Real-time Bird Monitoring with Citizen-Science Data

The Prototype Biodiversity Digital Twin (pDT) for Real-time Bird Monitoring leverages the power of citizen science and artificial intelligence to track bird populations. Bird populations are highly responsive to environmental changes, making them excellent indicators of ecological health. Climate change, for example, has been shown to shift migratory patterns and disrupt breeding cycles, leading to mismatches between birds and their food resources. Monitoring these changes is crucial for understanding and mitigating the impacts of environmental shifts. Citizen science has a rich history in bird research, providing vast amounts of data, though often plagued by issues such as observer bias and inconsistent sampling efforts. Utilising a mobile application that records bird vocalisations, this pDT combines these recordings with AI-based classification to provide real-time insights into bird distributions and singing activity. This approach aims to overcome traditional challenges in citizen-science data collection and offers a new framework for continuous bird population monitoring.
To address these challenges, this pDT developed a mobile application named MK ("Muuttolintujen kevät" or "Spring of Migratory Birds" in Finnish), which utilises AI to classify bird vocalisations from audio recordings that are uploaded by anyone using the app. The app not only identifies specific species classifications for the users who upload these files but also uploads raw audio files for further analysis. This dual approach allows for continuous improvement of classification models and ensures data quality as well as engaging citizen scientists.
A main objective of this pDT is to evaluate the feasibility of using citizen science for real-time bird monitoring while ensuring the data's scientific robustness. We aim to integrate these data with existing long-term monitoring efforts by developing standardised point count modules and generating calibration data through simultaneous expert and AI-based counts. An additional goal is to increase public awareness of environmental science and the impacts of climate change on biodiversity.