Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging.

Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-the-art for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.

Vampire Bats that Cooperate in the Lab Maintain Their Social Networks in the Wild.

Social bonds, maintained by mutual investments of time and energy, have greatly influenced the evolution of social cognition and cooperation in many species [e.g., 1-8]. However, there are two pitfalls regarding "social bonds" as an explanation for social structure and cooperation [1, 9-11]. First, studies often incorrectly assume that frequent association implies partner fidelity based on mutual social preference, but even seemingly complex nonrandom interaction networks can emerge solely from habitat or spatial structure [12-16]. Second, the false appearance of partner fidelity can result from stable options in the "partner market" [1, 9-11, 17]. For instance, individuals might preferentially groom the same partner, even if the decision depends entirely on the immediate costs and benefits rather than relationship history. Given these issues, a key challenge has been testing the extent to which social structure is driven by the intrinsic relationship history versus the extrinsic physical and social environment. If stable bonds exist, they should persist even if the individuals are moved to a dramatically different physical and social environment. We tested this prediction by tracking social relationships among common vampire bats (Desmodus rotundus) moved from the lab to the wild. We show that allogrooming and food sharing among female vampire bats induced in captivity over 22 months predicted their assortativity and association rates when we subsequently tracked them in the wild with custom-made high-resolution proximity sensors. The persistence of many relationships across different physical and social environments suggests that social structure is caused by both extrinsic constraints and intrinsic partner fidelity.

Proximity sensors on common noctule bats reveal evidence that mothers guide juveniles to roosts but not food.

Female bats of temperate zones often communally rear their young, which creates ideal conditions for naive juveniles to find or learn about resources via informed adults. However, studying social information transfer in elusive and small-bodied animals in the wild is difficult with traditional tracking techniques. We used a novel 'next-generation' proximity sensor system (BATS) to investigate if and how juvenile bats use social information in acquiring access to two crucial resources: suitable roosts and food patches. By tracking juvenile-adult associations during roost switching and foraging, we found evidence for mother-to-offspring information transfer while switching roosts but not during foraging. Spatial and temporal patterns of encounters suggested that mothers guided juveniles between the juvenile and the target roost. This roost-switching behaviour provides evidence for maternal guidance in bats, a form of maternal care that has long been assumed, but never documented. We did not find evidence that mothers guide the offspring to foraging sites. Foraging bats reported brief infrequent meetings with other tagged bats that were best explained by local enhancement. Our study illustrates how this recent advance in automated biologging provides researchers with new insights into longstanding questions in behavioural biology.

Wireless Sensor Platform for Detection of Vital Parameters of Bats.

In this paper an advanced sensor node for animal tracking is proposed, which includes an accelerometer, an air pressure sensor as well as an electrocardiography sensor. The system is designed for studying the physiology and behavior of bats by inferring activity, wing beat frequency as well as heart rate. This system offers outstanding functionality compared to other tracking nodes and is easily applicable thanks to its noninvasive design. Gluing the sensor to the bat's back keeps the impact on the animal at a minimum and retrieval of the animal to remove the tag is not required since the tag falls off after a few days.

BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking.

In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible.