Grant Agreement: 101082021Project Acronym: MARCO-BOLOProject Title: MARine COastal BiOdiversity Long-term ObservationsDeliverable Number: D2.4Work Package Number: WP2Deliverable Title: Report on the definition of eDNA-based EBVs with associated eDNA-based EBV datasets and efficiency of eDNA for detecting/quantifying taxa/species of interestDue Date: 30.11.2025Submission Date: 29.11.2025 Work Package 2 (WP2) aims to enable environmental DNA (eDNA)-based methods for standardized biodiversity monitoring. This report (D2.4) presents the outcomes of Task 2.4, which focused on defining eDNA-based Essential Variables — namely Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) — and evaluating their utility for European policy frameworks, including the Marine Strategy Framework Directive (MSFD), the Water Framework Directive (WFD), and the Habitats Directive. Building on other WP2 deliverables (D2.1, D2.2, and D2.3), we identified and generated a suite of eDNA-based EOVs from multiple case-study datasets, including a global survey (Tara Oceans), three coastal time-series (SOMLIT-Astan, LTER-MC/NEREA, the EMO BON UiT genomic observatory), and a dedicated cetacean dataset from the Portuguese coast (CIIMAR). This report demonstrates that EOVs are currently the most operational product directly derivable from eDNA data. The candidate eDNA-based EOVs presented here were formatted to Darwin Core standards and will be deposited in public repositories, providing the foundation for fully functional eDNA-based EOVs. These EOVs serve as standardized building blocks and EBV candidates that can, with expanded sampling and modelling, be transformed into full EBVs. These essential variables (EOVs/EBVs) can work as biological indicators aligned with European frameworks, such as the WFD and the MSFD, and regional conventions, such as OSPAR (Northeast Atlantic), or UNEP-MAP (Mediterranean Sea). Across the case studies, we demonstrate the usefulness of eDNA for generating EOVs and detecting policy-relevant taxa and species: Phytoplankton & Harmful algal bloom (HABs) events: eDNA metabarcoding from time-series data successfully captured seasonal phytoplankton dynamics and HABs events. Generated EOVs are relevant for assessing eutrophication and ecosystem function in marine environments. Fish communities: eDNA metabarcoding revealed seasonal patterns in fish diversity and community composition, while targeted species-specific digital droplet PCR (ddPCR) assays provided quantitative information for sentinel species such as the European anchovy, directly supporting regional indicator frameworks. Marine mammals: eDNA detected multiple cetacean species, including those protected under the EU Habitats Directive, with seasonal occurrences of species validated against visual surveys. Invasive Alien Species (IAS): eDNA expanded the known distribution of several OSPAR-listed invasive species, demonstrating strong potential for early detection in data-deficient areas. Species of conservation concern: eDNA detected several fish species listed as threatened, near-threatened, or vulnerable on the IUCN Red List, highlighting its value for monitoring vulnerable species. Since dedicated performance-evaluation experiments were not available, the efficiency (or usefulness) of eDNA-derived variables was evaluated by comparing them with expected biodiversity signals from conventional observations, and global biodiversity databases (GBIF, OBIS, iNaturalist). These comparisons showed that eDNA patterns were largely congruent with standard methods, while also providing additional insight into taxonomic diversity and species distributions. In conclusion, this deliverable provides a practical scheme and a set of validated case studies showing that eDNA-based EOVs offer a powerful and scalable tool for producing policy-relevant biodiversity indicators. These eDNA-based EOVs are a stepwise improvement from simple raw eDNA observations of individual species and fit the information needs of European and regional environmental directives, paving the way for more comprehensive, standardized, and efficient biodiversity monitoring.
Junger et al. (Sat,) studied this question.