Research poster - "Listening to mangroves: Using Autonomous Recording Units and Machine Learning tools to assess avian biodiversity in the mangroves of coastal Suriname"
Abstract:
This exploratory study investigates avian biodiversity in the mangroves of coastal Suriname, as part of an interdisciplinary project on flood risk management and coastline mapping. Automated Recording Units (ARUs) were deployed between December 2024–February 2025 and April–July 2025 across six focal sites representing the three species of mangroves found in the area: Avicennia germinans (Black), Laguncularia racemosa (White), and Rhizophora mangle (Red). Bird vocalisations were extracted from audio recordings and classified using the BirdNET algorithm. Acoustic Indices were calculated from the same audio and related to both mangrove composition and bird species richness. The results provide new information on the ecology of these mangrove habitats. By integrating non-invasive remote monitoring with machine-learning tools such as BirdNET, this study demonstrates how these state-of-the-art tools can aid our understanding of ecosystems in a data-driven world.
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