AI species recognition: This product uses AI recognition as the underlying technology, with endangered species as the core recognition object. It trains a large biodiversity recognition model that can support monitoring of mountains, rivers, forests, fields, lakes, grasses, and sands systems. The model is free and open to public welfare organizations dedicated to biodiversity conservation, such as research institutes, conservation organizations, and individuals. The reason why "wild friends" are so powerful is because they have a powerful "engine": YOLO World.
As the underlying universal model of 'wild friends', its primary characteristic is strong learning ability. It has powerful multimodal zero sample recognition and few sample recognition capabilities, which means it can quickly identify animal location regions and species information of multiple species through a small number of samples. For example, to recognize a new species, traditional models require thousands of photos and several days of training; YOLO World only requires a small number of photos and training iterations to achieve rapid adaptation.
Secondly, it has a high degree of tolerance. No longer limited to training and prediction of specific species, it has strong open vocabulary recognition ability and zero sample recognition ability, and can accurately identify and locate untrained species. For example, traditional models can only recognize trained species such as tigers and antelopes; The new model can also recognize snow leopards and foxes simultaneously - even if it has never trained these two animals before.
Another advantage of "wild friends" is that they spend less money. Common AI models heavily rely on high-performance acceleration cards, which result in high costs for both hardware environment and maintenance operations.
 

Developing different dissemination methods strengthens communication within the interface of research, policy, and practice. While a study's core findings may remain consistent, the way these results are shared must be tailored to suit the specific needs, preferences, and capacities of different stakeholders. This approach ensures that the information is not only accessible but also impactful, empowering stakeholders to make informed decisions or take appropriate action.

 For example, within the context of accompanying research in FLR implementation, the way results are communicated to implementers and policymakers differs from the approach used for academic audiences. Policymakers and implementers often operate in fast-paced environments where they require clear, concise, and actionable information. Policymakers and implementers benefit most from concise, straightforward communication that highlights actionable insights, often set apart from the detailed and structured format of scientific articles. 

By recognizing and adapting to these differences, our project as accompanying research bridges the gaps between evidence generation and practical application, fostering stronger connections and more meaningful collaborations between the worlds of science, policy, and practice.

The TREES project employs a multi-scale, cross-disciplinary approach to synthesize data from environmental, social, and economic analyses, providing a holistic understanding of FLR impacts across Africa with a key focus on East and West Africa. To achieve this goal, the overall objective is to mitigate the impacts of climate change in Africa through synthesis research that informs FLR policies and practices. This approach allows for a nuanced understanding of FLR practices and their impacts, which are adaptable across different regions. By combining data from various disciplines, including environmental science, social science, and economic analyses, the project provides a holistic understanding of FLR practices and their complex interplay. Therefore, similar research methods are applied in order to look into similar problems under different contexts. The multi-disciplinary research methods applied in different countries are contextualized to come up with research based tailored solutions to the context of the country.

An annual international mobility program of 3 months per year was set up for all PhD students based in the countries of F4F implementation. The programme was designed in a way that all PhDs came to the host institution in Germany (ZALF) at the same time, in order to facilitate a structured PhD supervision system. Whilst in Germany, the stay consisted of multiple interlinked components, such as: desk-based research activities, integration in host institution’s meetings and events, joined workshops on project planning, methods trainings, reflections on PhD progress (chances and challenges), in-person status meetings with GIZ/F4F, as well as joined outreach activities including for example a symposia by GIZ and ZALF on restoration in the Global South in Bonn and a workshop on the concept of Accompanying research at TropentagConference2023 in Berlin. Students were also encourage to participate in further trainings and conferences depending on individual interests and needs. 

To facilitate global collaborations, strengthening of international research structures, capacity building and global learning, the TREES project as solution strongly builds on international partnerships. The team itself is composed in most of the countries of international research tandems, whereby PhD and Master students originate from the country of study as well as Germany or other country. Whilst each student has his/her individual research focus, data collection is planned and implemented in the binational tandems. Supervision is provided in international supervision tandems whereby in each country a university is taking the country lead and co-supervision is provided by the project lead organization.  

We include renewable energy technologies such us solar panels  to power electic fences, improve livestoc water availability and sensored lights to mitigate economical loses in livestoc farms caused by predation over domestic animales, at the same time, we help rural farmer families to access electricity serveces and improve their food productivity, economicla and food founts

Our efforts are focused on developing a conservation culture in local communities by highlighting local biodiversity in local art expressions, educational programs, institutional alliances, local social movements engagement and scientific research.

We develop wildcats and potential prey community based monitoring with the families associated with Serraniagua in their private natural reserves by employing a small set of five trap cameras.

Collaborative planning space where all of the key actors at landscape scale work together to establish clear achievable goals that will lead to human-wild cats coexistence setting clear key indicators