Informace o projektu
DNAquaIMG: Innovating transnational aquatic biodiversity monitoring using high-throughput DNA tools and automated image recognition
(DNAquaIMG)
- Kód projektu
- SS73020001
- Období řešení
- 1/2024 - 12/2026
- Investor / Programový rámec / typ projektu
-
Technologická agentura ČR
- ERA-NET/Partnerství
- Partnerství pro biodiverzitu
- Fakulta / Pracoviště MU
- Přírodovědecká fakulta
- Spolupracující organizace
-
University of Jyväskylä
Aarhus Universitet
- Odpovědná osoba Claus Melvad
- Odpovědná osoba Patrick Leitner
- Odpovědná osoba Karolina Bacela-Spychalska
- Odpovědná osoba Florian Leese
- Odpovědná osoba Djuradj Milosevic
University College Dublin/Nattional University of Ireland
- Odpovědná osoba Mary Kelly-Quinn
Centro de Investigaçao em Biodiversidade e Recursos Genéticos
Swedish University of Agricultural Sciences
DNAquaIMG represents a transnational consortium with internationally leading expertise in DNA-based assessments of freshwater environments as well as the application of innovative automated image recognition methods for freshwater species detection. Both approaches hold complementary benefits to biodiversity assessments: DNA metabarcoding provides high taxonomic resolution and enables detection of yet undescribed biodiversity. In contrast, image-based methods can provide reliable species’ abundance data, size structure, and biomass, but may only identify specimens to coarse taxonomic resolution. In combination, these complementary tools offer an opportunity for greatly enriched data from bulk samples. With this project, we develop a strategy for improved transnational monitoring of biodiversity and ecosystem change using these novel tools in tandem. Specifically, we propose to further develop, test and harmonize DNA-based biodiversity monitoring and automated image-based biodiversity assessment and to provide a roadmap on how to implement these two novel monitoring approaches in combination into the existing monitoring context of the European Water Framework Directive (EG/2000/60, WFD). Using samples collected across a gradient of ecological quality classes determined through routine biomonitoring we will quantify the corresponding biodiversity change that results from a deterioration from a high to good, moderate, poor or bad status. Concomitantly, we will infer data from stream restoration case studies to assess if the improvement of ecological quality class is reflected in biodiversity increase. By this, DNAquaIMG will set the basis to generate more inclusive information on biodiversity change, support European biodiversity monitoring and contribute to effective aquatic biodiversity and ecosystem management.