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.  

Advancements in on-board technologies and AI integration hold great potential to further enhance the existing drone-based crocodilian monitoring method. Improvements in drone hardware, such as hybrid models with extended flight times and enhanced camera resolutions, allow for broader habitat coverage and the capture of more detailed imagery in complex environments. Integrating artificial intelligence (AI) represents a significant opportunity to streamline image analysis by automating crocodile detection and size estimation using allometric models. These AI-driven enhancements could provide near real-time data processing, reducing reliance on time consuming manual analysis.

This improvements are currently under development. We conducted an experimental study in Cameroon in April 2025 with students and young researchers from the University of Ngaoundéré and local NGOs, using drones equipped with thermal cameras and searchlights, and including AI-assisted automated data processing.

This building block on capacity building on local stakeholders including Indigenous including Peoples and Local Communities (IPLCs) to operate drones, enabling them to take active roles in conservation. 

Ease of Use of the method devellopted:

1. Minimal Technical Skills Required:
   Users only need basic training in drone operation and measurement extraction from high-resolution images. The process is straightforward:
   • Fly the drone following the standardized flight protocol.
   • Marke crocodilians on overhead images.
   • Measure the visible head length using accessible image analysis tools (e.g., ImageJ, QGIS).
   • Apply the corresponding allometric equation or lookup from pre-prepared tables (abaques) for total length estimation.
2. Readily Adaptable:
   The framework uses easy-to-read tables (abaques), making it accessible to both specilialists and non-specialists for operators can quickly apply the method without requiring advanced scientific expertise.
3. Accessible Equipment:
   The approach relies on consumer-grade drones and widely available software, ensuring affordability and reducing barriers to adoption.

Why It’s Effective:

The framework’s simplicity, scalability, and reliability make it ideal for diverse contexts, from remote wetlands to urban-adjacent habitats. It empowers a broad range of users to generate scientifically robust data.

The allometric framework is a non-invasive tool designed to estimate the total body length of crocodilians based on the measurement of their head length, captured through high-resolution drone imagery. By leveraging established species-specific head-to-body length ratios, this method eliminates the need for physical capture or handling, reducing risks for both researchers and wildlife. Validated for 17 of the 27 crocodilian species, the framework allow to provides reliable demographic data essential for population monitoring and conservation management.

The framework uses easy-to-read tables (abaques), making it accessible to non-specialists, operators can quickly apply the method without requiring advanced scientific expertise.

Understanding the demographic structure is vital for wildlife research and conservation. For crocodylians, accurately estimating total length and demographic class usually necessitates close observation or capture, often of partially immersed individuals, leading to potential imprecision and risk. Drone technology offers a bias-free, safer alternative for classification. This study evaluated the effectiveness of drone photos combined with head length allometric relationships to estimate total length, and propose a standardized method for drone-based crocodylian demographic classification. 

This building block establishes standardized flight parameters for effective crocodilian monitoring

• Involvement of the local community
• Responding to community needs 

For many conservationists, including our participants, the knowledge to effectively use conservation technology is not enough without the funding to access the tools. Recognizing this barrier, we provide each participant with USD$500 in seed funding to support the implementation of their conservation solutions. Participants are required to propose and carry out projects, which have ranged from building predator-proof bomas and underwater camera traps to developing AI tools, mobile apps, and community-driven citizen science initiatives. Each participant is required to report on their project’s progress over the following year, fostering accountability and impact tracking.

To ensure long-term sustainability, we also deliver training in grant writing, proposal development, and funder engagement to equip participants with the skills needed to secure sustained future funding. Ongoing mentorship and support also continue beyond the initial training. Our team, along with a growing alumni network, provides guidance on grant applications, reference letters, and professional development opportunities. Many of the projects and collaborations initiated during the program have led to graduate study, published research, and conference presentations, reinforcing participants’ continued growth as conservation leaders. 

Our technical training emphasizes experiential learning by giving participants direct, practical experience with conservation technologies. Whenever possible, students are encouraged to set up and deploy tools themselves in safe, low-pressure environments, creating space to experiment, make mistakes, and learn by doing. For instance, students may choose camera trap locations based on the classroom training module, then evaluate the effectiveness of their decisions by analyzing the resulting data. This process helps bridge theory and practice while building confidence in problem-solving and tool use.

In cases where participants cannot operate the tools directly, trainers and field practitioners from host institutions provide live demonstrations, such as tracking wildlife using GPS or operating drones, ensuring students still gain exposure to how these technologies function in real-world conservation settings.

We select participants who are at the beginning stages of their careers, such as those who have completed their bachelor’s degrees and are entering the NGO or conservation workforce or embarking on higher education.The goal is to identify participants whose careers would benefit the most from the type and amount of training, funding, mentorship, and support we provide. Over the past two years, we’ve recruited at least one participant from a non-academic background who nevertheless possesses extensive on-the-ground experience. These individuals have thrived in the program, highlighting an opportunity to further cater to this audience in future iterations.