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- Conservation Technology - Paris, France
Artificial intelligence is increasingly being used in the field to analyse information collected by wildlife conservationists, from camera traps and satellite images to audio recordings. AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings - hugely reducing the manual labour required to collect vital conservation data. The AI For Conservation group is intended to unite and inspire all WILDLABS community members—whether already involved in AI for conservation, or not—to understand how to use and/or directly contribute to open-source research and development efforts.
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- Open-Source Solutions for Amphibian Passive Acoustic Monitoring: Lessons from Patagonia
Monitoring amphibians across the temperate forests of Patagonia presents significant logistical and technical challenges. Remote locations, harsh environmental conditions, and the large volumes of data generated by Passive Acoustic Monitoring (PAM) can make long-term biodiversity surveys difficult to implement and maintain. In addition, environmental data often relies on multiple independent devices, increasing costs, complexity, and logistical demands in remote field conditions. Through the WILDLABS Awards 2025, our team explored practical ways to address these challenges by combining open-source hardware, environmental sensing, and AI-assisted acoustic analysis.
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The Animal Movement Group is a collaborative community dedicated to advancing the study, monitoring, and conservation of animal movement. It provides a space for researchers, practitioners, and innovators to exchange knowledge, explore bio-logging approaches and data, and address conservation challenges linked to species mobility.
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- Wild Moves and Wild Album: New GBIF Data Portals for Animal Tracking and Camera Trap Data
New data portals are making it easier to discover and explore wildlife tracking and camera trap datasets from around the world.
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