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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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• Help shape best-practice guidance on conservation technology - input to survey

🌍 Conservation technology is transforming how we protect wildlife, but are we thinking carefully enough about the risks? Drones, camera traps, GPS trackers, acoustic sensors, AI, and remote sensing have become essential tools for conservation practitioners around the world. They help us monitor species, detect threats, and respond faster than ever before. But these same technologies can also introduce unintended risks, and in some cases, can be exploited by those seeking to harm the very wildlife we're trying to protect. 🦏 Input now and/or join the discussions/research.  

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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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• Deep Voice - A Free Online Platform for AI-Based Marine Mammal Sound Detection and Classification

Passive acoustic monitoring floods marine researchers with data that can take months to annotate by hand, and the AI models that could help have long required Python setup, GitHub repos, and complex config files. Funded by the WILDLABS Awards 2025, Deep Voice removes that barrier with a free, public web app that turns marine mammal sound detection into a simple drag-and-drop task.