differences in Tair between densely urban and open/green areas are the largest during the night hours, bats can serve as efficient agents to monitor UHI effects, despite the method limitations.

The study of inter-sensory integration has focused largely on how different sensory modalities are weighted and combined in perception [1–3]. However, the extent to which information acquired through one sensory modality is modulated by another is yet unknown. We studied this problem in the Egyptian fruit bat (Rousettus aegyptiacus), an animal equipped with two modalities supporting high resolution distal sensing: biosonar and vision [4,5].

Biologging devices are deployed on animals to collect ultra-fine-scale movement data that reveal subsecond patterns in locomotion or long-term patterns in motion and space use. Often these two data types, although complementary, are rarely collected within the same study, given the limiting factors of memory space, power requirements and the need to retrieve stored data from animals. Biologging requires a revolutionary advancement in data networking to overcome these restrictions that constrain big data collection; for the continuous recording and remote download of fine-scale movement and environmental data, from long-term deployments and multiple individuals.

Here, we adopt a strategy from the Internet of Things and develop the use of Wi-Fi as a solution for big data biologging. Our ‘WildFi’ tag uses pre-existing, or easy-to-set-up, infrastructure in smartphones and Wi-Fi gateways. We demonstrate the power of memory management and an embedded modular software architecture for functionality, including collective data retrieval at multiple gateways.

We find that Wi-Fi, together with smart embedded software, increases the retrieval efficiency of biologging data by orders of magnitude compared to other available systems: with a transmission speed of 230 kByte/s and range of ≤200 m that is 11 times faster than Bluetooth low energy and >3000 times faster than LoRaWAN. Case studies on a domestic dog (Canis lupus familiaris), aviary-housed cockatiels (Nymphicus hollandicus) and free-roaming pangolins (Smutsia temminckii) demonstrate the functionality of the WildFi tag for remote and robust autonomous Wi-Fi data transmission under a range of conditions.

Modularity in software and hardware allows for project-specific tailoring beyond reconfiguring sampling parameters of a biologger, which we encourage with open-source sharing of our architecture design. Enhanced communication between animal-attached devices, Wi-Fi infrastructure and smartphones, alongside smart and collaborative data retrieval, eases restrictions for big data collection in animal ecology.

Bats are remarkable in their dynamic control over body temperature, showing both hypothermia with torpor and hyperthermia during flight. Despite considerable research in understanding bats’ thermoregulation mechanisms, knowledge on the relationship between flight and body temperature in bats remains limited, possibly due to technological restraints. We used onboard dataloggers including a temperature sensor and an inertial sensor (accelerometers) and continuously recorded the flight behavior and skin temperature (Tsk) subcutaneously of a perch-hunting bat, Hipposideros armiger, both in the laboratory and in the field……..

Goldshtein et al. document bats’ navigation ontogeny. Results suggest that mothers facilitate learning of navigation by repeatedly placing their pups on specific trees, which the pups later fly to on their first independent flights. Pups seem to learn navigation routes while being transported upside down by their mothers.

Urbanization is one of the most influential processes on our globe, putting a great number of species under threat. Some species learn to cope with urbanization, and a few even benefit from it, but we are only starting to understand how they do so. In this study, we GPS tracked Egyptian fruit bats from urban and rural populations to compare their movement and foraging in urban and rural environments. Because fruit trees are distributed differently in these two environments, with a higher diversity in urban environments, we hypothesized that foraging strategies will differ too.

Along with its many advantages, social roosting imposes a major risk of pathogen transmission. How social animals reduce this risk is poorly documented. We used lipopolysaccharide challenge to imitate bacterial infection in both a captive and a free-living colony of an extremely social, long-lived mammal-the Egyptian fruit bat. We monitored behavioral and physiological responses using an arsenal of methods, including onboard GPS to track foraging, acceleration sensors to monitor movement, infrared video to record social behavior, and blood samples to measure immune markers. Sick-like (immune-challenged) bats exhibited an increased immune response, as well as classic illness symptoms, including fever, weight loss, anorexia, and lethargy. Notably, the bats also exhibited behaviors that would reduce pathogen transfer. They perched alone and appeared to voluntarily isolate themselves from the group by leaving the social cluster, which is extremely atypical for this species. The sick-like individuals in the open colony ceased foraging outdoors for at least two nights, thus reducing transmission to neighboring colonies. Together, these sickness behaviors demonstrate a strong, integrative immune response that promotes recovery of infected individuals while reducing pathogen transmission inside and outside the roost, including spillover events to other species, such as humans.

Sensory systems acquire both external and internal information to guide behavior. Adjustments based on external input are much better documented and understood than internal-based sensory adaptations. When external input is not available, idiothetic—internal—cues become crucial for guiding behavior. Here, we take advantage of the rapid sensory adjustments exhibited by bats in order to study how animals rely on internal cues in the absence of external input. Constant frequency echolocating bats are renowned for their Doppler shift compensation response used to adjust their emission frequency in order to optimize sensing. Previous studies documented the importance of external echoes for this response.

Multiple methods have been developed to infer behavioral states from animal movement data, but rarely has their accuracy been assessed from independent evidence, especially for location data sampled with high temporal resolution. Here we evaluate the performance of behavioral segmentation methods using acoustic recordings that monitor prey capture attempts.

We recorded GPS locations and ultrasonic audio during the foraging trips of 11 Mexican fish-eating bats, Myotis vivesi, using miniature bio-loggers. We then applied…..

Foraging behavior is influenced by the distribution of prey in time and space and the presence of conspecifics. Echolocating bats, which advertise their behavior while vocalizing, provide a unique opportunity for understanding how an organism interacts with conspecifics and the environment to find food. Here I use GPS tracking combined with on-board recording to investigate the foraging movements of lactating Mexican fish-eating bats, Myotis vivesi, in the Gulf of California, Mexico, over a 5-year period. In Chapter 1, I assessed five alternative methods for behavioral state segmentation of GPS tracked foraging paths using on-board audio for validation. While most methods perform well, hidden-Markov model segmentation showed the highest accuracy at predicting foraging movement. In Chapter 2, I evaluated habitat selection across multiple scales for fish-eating bats foraging in the Midriff Islands Region in the …

Observations of animals feeding in aggregations are often interpreted as events of social foraging, but it can be difficult to determine whether the animals arrived at the foraging sites after collective search [1–4] or whether they found the sites by following a leader [5, 6] or even independently, aggregating as an artifact of food availability [7, 8]. Distinguishing between these explanations is important, because functionally, they might have very different consequences. In the first case, the animals could benefit from the presence of conspecifics, whereas in the second and third, they often suffer from increased competition [3, 9–13]. Using novel miniature sensors, we recorded GPS tracks and audio of five species of bats, monitoring their movement and interactions with conspecifics, which could be inferred from the audio recordings. We examined the hypothesis that food distribution plays a key role in determining social foraging patterns [14–16]. Specifically, this hypothesis predicts that searching for an ephemeral resource (whose distribution in time or space is hard to predict) is more likely to favor social foraging [10, 13–15] than searching for a predictable resource. The movement and social interactions differed between bats foraging on ephemeral versus predictable resources. Ephemeral species changed foraging sites and showed large temporal variation nightly. They aggregated with conspecifics as was supported by playback experiments and computer simulations. In contrast, predictable species were never observed near conspecifics and showed high spatial fidelity to the same foraging sites over multiple nights. Our results suggest that …

Passive acoustic monitoring (PAM) is an increasingly common method for studying populations of vocally active species. However, the detection of individuals not resident to a site may obfuscate inferences about occurrence and population change. Here, we provide a framework for distinguishing resident from non-resident individuals to estimate territory—rather than site—occupancy in PAM programs by leveraging datasets on vocal behavior and acoustic detections for spotted owls (Strix occidentalis) in the Sierra Nevada, California, USA. Based on acoustic/GPS tags, the extent over which individuals typically vocalized (the “vocal home range”) was small relative to space use, such that the likelihood of double counting resident territory-holders across multiple survey sites was low. However, comparing passive acoustic detections to known resident owl locations revealed that detections occurred at PAM survey sites known to be unoccupied, possibly because of the presence of non-territorial individuals. Strict thresholds that required acoustic detections over multiple survey periods successfully removed all detections of non-resident individuals but increased the probability of not detecting resident individuals. Conversely, relatively liberal thresholds that minimized the probability of missing resident individuals increased the probability of detecting non-residents. Thus, a tradeoff exists between error types, with optimal threshold criteria dependent on conservation objectives. Our study highlights the importance of examining patterns in individual vocal behavior and acoustic detections to minimize inferential errors in PAM. It also provides a generalizable framework that can be tailored according to specific conservation objectives to strengthen inferences from PAM as it becomes standard practice in conservation science.