Overview
Invasive marine species (Non-Indigenous Species - NIS) are a major threat to marine ecosystems and biodiversity across Europe. Early detection and rapid response are essential to preventing their spread. This DUC focuses on using genetic monitoring, citizen science, and environmental data to provide early warnings and develop predictive models for managing NIS in Europe’s coastal regions.
Challenge
Detecting and managing invasive species is difficult due to limited data and uncertainties about how to respond effectively. Environmental agencies need clearer guidance on when and how to act. A more coordinated and data-driven approach is crucial for faster, more informed responses to these invasions.
Solution
This DUC combines genetic data from specialised monitoring networks (EMO BON), citizen science alerts, and traditional systematic monitoring programs with marine environmental (e.g., temperature, salinity) and socio-economic data (e.g., traffic, ports, marinas). Genetic data, systematic observations, and environmental data (e.g., water temperature, salinity) are combined to identify invasion hotspots and predict shifts in species distribution.
The goal is to provide actionable insights that help prioritize and speed up management actions.
Biological monitoring and sensor resources
(Methods and networks used to collect biological data about marine species, in this case non-indigenous species (NIS) )
- Genetic monitoring networks (EMO BON) for tracking species through DNA collected from water samples, sediments, or organisms.
- Citizen science networks such as iNaturalist platforms which include public participation in species identification
- Systematic and opportunistic observation networks - structured programs that either systematically monitor species at regular intervals or opportunistically collect data when available (including from citizen scientists).
- National biological monitoring networks - country-specific programs dedicated to monitoring NIS in the marine environment.
Data Sources
- Genetic data: DNA-based information from sequencing platforms such as ENA from European coastal observatories EMBRC-ERIC that provide raw genetic data to understand species' genetic profiles.
- Amplicon-based metabarcoding sequence data: DNA sequencing data from water samples, hard substrates, and plankton surveys.(EMO BON and other European Observatories)
- Conventional observation data: Data from established networks such as GBIF (Global Biodiversity Information Facility) and OBIS (Ocean Biogeographic Information System) that provide general species occurrence and biodiversity data
- Global environmental data layers from LifeWatch ERIC (Bio-Oracle): Environmental data layers from the past including temperature, salinity, and other factors influencing marine habitats.
- Socio-economic data: Information related to human activities, such as marine traffic, port activities, and socio-economic impacts from agencies like HELCOM and OSPAR.
Analysis Tools
- PEMA Pipeline: A bioinformatics tool for analyzing genetic data (e.g., 16S/18S rRNA, ITS, COI marker genes) from metabarcoding datasets to identify NIS.
- Species Distribution Models (SDMs): Predictive models using environmental data to forecast areas at high risk of NIS invasions.
- WRiMS Invasive Species Checker: A tool to cross-reference species occurrences with known invasive species databases, enhancing monitoring efforts.
- Phylogeographic Tools: Software and R packages (e.g., phyloseq, rgbif) to study genetic variation and trace migration patterns across different regions.
Expected outputs
The analyses conducted through this approach will produce a variety of valuable outputs to support the management of non-indigenous species (NIS) in marine environments. Anticipated outcomes are:
- Biogeographic Maps: Visual representations of NIS distribution patterns, highlighting potential future hotspots and migration routes based on current data.
- Early Warning System: Development of actionable early warning alerts for environmental agencies, enabling faster and more effective NIS management interventions.
- Management Recommendations: Insights into high-priority areas for intervention, including potential removal of harmful species like Styela clava, and assessments of ballast water treatment measures.
Target Stakeholders
Environmental agencies and research institutions that manage NIS, municipalities, county councils, port authorities. More specifically, the DUC is based on active collaboration with the
Swedish Agency for Marine and Water Management (SwAM), the Swedish Transport Agency, and the County Administrative Board of Western Sweden (Västra Götaland).
Regulated by MSFD and the Ballast water management convention (BWMC).
Digital twin Features demonstration
DUC 1 demonstrates two key features of the Digital Twin (DT):
- Sensitivity and anticipation of significant events through rapid response to alien intrusions.
- Identifying data gaps and analytical limitations:
Status: ready for the implementation
Leaders: Matthias Obst (University of Gothenburg), Cristina Huertas (LifeWatch ERIC)
