NFTree deploys a robust Digital MRV system that combines satellite imagery, drone-based observation, artificial intelligence (AI), and community-sourced data to measure carbon stocks, forest productivity, and biodiversity. The system processes spatial and biophysical data using tools like Google Earth Engine and machine learning models to detect forest changes at high resolution. Community-based monitoring complements technological inputs to validate and enrich ecological datasets. This multi-source approach ensures transparent reporting, boosts credibility with buyers and donors, and enhances local engagement in conservation efforts .

NFTree tokenizes plots of 10x10 meters within conservation areas, using blockchain technology to create unique digital assets that represent ecological value, including carbon and biodiversity indicators. These NFTs are embedded with monitoring data generated by the dMRV system and are linked to geo-referenced locations. Each NFT is assigned a traceable identifier and linked to the DAO governance model, which regulates the reinvestment of funds. The proceeds from the purchase of NFTrees are allocated through a fiduciary fund to support the management and restoration of priority areas defined by the DAO statutes.

NFTree promotes the formation of decentralized autonomous organizations (DAOs) that operate as governance bodies co-designed with landowners and local actors. These DAOs are formalized through statutes that outline voting rights, membership, responsibilities, and procedures for fund allocation and monitoring. In places like Guayabillas, the DAO is adapted to local contexts and integrates with existing instruments such as community meetings. These governance structures enable transparency, local prioritization of conservation areas, and collective oversight of restoration and MRV efforts. NFTree incorporates digital tools to manage the DAO on-chain, while also maintaining analog mechanisms when needed due to technological constraints.

From soil moisture and water levels to animal migrations and habitat health, data from sensors travels via Cisco LoRaWAN gateways and Actility’s ThingPark™ Platform to central operations rooms, where platforms like EarthRanger provide a comprehensive 360-degree view of ecosystem health and threats. Previously, these have been donated by Cisco Inc. 
These LoRaWan gateways now support over 800 IoT sensors across protected areas. 

Actility  LoRaWAN Things Park Network ServerThe network server connects sensors, gateways and end-user applications and ensures reliable and secure data routing all along the LoRaWAN network. Along with the Operation Support System (or OSS), they are the brain that controls the complete LoRaWAN network

To address human-carnivore conflict, a range of protective measures were implemented in three villages of Limi Valley, Humla, Nepal, with the active involvement of local communities. These measures were designed to protect livestock from depredation by wolves and snow leopards, ensuring the safety of both local livelihoods and wildlife conservation efforts. Key actions include:

• Commitment to Zero Poaching Policy: Local villagers were engaged to establish a strong commitment to a zero-poaching policy, fostering a collective responsibility for wildlife protection.
• Construction of Communal Predator-Proof Night Corrals: Villagers collaborated to build sturdy, predator-proof corrals where livestock could be safely kept at night, reducing the risk of depredation.
• Distribution of Predator-Deterring Foxlights: Foxlights, an effective visual deterrent for predators, were distributed to livestock herders, helping to prevent attacks on livestock by mimicking a human patrolling with lights at night.
• Co-funding and Maintenance Responsibilities: Villagers took on responsibilities for co-funding the construction of the corrals and ensuring their proper maintenance over time, strengthening their investment in the success of the conservation efforts.

These actions were designed not only to protect livestock but also to build a sense of ownership and responsibility within the local communities, ensuring the sustainability of the efforts. GBF targets 8 and 9.

The creation of Community Conservation Groups (CCG) has been fundamental in building local capacity for effective conservation of the Himalayan wolf. These groups are composed entirely of local residents who are trained to participate actively in monitoring and conservation activities. Periodic workshops have been conducted to provide training in species monitoring, data collection, and camera trap management. Through these workshops, local participants gain valuable skills that enable them to contribute to the long-term success of the conservation project.

Community engagement and knowledge transfer are done by periodical workshops and follow-up on monitoring results using an audiovisual presentation. No remote digital platform can be used by local communities so far as there is no internet connection in the territory. The use of biodiversity credits as financial support for this block is currently under study. With this block we address the GBF targets 20, 21 and 22.

The research on Himalayan wolf ecological requirements to face the climate crisis is based on camera trap data collected in the field in Limi valley of upper Humla (Nepal) from 2021 and 2023. 61 Cameras were powered by batteries and information was stored in SD cards. SD cards were collected by local collaborators who were trained specifically on these management tasks. After delivery, data was deposited in a cloud storage and camera trap data was processed using Traptagger, Wild eye AI technology. Local collaborators were equipped with GPS devices to register events and handle camera trap management. With this block we address GBF targets 1, 2, 3, 4, 8, and 9. Targets 13 and 14 have already been reached through scientific output describing the uniqueness of Himalayan wolf genetic identity. (Werhahn 2018, Werhahn 2020).

Programs like eco-classrooms, guided tours, and school collaborations raised awareness, while immersive experiences, such as observing salmon in their natural habitats, fostered public engagement.

More than 500,000 native trees were planted, converting polluted farmlands into forested areas. Additionally, wastewater treatment systems were implemented to minimize runoff from recreational zones.