Advancing European Taxonomic for Biodiversity Conservation (BioTax-EU)

Specific Objectives
This proposal aims to strengthen taxonomy-related skills and capacities, especially for underrepresented taxa and regions. It envisions an open-access, FAIR-aligned catalogue of taxonomic databases integrating genetic, species-level, and ecosystem classification data for scientific and policy applications. The project will pilot advanced taxonomic tools, such as AI-enhanced species recognition and environmental DNA/RNA analytics, to improve biodiversity monitoring. By linking taxonomy with monitoring systems, it will help standardize data collection and management across Europe. The initiative includes citizen science and stakeholder engagement to broaden participation and knowledge dissemination. Financial support will be offered to third parties—especially in Central and Eastern Europe, the Mediterranean, and outermost regions—to address expertise and data gaps.

Ambition
The project aims to reshape European biodiversity taxonomy by integrating identification, digitalization, and data management into unified, standardized workflows. It will establish a robust biodiversity data infrastructure and long-term monitoring based on expert-validated, tech-driven methodologies. Innovations in genomics—such as DNA barcoding, metagenomics, and whole-genome sequencing—will broaden biodiversity assessments. A Europe-wide network of taxonomy and genomics experts will be developed, supported by structured training and certification. Outputs will align with EU environmental policies and global biodiversity governance to ensure scientific results inform regulation and sustainability.

Methodology
A collaborative network of taxonomists, genomics labs, research institutions, and policy actors will be formed to co-create training programs, structured around ECTS. Through workshops, online courses, and certifications, the project will build capacity in underrepresented regions.

Digital taxonomy will advance via an open-access catalogue merging existing databases and ensuring FAIR-compliant interoperability. Integrated data will span from genetic sequences to habitat classifications. AI and machine learning will support species recognition and data harmonization.

The project will pilot innovative taxonomic methods, including eDNA/eRNA analysis, AI-powered recognition, and standardized sampling protocols. A repository of validated reference collections and ID keys will support fieldwork and taxonomy professionals.

Citizen science will contribute to data collection and public awareness. Strong policy interfaces, in coordination with the EC Knowledge Centre for Biodiversity and BioAgora, will promote uptake of scientific results in policy-making.

Up to 30% of EU funding will be sub-granted to third-party entities in targeted regions to bridge knowledge and data gaps. A transparent selection process will guide support, monitor progress, and ensure integration of outcomes.

Expected Impact
The project will strengthen European taxonomic infrastructure and expertise, align biodiversity monitoring with conservation policies, and support a high-quality data ecosystem. It will enhance Europe’s capacity to meet biodiversity targets and contribute to the Kunming-Montréal Framework. Broad engagement of scientists, citizens, and policymakers will foster an inclusive model for biodiversity conservation and research.