Environmental Monitoring and AssessmentEcologyPeer-reviewed journal article
Passive acoustic monitoring as a tool for early detection of invasive animal species: a systematic review and a case study
David BeckeriD, Marit Kinga KasteniD, Torben WeberiD, Ingo GraßiD, Thomas HilleriD
Abstract
Invasive animal species are spreading rapidly across the globe, creating an urgent need for efficient early-detection and monitoring tools. Passive acoustic monitoring has become an established method in biodiversity research, but its application to invasive species monitoring has been less systematically explored. Here, we combine a systematic literature review with a field-based case study to evaluate the potential of passive acoustic monitoring for invasive animal detection. We identified 26 studies on acoustic monitoring of invasive animals, mainly addressing amphibians (11 studies), birds and fish (five each) with most studies from the USA and Australia. The use of acoustic monitoring of invasive species has increased during the past decade, with recent studies applying automated detection, machine learning, and large-scale monitoring frameworks. As a case study, we further tested the feasibility of low-cost acoustic monitoring of the invasive American bullfrog (Lithobates catesbeianus) in southwestern Germany, combined with automated identification using BirdNET. We successfully confirmed bullfrog presence in eight of the eleven monitored lakes, including sites close to a protected nature reserve. Our results highlight the growing potential of passive acoustic monitoring of invasive species under field conditions. In combination with automated species detection, manual validation, and emerging real-time monitoring devices, passive acoustic monitoring becomes an increasingly powerful tool for early intervention and scalable management of biological invasions.
- assay: imaging
- research focus: ecology & biodiversity
- approach: statistical model
- approach: benchmark study
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 11th percentile
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