Passive acoustic surveillance (PAS) technology has the potential to help prevent establishment of acoustically (i.e. sound) identifiable high-risk invasive species, from both developed and developing countries.
Detecting invasive species early leads to more feasible and cost-effective control and potential eradication. PAS could provide a solution for repeated, long-term, continuous monitoring – potentially over large spatial scales in a variety of habitats, generating data that can be curated and permanently stored for collaborative multi-disciplinary use in much the same way as traditional museum specimens. To overcome difficulties associated with managing and analysing excessively large volumes of data, researchers have developed species-specific algorithms to automate the detection of a wide variety of mammalian, avian, amphibian and invertebrate taxa (summarised in Aide et al 2013).
In addition to developing a final automated remote detection system for starlings, we will also draw upon the outputs from CISS Project Development of integrated passive and active surveillance tools and networks and recent international research identifying the high-risk transport pathways for invasive species (e.g. Tingley et al 2017) and design an additional species-specific detection algorithm. We will integrate this algorithm with innovative remotely accessible passive acoustic surveillance units built from affordable, effective and accessible electronic components. In collaboration with end-users, we aim to demonstrate the benefits of PAS by deploying multiple units in key locations.
The project receives funding from the Australian Government Department of Agriculture, Water and Environment
February 2021 update:
A working prototype device is collecting data from Adelaide. A second different approach to audio processing is also being developed. Both approaches are constantly being refined and outputs from both methods are being compared to determine the most precise, accurate and energy efficient option.
To maximise the surveillance area, and reduce slow processing, storage space and power consumption of the device, a single compression microphone is being investigated over a stereo recording channel. Possibilities to ensure the devices can transfer data from remote field locations is also being researched.
Potential sources of some common false positives from the project area have been identified (e.g. Australian Golden Whistler, Swamp Harrier, New Holland Honey-eater, Yellow throated miner) the algorithm is being trained to avoid returning these species as false detections.