Bats have caught the attention of a number of scientists and have been the subject of several studies in recent times (see a, b, c). Researchers are now in the midst of a new project called, “CULTSONG“, which studies animal culture and examines bat song dialects that differ from less distinct general chatter and are used for specific social purposes such as territorial signalling and courtship.
This work may have significant implications for investigating how culture – or learning gained through socially transmitted behavior – affects evolution. That includes human evolution, which is already known to have been influenced through interactions between culture and genes, such as in the development of lactose tolerance after the onset of livestock farming. Additionally, vocal learning in other mammals has only had limited study, so these new investigations could help shed light on how language evolves.
Due to the complexity of their communication bats offer a rich means to analyze social interaction and linguistic development in animals in general. Recently, for example, researchers found through sound recordings that adult S. bilineata females use ‘baby talk’ with a different timbre and pitch when addressing pups. Scientists speculate that this behavior could perform a similar role to that in humans, where it increases attention and facilitates vocal learning by helping the baby to pick out elements of speech.
Other recent research has also highlighted the fact that bat interactions are more complex than previously believed such as the finding that adult male bats communicate differently with pups in a way that seems to transmit their group’s ‘vocal signature’.
In the GPS-Bat project, researchers at Tel Aviv University in Israel have been looking into social communication as part of decision-making in bats. Rather than researching the cultural implications of bat songs as the previously mentioned study has done, the Israeli team is looking into interaction through bats’ everyday background ‘chattering’. The study has been made possible by new technology such as machine-learning tools adapted from use for human voice recognition.
The team captured adult Egyptian fruit bats (Rousettus aegyptiacus) in a natural roost in Israel, then continuously monitored them and the pups they gave birth to using ultrasonic microphones and video cameras. Machine learning enabled them to discern context from the chatter’s frequency, such as whether it concerned food, sleep or sex, as well as the specific individuals involved.
The Israeli research team has also created a publicly available database of almost 300,000 files that is described as ‘probably one of the biggest databases ever collected for an animal’, representing the full repertoire of bat vocalizations they recorded. The goal is to provide a comprehensive starting point for further studies in animal social communication.
Researchers have also demonstrated the emergence of chatter dialects through social learning in bats. In one study, three groups of pups were exposed for a year, until adulthood, to their mothers’ vocalizations, plus an artificial playback representing a group-specific dialect. They each emerged with distinct dialects biased towards the playback, suggesting bats are influenced by the entire social crowd around them.
The team is now further analyzing the data set it has created, looking to break down the bats’ communication in-depth by analyzing the order of sounds in their vocalizations to find out the structure of this ‘language’ – something that can be likened to examining syntax in human speech.