To understand how different land uses affect ecosystem functions, the project applied InVEST modelling tools to map and quantify carbon storage, sediment retention, and habitat quality in three micro-watersheds. This allowed the project team and local stakeholders to see the “what” (the ecological state of the landscape), “why” (which land uses provided more benefits), and “how” (where interventions were needed). For instance, forest and shrubland areas were found to store significantly more carbon and reduce erosion compared to basic grain croplands. This modelling helped prioritize areas for restoration and agroforestry. The visual outputs and metrics supported evidence-based discussions with communities and decision-makers, integrating ecological science into watershed-level planning.

A collaborative and participatory approach is central to the development of training materials. To ensure relevance, practicability, and ownership, a task force is typically formed—comprising representatives from ministries, academia, fish farmers, value chain actors, and researchers. Iterative processes, validation workshops, and stakeholder consultations are employed to refine the materials and ensure they reflect local needs.

Training should address not only the 'how' but also the 'why'. By explaining the rationale behind specific practices—such as reducing environmental impacts or promoting food and nutrition security—farmers gain a deeper understanding and are empowered to make informed decisions that align with sustainability goals. This goes beyond simply following instructions; it fosters critical thinking and adaptive problem-solving.

To build resilient and thriving enterprises, training should also incorporate elements such as business education, innovations along the value chain, and the use of decentralized renewable energy technologies. These components enable fish farmers to enhance their financial literacy, respond to market and environmental challenges, and implement innovative solutions for increased productivity and sustainability.

The initial step is conducting a thorough needs assessment and gap analysis by experienced technical team members from the project and partners. This process involves screening existing materials, consulting with stakeholders and actors in the fish value chain and identifying gaps in knowledge and practice. A field survey can be conducted to collect data on the needs of the beneficiaries and necessary framework requirements for training, e.g. technology availability, training duration, and intervals. 

NOARKTECH’s WildGuard AI uses on-device Edge AI models and LoRaWAN communication to process data locally and transmit alerts even in low-connectivity regions. This low-power, scalable network allows instant wildfire detection, animal tracking, and real-time environmental monitoring.

NOARKTECH’s WildGuard AI integrates bio-acoustic microphones, air quality sensors (CO, VOC), and hyperlocal climate monitors to detect wildlife movement, forest fires, and ecological disturbances. This system enables real-time environmental intelligence for conservation, climate resilience, and human-wildlife conflict prevention.

The local leadership process began between 1997 and 1998,
when a group of artisanal fishers identified a growing conflict
with industrial fishing that affected their practices and territories.
The most critical point of the conflict occurred between 2002 and
2005, when the industry intensified its presence, generating loss
of equipment and greater pressure on the resources. This
prompted the community to organize to represent their interests
and seek solutions from the government. Leveraged by local
governance schemes, these leaders were able to support each
other in order to advance the process of establishing the ZEPA.

Building local and regional expertise in DNA barcoding and metabarcoding is vital for sustainable biodiversity conservation. Supported by BBI-CBD funding, our training programs target conservation practitioners from Lebanon, Tunisia, Côte d'Ivoire, and Jordan, including those without prior molecular biology experience. These hands-on workshops cover sample collection, laboratory techniques, data analysis, and interpretation, empowering participants to independently apply molecular tools in their contexts. Capacity building democratizes access to innovative technologies, fosters regional collaboration, and ensures continuity beyond the project lifecycle.

Meaningful engagement with Lebanese Ministries of Environment and Agriculture, local NGOs, practitioners, and communities ensured that scientific insights informed policy and restoration practices. By communicating findings clearly and collaboratively, we helped integrate molecular data into the National Biodiversity Action Plan. Awareness campaigns targeted schools, universities, farmers, and land managers, raising understanding of the ecological roles animals play in forest regeneration. This knowledge mobilization builds local ownership, promotes evidence-based decision-making, and bridges science with societal needs for long-term ecosystem resilience.

Partnerships with the Smithsonian Institution, iBOL, and Saint Joseph University have been central to our project’s success. The Smithsonian provided advanced expertise in metabarcoding methodology and quality assurance, enabling rigorous application of DNA analysis. iBOL supports the expansion of barcoding efforts, particularly for insects, linking our regional data to global biodiversity initiatives. Saint Joseph University leads research implementation and capacity building, ensuring regional ownership and continuity. These collaborations combine global knowledge with local ecological and institutional context, enabling innovation and scalability.

The creation of a comprehensive, open-access DNA reference library of native plant and animal species was foundational to our solution. Recognizing that global databases lacked coverage for many Eastern Mediterranean species, we built the first Lebanese library encompassing plants, mammals, and now expanding to insects, birds, and fungi. This reference database improves the accuracy of DNA sequence matching and enables precise identification of species present in environmental samples. It also fills a critical regional data gap and facilitates ecological studies, biodiversity monitoring, and conservation planning. By publishing the library openly, we promote transparency, collaboration, and the potential for adaptation in similar biodiversity hotspots.