Automated proximity sensing in small vertebrates: design of miniaturized sensor nodes and first field tests in bats

A Wireless Wearable Ecosystem for Social Network Analysis in Free-living Animals

Studying animal social systems requires understanding variations in contact and interaction, influenced by factors like environmental conditions, resource availability, and predation risk. Traditional observational methods have limitations, but advancements in sensor technologies and data analytics provide new opportunities. We developed a wireless wearable sensor system, "Juxta," with features such as modular battery packs and a smartphone app for data collection. A pilot study on free-living prairie voles (Microtus ochrogaster), a species with complex social behavior, demonstrated Juxta's potential for studying social networks and behavior. We propose a framework for merging temporal, spatial, and event-driven data, which can help explore complex social dynamics across species and environments.

A Wireless Wearable Ecosystem for Social Network Analysis in Free-living Animals

Understanding the dynamics of animal social systems requires studying variation in contact and interaction, which is influenced by environmental conditions, resource availability, and predation risk, among other factors. Traditional (direct) observational methods have limitations, but advancements in sensor technologies and data analytics provide unprecedented opportunities to study these complex systems in naturalistic environments. Proximity logging and tracking devices, capturing movement, temperature, and social interactions, offer non-invasive means to quantify behavior and develop empirical models of animal social networks. However, challenges remain in integrating different data types, incorporating more sensor modalities, and addressing logistical constraints. To address these gaps, we developed a wireless wearable sensor system with novel features (called "Juxta"), including modular battery packs, memory management for combining data types, reconfigurable deployment modes, and a smartphone app for data collection. We present data from a pilot study on prairie voles ( Microtus ochrogaster ), which is a small mammal species that exhibits relatively complex social behavior. We demonstrate the potential for Juxta to increase our understanding of the social networks and behavior of free-living animals. Additionally, we propose a framework to guide future research in merging temporal, spatial, and event-driven data. By leveraging wireless technology, battery efficiency, and smart sensing modalities, our wearable ecosystem offers a scalable solution for real-time, high-resolution data capture and analysis in animal social network studies, opening new avenues for exploring complex social dynamics across species and environments.

An implantable neurophysiology platform: Broadening research capabilities in free-living and non-traditional animals

Animal-borne sensors that can record and transmit data (“biologgers”) are becoming smaller and more capable at a rapid pace. Biologgers have provided enormous insight into the covert lives of many free-ranging animals by characterizing behavioral motifs, estimating energy expenditure, and tracking movement over vast distances, thereby serving both scientific and conservational endpoints. However, given that biologgers are usually attached externally, access to the brain and neurophysiological data has been largely unexplored outside of the laboratory, limiting our understanding of how the brain adapts to, interacts with, or addresses challenges of the natural world. For example, there are only a handful of studies in free-living animals examining the role of sleep, resulting in a wake-centric view of behavior despite the fact that sleep often encompasses a large portion of an animal’s day and plays a vital role in maintaining homeostasis. The growing need to understand sleep from a mechanistic viewpoint and probe its function led us to design an implantable neurophysiology platform that can record brain activity and inertial data, while utilizing a wireless link to enable a suite of forward-looking capabilities. Here, we describe our design approach and demonstrate our device’s capability in a standard laboratory rat as well as a captive fox squirrel. We also discuss the methodological and ethical implications of deploying this new class of device “into the wild” to fill outstanding knowledge gaps.

Social foraging in vampire bats is predicted by long-term cooperative relationships

Stable social bonds in group-living animals can provide greater access to food. A striking example is that female vampire bats often regurgitate blood to socially bonded kin and nonkin that failed in their nightly hunt. Food-sharing relationships form via preferred associations and social grooming within roosts. However, it remains unclear whether these cooperative relationships extend beyond the roost. To evaluate if long-term cooperative relationships in vampire bats play a role in foraging, we tested if foraging encounters measured by proximity sensors could be explained by wild roosting proximity, kinship, or rates of co-feeding, social grooming, and food sharing during 21 months in captivity. We assessed evidence for 6 hypothetical scenarios of social foraging, ranging from individual to collective hunting. We found that closely bonded female vampire bats departed their roost separately, but often reunited far outside the roost. Repeating foraging encounters were predicted by within-roost association and histories of cooperation in captivity, even when accounting for kinship. Foraging bats demonstrated both affiliative and competitive interactions with different social calls linked to each interaction type. We suggest that social foraging could have implications for social evolution if "local" within-roost cooperation and "global" outside-roost competition enhances fitness interdependence between frequent roostmates.

Animal board invited review: OneARK: Strengthening the links between animal production science and animal ecology

Wild and farmed animals are key elements of natural and managed ecosystems that deliver functions such as pollination, pest control and nutrient cycling within the broader roles they play in contributing to biodiversity and to every category of ecosystem services. They are subjected to global changes with a profound impact on the natural range and viability of animal species, the emergence and spatial distribution of pathogens, land use, ecosystem services and farming sustainability. We urgently need to improve our understanding of how animal populations can respond adaptively and therefore sustainably to these new selective pressures. In this context, we explored the common points between animal production science and animal ecology to identify promising avenues of synergy between communities through the transfer of concepts and/or methodologies, focusing on seven concepts that link both disciplines. Animal adaptability, animal diversity (both within and between species), selection, animal management, animal monitoring, agroecology and viability risks were identified as key concepts that should serve the cross-fertilization of both fields to improve ecosystem resilience and farming sustainability. The need for breaking down interdisciplinary barriers is illustrated by two representative examples: i) the circulation and reassortment of pathogens between wild and domestic animals and ii) the role of animals in nutrient cycles, i.e. recycling nitrogen, phosphorus and carbon through, for example, contribution to soil fertility and carbon sequestration. Our synthesis identifies the need for knowledge integration techniques supported by programmes and policy tools that reverse the fragmentation of animal research toward a unification into a single Animal Research Kinship, OneARK, which sets new objectives for future science policy. At the interface of animal ecology and animal production science, our article promotes an effective application of the agroecology concept to animals and the use of functional diversity to increase resilience in both wild and farmed systems. It also promotes the use of novel monitoring technologies to quantify animal welfare and factors affecting fitness. These measures are needed to evaluate viability risk, predict and potentially increase animal adaptability and improve the management of wild and farmed systems, thereby responding to an increasing demand of society for the development of a sustainable management of systems.

Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data

In the 4.5 decades since Altmann (1974) published her seminal paper on the methods for the observational study of behaviour, automated detection and analysis of social interaction networks have fundamentally transformed the ways that ecologists study social behaviour. Methodological developments for collecting data remotely on social behaviour involve indirect inference of associations, direct recordings of interactions and machine vision. These recent technological advances are improving the scale and resolution with which we can dissect interactions among animals. They are also revealing new intricacies of animal social interactions at spatial and temporal resolutions as well as in ecological contexts that have been hidden from humans, making the unwatchable seeable. We first outline how these technological applications are permitting researchers to collect exquisitely detailed information with little observer bias. We further recognize new emerging challenges from these new reality-mining approaches. While technological advances in automating data collection and its analysis are moving at an unprecedented rate, we urge ecologists to thoughtfully combine these new tools with classic behavioural and ecological monitoring methods to place our understanding of animal social networks within fundamental biological contexts.

Social structure and relatedness in the fringe-lipped bat (Trachops cirrhosus)

General insights into the causes and effects of social structure can be gained from comparative analyses across socially and ecologically diverse taxa, such as bats, but long-term data are lacking for most species. In the neotropical fringe-lipped bat, Trachops cirrhosus, social transmission of foraging behaviour is clearly demonstrated in captivity, yet its social structure in the wild remains unclear. Here, we used microsatellite-based estimates of relatedness and records of 157 individually marked adults from 106 roost captures over 6 years, to infer whether male and female T. cirrhosus have preferred co-roosting associations and whether such associations were influenced by relatedness. Using a null model that controlled for year and roosting location, we found that both male and female T. cirrhosus have preferred roosting partners, but that only females demonstrate kin-biased association. Most roosting groups (67%) contained multiple females with one or two reproductive males. Relatedness patterns and recapture records corroborate genetic evidence for female philopatry and male dispersal. Our study adds to growing evidence that many bats demonstrate preferred roosting associations, which has the potential to influence social information transfer.

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.

The role of past experience in development of feeding behavior in common vampire bats

The life history strategy of common vampire bats (Desmodus rotundus) suggests that learning might play a role in development of their foraging skills. We took advantage of 12 captive births in a study colony of vampire bats to test the role of past experience in two aspects of feeding. First, we compared preferences for blood temperature in 32 wild-born vampire bats versus 11 captive-born vampire bats that had only previously fed on blood of ambient temperature or colder. We found no evidence for a preference in either group for blood presented at 4 °C versus 37 °C. Second, we tested whether captive-born vampire bats with no previous experience of feeding on live animals could successfully feed on a live chicken. Five of 12 naïve captive-born bats were able to bite the chicken and draw blood, but only one bat gained more than 5% of body mass. We were unable to reasonably compare their feeding performance with that of wild-born bats because only two of three wild-born, short-term captive bats fed on the chicken and none of the seven wild-born, long-term captive mothers attempted to feed. This unexpected lack of feeding might be due to a previously reported age-dependent neophobia. When six of the captive-born bats were released in the wild, they appeared to feed successfully because they survived for more than three consecutive nights. We suggest further tests that would better clarify the role of learning in the development of foraging in vampire bats.

Advances in population ecology and species interactions in mammals

The study of mammals has promoted the development and testing of many ideas in contemporary ecology. Here we address recent developments in foraging and habitat selection, source–sink dynamics, competition (both within and between species), population cycles, predation (including apparent competition), mutualism, and biological invasions. Because mammals are appealing to the public, ecological insight gleaned from the study of mammals has disproportionate potential in educating the public about ecological principles and their application to wise management. Mammals have been central to many computational and statistical developments in recent years, including refinements to traditional approaches and metrics (e.g., capture-recapture) as well as advancements of novel and developing fields (e.g., spatial capture-recapture, occupancy modeling, integrated population models). The study of mammals also poses challenges in terms of fully characterizing dynamics in natural conditions. Ongoing climate change threatens to affect global ecosystems, and mammals provide visible and charismatic subjects for research on local and regional effects of such change as well as predictive modeling of the long-term effects on ecosystem function and stability. Although much remains to be done, the population ecology of mammals continues to be a vibrant and rapidly developing field. We anticipate that the next quarter century will prove as exciting and productive for the study of mammals as has the recent one.

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.

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.

Mobile platform sampling for designing environmental sensor networks

This paper proposes a method to design the deployment of sensor nodes in a new region where historical data is not available. A number of mobile platforms are simulated to build initial knowledge of the region. Further, an evolutionary algorithm is employed to find the optimum placement of a given number of sensor nodes that best represents the region of interest.