SAFE project - audio recordings; Birds in Borneo

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Dear Colleagues,

The SAFE Project has been placing recording devices throughout the rainforest in Borneo. That audio is now available to listen to here - acoustics.safeproject.net.

Try out listening to the dawn chorus starting at 6am when the animals are just waking. Or see if you can work out which of the animals you're hearing on the stream - we'll list animals that live in that area and area likely to be around at that time. You may also be surprised to find out that from the sound alone you are able to hear differences between separate parts of the forest.

We hope you enjoy exploring.

For more information about the audio recording devices we developed for this project, please see the paper we recently published in Methods in Ecology and Evolution -

https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.13089   

Best regards
Lorenzo

-- 
Dr Lorenzo Picinali
Senior Lecturer in Audio Experience Design
Director of Undergraduate Studies
Dyson School of Design Engineering
Imperial College London
Dyson Building
Imperial College Road
South Kensington, SW7 2DB, London 
T: 0044 (0)20 7594 8158
E: l.picinali@imperial.ac.uk

http://www.imperial.ac.uk/people/l.picinali

www.imperial.ac.uk/design-engineering-school

Abstract

1. Automated methods of monitoring ecosystems provide a cost‐effective way to track changes in natural system's dynamics across temporal and spatial scales. However, methods of recording and storing data captured from the field still require significant manual effort.
2. Here, we introduce an open source, inexpensive, fully autonomous ecosystem monitoring unit for capturing and remotely transmitting continuous data streams from field sites over long time‐periods. We provide a modular software framework for deploying various sensors, together with implementations to demonstrate proof of concept for continuous audio monitoring and time‐lapse photography.
3. We show how our system can outperform comparable technologies for fractions of the cost, provided a local mobile network link is available. The system is robust to unreliable network signals and has been shown to function in extreme environmental conditions, such as in the tropical rainforests of Sabah, Borneo.
4. We provide full details on how to assemble the hardware, and the open‐source software. Paired with appropriate automated analysis techniques, this system could provide spatially dense, near real‐time, continuous insights into ecosystem and biodiversity dynamics at a low cost.