understanding connectivity through song
Our previous work on Shortwing song showed that two genetically different sky islands were different in breeding song structure. This song project is an extension of this work to examine differences in song across all sky islands in the species’ range. This will help us examine if the predictions we made regarding population connectivity based on genetics hold for songs of all populations of the species both across islands and within islands across a fragmented landscape.
SHORTWING song across islands
Ramki Sreenivasan
People in the project
Chetana joined this project after working with Agumbe Rainforest Research Station. She has recorded songs on different sky islands over the last one year and contributed to building a song library for the project. She plans to start her Masters programme this year.
Pavan was part of the IIT team thar works on the technology front of this project. His major interest is in signal processing, particularly in speech recognition. He did some preliminary work with a code to automatically separate Shortwing songs from other species.
A final year undergraduate student from the Department of Electrical and Electronics Engineering NIT Jamshedpur, Mahesh is interested in Speech Signal Processing, Speech Recognition & DSP. As a Summer Research Fellow 2011 at IIT Madras, Mahesh developed a new algorithm for bird call identification based on speaker identification that won the 3rd poster prize at Young Ecologist Talk & Interact 2011. Currently developing bird call identification software on iOS or Android application, hardware implementation and extension to more species based on this algorithm.
Automated song monitoring
Shola habitat on any large sky island is fragmented and disconnected by the formation of commercial plantations about 100 - 150 years ago. This production landscape now hosts remnant shola forest patches that have been reported to harbour many threatened, endemic birds including the Shortwing. However, it is not clear if these birds are passing through these patches or if they are using these over a longer term for breeding.
This collaborative project is with Dr. Anil Prabhakar, from IIT Chennai is an avid birdwatcher who has always been interested in avian acoustics and has experience in signal processing. He has also been working on creating several automated devices and now hopes to build an automated recording device that will send us recordings of birds using the cellular phone network from this sky island landscape. The IIT Chennai team also includes Dr. Nitin Chandrachoodan helping us build the embedded systems and the wireless network and includes a few rotating students.
This collaborative study uses technology that can be used to answer several biological questions. We propose to examine occupancy of remnant forest patches by threatened, endemic birds in a production landscape. This project will provide the owners and managers of production landscapes in priority sites with an assessment of avian biodiversity in their land holdings. This information may be useful for these managers to get their private holdings audited or certified for green and conservation practices. The project will also engage with these owners and managers to sensitise them on the importance of such species. Over a longer period this can also lead to an understanding of timing of breeding of birds in the sky island complex and any possible effect of climate change.
Funding
IIT-Chennai
Support
NIAS
Ramki Sreenivasan
We are extending the current song work, complimenting the expanding genetic work , by collecting recordings of breeding songs (and calls) of different bird species on sky islands. We are hoping to examine if species with different levels of ecological specialisation have varying levels of song divergence.
multi-species song variation across islands
