TABMON

Context

TABMON is a research project that aims to advance biodiversity monitoring across Europe through a novel approach using autonomous acoustic sensing. This project is designed to fill gaps in current biodiversity reporting and contribute to achieving the targets set in the EU Biodiversity Strategy for 2030. It involves harmonising the collection, analysis, and integration of acoustic biodiversity observations, leveraging advancements in technology and Artificial Intelligence (AI).

At its core, TABMON seeks to demonstrate the effectiveness of acoustic observation in transnational biodiversity monitoring. It focuses on deploying an acoustic monitoring network that captures and analyses sounds across different European landscapes, using these audio data to gain insights into species distribution, abundance, and migration patterns. Through its innovative approach and transdisciplinary collaboration, TABMON sets out to enhance the effectiveness of biodiversity monitoring and contribute significantly to the conservation and management of European biodiversity.

Main objectives

The central objective of TABMON is to develop a transnational biodiversity monitoring with autonomous acoustic sensors across a large latitudinal range in Europe, demonstrating how acoustic sensing can complement existing monitoring efforts to fill current gaps in reporting to EU directives, and assessing the targets outlined in the EU Biodiversity Strategy.

Main activities

The TABMON project is characterised by a series of specific, targeted activities that collectively aim to advance the field of biodiversity monitoring through acoustic techniques:

• Acoustic Sensor Deployment: Installation of advanced acoustic sensors across various European biodiversity ecosystems to record natural soundscapes. These sensors are designed to continuously record the natural soundscapes of various ecosystems, capturing a wide array of biological sounds that indicate the presence and activities of different species.
• Data Collection and Analysis: The recorded audio data, rich in ecological information, will be systematically collected and analysed using sophisticated artificial intelligence algorithms. This process involves identifying species- specific calls and sounds, which can provide insights into species diversity, population density, and behavioural patterns.
• Biodiversity Indicators Development: Based on the analysis, the project will develop key biodiversity indicators that can be used to assess the state of ecosystems and track changes over time. These indicators will be crucial for informing conservation strategies and policy decisions.