Sound carries substantial information about local biodiversity, being used for navigation and communication by a wide range of taxa. Acoustic information is now commonly used to assist in point-surveys of many of these species, aiding the identification of bats, grasshoppers, birds, amphibians, and even individual animals.
The integration of 3D audio sensors for acoustic monitoring could offer additional cues in order not only to be able to identify the species and numbers, but also to gather information about movements, direction, velocity, and other relevant data.
A 3D microphone array will be designed and integrated within a custom built multichannel audio recorder. High-quality low-power electret microphones will be arranged in a spherical array, in order to allow the recording of omnidirectional audio cues, as well as directional ones. The whole system will be integrated with a solar-powered deep-cycle battery, GPRS/3G/4G connectivity for regularly uploading recorded data, and data compression capabilities.
The system will designed in order to allow for simple one-manned installation on a tree. A series of benchmark tests will be carried out in order to calibrate the recording quality and data compression, allowing the recording of meaningful and usable data, and at the same time giving the possibility or regularly upload the recording data with non-optimal network coverage.
The system will be initially tested in the UK, using the VR acoustic facilities within the Dyson School of Design Engineering and the field sites at Silwood Park, and will then be deployed in Malaysia, as part of the on-going monitoring by Prof Ewers' research group.
With the recorded data, previously developed statistical methods will be used to implement autonomous, continuous biodiversity monitoring. First, species calls in the acoustic signal will be automatically detected using existing signal processing techniques, which allow to apply a battery of more than 9000 signal processing algorithms to species' calls to develop an acoustic 'fingerprint' for species (support from Dr Nick Jones from Imperial Mathematics will be sought for this specific research stage). Second, the spatial audio data will be decoded using techniques such as beamforming and 3D Ambisonic, to determine angular position and distance of detected sounds and calls. Third, we will use these data to identify individuals within an acoustic record, and use those data to apply detectability statistics to gain more accurate measures of species' abundances.
These metrics will be calibrated using field data on the species richness of bats, birds, amphibians, mammals and invertebrates, collected as part of on-going monitoring by Prof Ewers' research group in Malaysia. Snapshot samples of diversity of the various taxa at each of the acoustic monitoring sites will be used at multiple time points to test the correlations between observed biodiversity and acoustically derived species records and information metrics. These calibrated metrics will be compared in primary and logged rainforest and along a gradient of historical logging intensity to determine the impacts of forest disturbance on biodiversity.
The proposed research builds on a current PhD project (supervised by the same team), and aims at integrating on the developed acoustic monitoring device 3D microphone arrays and encoders, and at implementing novel methods and techniques to decode and analyse the spatial acoustic data.