IoT Heroes Create Wireless Network to Study Bats

01/19/2021 | Silicon Labs | 5 Min Read

We recently had the opportunity to speak with two authors using new and unconventional animal tracking research: biologist Simon Ripperger of the Department of Evolution, Ecology, and Organismal Biology at Ohio State University and engineer Niklas Duda of the Institute for Electronics Engineering, Friedrich-Alexander-University Erlangen-Nuremberg (FAU) in Germany. The talented duo's animal tracking research went viral in October when one of their new studies confirmed that vampire bats in the wild socially distance themselves when sick.

The social distancing study was one of several consecutive case studies published since 2019, detailing the first-of-its-kind wireless biologging network they designed to track and study wild bats. The new biologging technology allows for simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download - all of which enabled their team to collect never-before-available data and observations on bats in the wild. The wireless sensor network has not only resulted in riveting findings about the social nature of bats, it has also opened the door to a new realm of scientific knowledge concerning the spread of infectious diseases, wildlife resources, foraging strategies, and physiology. The two brilliant scientists explain how their research came about and how new technology is enabling scientists and animal conservation experts to break boundaries in animal biologging.

Tagged vampire bat (Desmodus rotundus)
Photo credit: Sherri & Brock Fenton

Tell us how you all started working together and give us some background on your bat studies.

Simon: I've been involved with this project since the end of 2013 and was inspired by my advisor, who is also a bat biologist. He used to go to Greece for field work all the time, but their method of tracking and biologging bats was a bit unbelievable - he was essentially running behind bats, chasing them with an antenna. We knew there had to be a better way to do this, and the university had a long history of cooperation between computer scientists, engineers, and biologists. They decided to create a big, collaborative project on wireless sensor networks using a fully automated tracking system for bats.

Bats are a great species to start with because they're elusive -it's hard to observe them, and they're nocturnal and tiny. If your project can succeed with bats, it can probably work with most species. This was the motivation for the research unit, which was funded by the German Research Foundation (DFG - Deutsche Forschungsgemeinschaft).

Can you tell us more about the wireless sensor network and how it gathers information?

Simon: I would say it is the most sophisticated sensor network for biologging -the degree of automation and data quality is certainly unique because we've combined different functionalities. We have high-resolution tracking to allow us to track animals with tags at small scales, and we also do proximity sensing. The tags can be as light as one gram, including housing and battery. If you look at systems for GPS tracking, the remote download function costs several grams because it's so expensive in terms of energy. This all adds considerable weight to the tags, so it's amazing to have this 1-gram tag with the option to retrieve data remotely.

For me as a biologist, the most exciting function is the proximity tracking. The tags talk to each other and exchange information, so we can get social networks of an entire group of animals every few seconds — simply mind-blowing if you have been studying social networks in animals — and the data quantity is amazing.

Why did you choose Silicon Labs for your wireless network?

Niklas: We have used Silicon Labs EFR32 SoCs since 2017 in all of our studies. Our tags have proximity logging and localization functions that operate at two different frequency levels. Before using Silicon Labs, we had to use three separate ICs to accommodate these functions. However, the Silicon Labs Flex Gecko integrates transceivers for both frequencies and a microprocessor core in one component. The ability to scale from three components to one makes the PCB smaller and makes it easier to control the radios, resulting in overall improved performance. We also wanted the Silicon Labs Gecko solution for its ultra-low-power functions. When tagging animals, we need our solution to be as small, light, and low power as possible, and Silicon Labs solutions support this need.

Can you tell us more about what you have learned about bats from your studies with the technology?

Simon: The first study we conducted was on noctule bats: European bats that live in city parks. Every few days, the bats switch their roosting site; therefore, we wanted to find out how offspring know where the group's ever-changing roosting sites are located. Up until now, this has been impossible to track. With our wireless network, we found that mothers actually guide their pups to the new roosting sites; they leave the roost together, fly together, and arrive at the new roost together. This first simple application of our proximity sensing discovered a whole new form of maternal care in bats.

We then moved on to studying vampire bats, the most social species of bats. They have social connections similar to human friendships as they recognize each other, prefer to associate with certain individuals from a group, groom each other, and even share food. This behavior has been studied mainly in captivity because it's so hard to observe bats in the wild. We were able to use our proximity sensors to see whether these social behaviors are simply an artifact of captivity or whether they held up in the wild. We took bats in captivity that we knew had social relationships with one another and released them back to the wild after two years. We could track associations between all the bats in their natural habitat and show that these social relationships were maintained in the wild, even with new bats to interact with and in a totally different setting. It showed for the first time that these relationships are very stable and persist in the wild. There would be no way to observe these behaviors without this technology.

One of your studies was widely covered by international media this past fall. Can you tell us about what you found?

Simon: We used our wireless network to observe bats' social networks and how they are affected when a bat is sick. We gave half the group an immune-challenging substance—a substance that doesn't actually make them sick but makes the immune system react. With our high-resolution data, we could observe what happens to the network when the bats get sick. We found that their social encounters decreased -what we call social distancing -and after this period of sickness, the level of interaction with the “sick” bats went back to normal. Essentially, we found they manage to distance themselves from the group when they feel sick.

What are your future plans for studies?

Niklas: We're spinning out a company, Dulog, to sell this technology to use with other animals. The technology is in development with several pilot customers and should be commercially available later this year.

Simon: The applications have no end - from preventing the spread of infectious diseases to studying information flow among social animals on food resources and even mating behavior—the sky is the limit! Why do social animals behave the way they do? With our technology, you can now observe their natural behaviors without interfering, but you can also use it to see how animals react to experimental approaches in the wild.

Where do you see the IoT going in the next 5-8 years?

Niklas: As IoT develops, sensors are getting smaller, which really benefits the scientific community - we reap the benefits of IoT that the larger commercial markets drive.

Simon: For biology, leaps forward have always been inspired by technology. Animal tracking has been around for 50 or 60 years, but advancements in IoT have allowed these recent developments to create a true renaissance in biologging and animal tracking. You can use benefits from ultra-low-power computing in various aspects of biology studies, and we not only get better data, but we can get it for a much wider range of animal species.

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