Editor's note
Transparency is the theme of this week.
Across monitoring platforms, carbon projects, supply chains, and research, forestry is moving toward systems where assumptions can be inspected rather than taken on trust. Not because regulation demands it, but because credibility increasingly depends on it.
What stands out is that this shift is not driven by entirely new data. It is driven by better use of existing datasets—connected, exposed, and made legible through AI. When information becomes easier to interrogate, transparency stops being a promise and starts being a property of the system itself.
Axel
WHAT GOT ME THINKING
Global Nature Watch Goes Live with AI Forest Monitoring
Land & Carbon Lab (convened by World Resources Institute and Bezos Earth Fund) has officially opened Global Nature Watch, an AI-powered platform that combines 80+ peer-reviewed datasets into a single chat interface. Users can ask questions in plain language, like "What's the carbon stock in this forest?" and receive maps, statistics, and satellite imagery instantly. The system monitors all ecosystems (not just forests), tracks real-time disturbances, and operates in 170+ languages, making planetary-scale environmental data accessible to anyone.
Axel’s notes: What makes this particularly interesting is not the volume of data, but how it is exposed. By connecting dozens of established, peer-reviewed datasets and placing them behind a conversational interface, Global Nature Watch lowers the barrier to scrutiny dramatically.
This is a strong proof point that the future lies in doing more with data that already exists. AI here is not generating new knowledge, but enabling access, comparison, and questioning at a scale that was previously impractical. When anyone can ask how carbon stocks, disturbances, or land use change are measured—and immediately see the underlying evidence—transparency becomes operational rather than rhetorical.
Romanian Forest Project Makes All Verification Data Public
Vlad Chitulescu, a Romanian forest owner behind Silvador, posted January 29 that he's publishing all his forest carbon verification data publicly—no NDA, no login required. Breaking with industry norms where project documentation is often locked behind access walls, he's making baseline studies, monitoring reports, and third-party audits freely available to anyone. His bet: radical transparency attracts better buyers than sales pitches. Silvador uses LiDAR, drones, and AI to monitor 1,000+ hectares and holds triple certification (VCS, SD VISta, FSC). The tech stack and open-data approach offer a glimpse of how the next generation of forest owners might compete in carbon markets.
Fast-Growing Trees Reshape Forests And Challenge AI Models
New research published January 27 shows that fast-growing, naturalized tree species are increasingly dominating future forests across Europe and North America. While ecologically interesting, the shift has major implications for AI-driven reforestation planning: many models assume historical species distributions will hold, but climate change is rewriting the rulebook. Forest managers using AI for site-species matching will need to update their training data to reflect which trees actually thrive, not just which were traditionally planted.
Deep Learning Tracks Individual Logs from Stump to Mill
A new peer-reviewed study in the International Journal of Forest Engineering presents a "precise deep learning approach" for timber traceability along the entire value chain. The system uses neural networks to identify and track individual logs from harvest through processing, addressing transparency challenges in timber supply chains. It's a practical step toward verifying legal sourcing and ensuring chain-of-custody compliance without relying solely on paper documentation.
LiDAR Drones Map the Maya Forest in Eight Days
An expedition just completed an eight-day aerial mapping campaign across the Maya Forest Corridor in Belize and Guatemala using LiDAR-equipped drones. The Trinity Quantum Pro and Sky Front Perimeter 8 systems collected high-precision topography and vegetation structure data even through dense canopy, enabling carbon stock estimates and ecosystem health assessments in hard-to-reach areas. The Wildlife Conservation Society led the effort with support from Island Foundation and local aviation authorities.