Despite extensive research activities, significant knowledge gaps about biodiversity still exist. Many species, their genetic differences, and their functions within ecosystems are still insufficiently researched.

With the funding measure “BiodivDetect – Technologies and Methods for Recording and Assessing Unexplored Aspects of Biodiversity in Germany” want that BMFTR help to close these knowledge gaps.

The focus is on research and development projects that combine modern technologies with biological and ecological expertise.

Artificial Intelligence can help analyze large and complex data sets, automatically identify organisms, and investigate previously difficult-to-detect relationships within ecosystems.

In addition to AI-based analytical methods, the funding guidelines mention remote sensing, high-throughput sequencing, and robotics as relevant technologies.

Three focuses of funding

The funded research networks should consider all three thematic priorities of the call:

1. Develop tools and use technologies

The first focus is on the development and application of innovative methods for recording biological diversity. This includes in particular modern sensors, automated processes, and AI-supported data analysis.

2. Capture hidden biodiversity and uncover functional significance

The second focus is on previously little-researched species, genetic diversity, and ecological functions. The aim is to gain new insights into how different organisms contribute to the functioning and stability of ecosystems.

3. Implement technologies and transfer insights into applications

The developed methods and research findings should be incorporated into concrete applications. This includes, for example, biodiversity monitoring, assessment of ecological changes, and support for conservation and management measures.

A particular focus is on terrestrial ecosystems and inland waters, especially rivers and lakes. Marine ecosystems are not the subject of the tender.

Data quality and automated evaluation in focus

A central goal of BiodivDetect is to establish long-term usable and quality-assured data foundations.

These are intended to allow comparisons of changes in biological diversity over longer periods and across different regions.

Especially for AI applications, the availability of high-quality data is crucial. Automated detection methods can, for example, help to systematically evaluate large amounts of image, sensor, or genetic data.

The funding measure therefore combines technological innovations with taxonomic expertise, natural history collections, and citizen science approaches.

The insights gained should enable a more informed assessment of biodiversity changes in the long term and the development of effective conservation measures.

Up to 1.5 million euros per research association

Being promoted exclusively joint projects with a clear application and transfer reference.

Eligible applicants include, in particular, universities, non-university research institutions, research museums, public institutions, and commercial enterprises. Other suitable institutions may also participate if they make a professionally justified contribution to the project.

Application deadline

Project sketches for BiodivDetect can be submitted until 26. November 2026 be submitted.

The selection process consists of two stages. Initially, the research networks submit a project outline. The template provided by the project sponsor Jülich must be used for this.

After the evaluation, selected associations are invited to submit a full funding application.

The measure is part of the BMFTR research initiative for the preservation of biodiversity (FEdA) and contributes to the research strategy "Research for Sustainability" (FONA).

In particular, there are points of connection for the AI ecosystem in the areas Computer vision, machine learning, remote sensing, automated pattern recognition, and intelligent data analysis.