Anuran Bioacoustics & Behaviour
Studying how frogs vary their vocal sequence structure based on behavioural context
June 2019 - Aug 2020
Supervisors: Dr. Anand Krishnan, Dr. Seshadri K.S.
Do frogs use different types of vocal sequences in different contexts? If so, how may sequence structure vary with social context? I spent the monsoon of 2019 recording vocalizations of Nyctibatrachus humayuni, a frog with a simple two-note repertoire, and the monsoon of 2020 recording the vocalizations of Pseudophilautus amboli, a frog with a complex six-note repertoire, to try to answer these questions. This work was conducted as two summer projects in Dr. Anand Krishnan's lab at IISER Pune and in collaboration with Dr. Seshadri K.S., a postdoc in Dr. Maria Thaker’s lab at IISc. We uncovered evidence that anurans change vocal sequence structure based on behavioral context, and do so in diverse ways.
As part of this project, I developed a novel computational technique for analyzing vocal sequence that has since found more general applications in describing and studying the syntactic structure of animal vocalizations (Madabhushi et al. 2023). This technique, which we call 'co-occurrence analysis', is a more robust alternative to the common technique of obtaining transition probability matrices to describe vocal sequence structure by assuming the underlying processes are low-order Markovian, an assumption that we know is often not justified. If these ideas interest you, you can read more about it in Bhat et al. 2022 in Animal Behaviour (Feel free to email me if you do not have access to the full text). You can also listen to me give a quick ten minute talk on the work here: The presentation was selected as a finalist for SICB's Marlene Zuk best student presentation award in 2022.
As part of this project, I developed a novel computational technique for analyzing vocal sequence that has since found more general applications in describing and studying the syntactic structure of animal vocalizations (Madabhushi et al. 2023). This technique, which we call 'co-occurrence analysis', is a more robust alternative to the common technique of obtaining transition probability matrices to describe vocal sequence structure by assuming the underlying processes are low-order Markovian, an assumption that we know is often not justified. If these ideas interest you, you can read more about it in Bhat et al. 2022 in Animal Behaviour (Feel free to email me if you do not have access to the full text). You can also listen to me give a quick ten minute talk on the work here: The presentation was selected as a finalist for SICB's Marlene Zuk best student presentation award in 2022.