From Biofouling to Biosecurity:
This document is a Q&A on eDNA detection of invasive marine species
Q: What are NIMS?
A: Non-indigenous marine species, meaning species that are not originating from the region or ecosystem they are found in. Not all NIMS are necessarily considered “invasive” but it is hard to know if they will be until they are established in a new environment so they are always considered a threat.
Q: Why are NIMS a threat?
A: They can threaten local marine biodiversity, alter ecosystem functioning, eradicate native species, disrupt food chains, disrupt, damage, and degrade infrastructure, and cause economic losses in aquaculture, fisheries, and tourism.
Q: What is currently the primary pathway for introducing NIMS?
A: Ship hull biofouling (marine growth on vessel hulls).
Q: Why has biofouling overtaken ballast water as the dominant vector?
A: Because the implementation of international Ballast Water Management (BWM) regulations has successfully reduced the risk of species travelling in ballast water.
Q: What factors are accelerating these marine invasions?
A: Increased global maritime traffic and speed of transport, globalisation, and climate change are combining to expand the range of travel and conditions suitable for non-native species survival.
Q: Which regions in Norway face the highest risk of introduction?
A: The Oslofjord and the western coast of Norway, i.e. the areas that see the highest vessel traffic.
Q: What novel methodology did this study test?
A: It integrated robotic (ROV) ship hull cleaning with capture (closed loop) with DNA analyses of the collected waste to create an early warning system for alien species.
Q: How does the ECOsubsea ROV system solve a major pollution risk?
A: Unlike conventional hull cleaning that releases debris into the water, this ROV uses rotating water jets and suction to collect all cleaned material for secure onshore treatment and disposal.
Q: What happens to the wastewater processed by the container unit?
A: It undergoes multiple stages of mechanical filtration down to 1 micron before being safely released back into the sea.
Q: What four distinct sample categories were gathered?
A:
Sedimentation tank water (tank water).
Water sieved out under the biofouling material bags (biofouling water).
Physical biofouling waste solids.
Port water (used as localised control samples).
Q: What types of ships were sampled in the study?
A: Five platform support vessels (PSVs), one cargo vessel/icebreaker, one cruise vessel, and four coastal steamers (passenger ferries).
Q: Which vessel types recorded the most species?
A: In general there were more species collected from the cargo and cruise ships than the passenger ferries and petroleum service vessels. The cruise ship harboured the highest number of NIMS.
Q: Where and when did the fieldwork occur?
A: In the Norwegian ports of Tananger and Bergen, between March 18 and May 17, 2024.
Q: How many official Norwegian list invasive species were detected?
A: 19 invasive species.
Q: What are ‘door-knocker’ species?
A: High-risk alien species that have not yet established locally but pose an imminent threat of invasion. They are considered to have the biological capacity to survive in that potential new environment and there is an established pathway exposing them to that new environment i.e. ship hulls.
Q: How many door-knocker species did the study detect?
A: 8 door-knocker species.
Q: How did researchers prove the door-knockers came from the hulls and not local waters?
A: None of the 8 door-knocker species were found in the local port control water samples; they were detected exclusively within the vessel cleaning materials.
Q: What is the difference between the two primary DNA tools used?
A: Quantitative PCR (qPCR) was used to target a specific single invasive species (Didemnum vexillum), while DNA-metabarcoding was used to identify hundreds of species simultaneously across whole biological communities.
Q: Which genetic markers were deployed for metabarcoding?
A: The TAReuk marker (targeting the nuclear 18S rRNA gene for eukaryotes) and the Leray-XT marker (targeting the mitochondrial COI gene for invertebrates).
Q: How many genetic taxa were discovered in total?
A: 2,199 genetic taxa (OTUs) across 161 total samples.
Q: How many species remained after filtering out single-celled organisms?
A: 784 multicellular eukaryote species.
Q: What were the most diverse animal and plant groups detected?
A: Arthropoda (129 species), Annelida (111 species), Mollusca (87 species), and Rhodophyta/red algae (67 species).
Q: Which vessel category carried the highest biosecurity risk?
A: International traffic vessels. The single cruise ship harbored the highest concentration of NIMS (11 total species, 8 of which were completely unique to it).
Q: What is Didemnum vexillum and what did the qPCR (Quantitative Polymerase Chain Reaction) analysis indicate?
A: Known as ‘sea vomit’, it is a severe-risk colonial sea squirt that has already established in many Norwegian ports. While it tested positive in a sample from a supply vessel (PSV2), it also tested positive in local port water, meaning it likely originated from the harbour rather than the ship.
Q: What were the most severe self-reproducing NIMS found?
A: The red alga Bonnemaisonia hamifera, the copepod Penilia avirostris and the barnacle Amphibalanus improvisus.
Q: Which sample material yields the most DNA data?
A: No single material stands out alone. Tank water, biofouling water, and biofouling solid material all yielded similar numbers of species, but they caught different species. No single material detected more than 50% of the total recorded NIMS.
Q: What surprising relationship was found regarding hull fouling density?
A: Hulls with higher fouling density (more physical mass of growth) actually displayed a decline in overall species richness than those with a lower density.
Q: Can this system be incorporated into standard port operations?
A: Yes. It is non-intrusive, can be integrated into routine commercial cleaning operations with minimal vessel disruption, and provides standardised, repeatable data.
Q: How does this method change marine biosecurity management?
A: It allows countries like Norway to move away from reactive visual monitoring and transition into a proactive, evidence-based early warning framework to intercept invasive species before they settle.
Q: Were there any limitations to the study?
A: Yes, the study had several methodological and data-related limitations, which can be summarised as follows:
● The sampled vessels were heavily skewed toward domestic based or off-shore vessels, therefore, the cruise vessel representing most of the NIMS detected is not likely due to the vessel category (cruise) but more because it represents a true international trading vessel. Future analysis needs to be targeted to get a larger sample of various international vessels.
● Undetected Cryptic Species: The genetic markers used were incapable of discriminating between certain alien species and their native Norwegian sister species due to identical or near-identical DNA sequences (e.g., Acartia hudsonica sequence was identical to the NIMS Acartia tonsa). Therefore, some alien species went completely unrecorded.
● Unclassified Meiofauna: In several distinct groups—specifically Nematoda (roundworms), Platyhelminthes (flatworms), Tardigrada (water bears), and Porifera (sponges)—most species could not be classified as native or alien. This is due to a total lack of baseline scientific knowledge regarding their natural global distributions.
● Venn Diagram Statistical Deviations: The report explicitly flags that because the study analysed more than three distinct sample groups, the deployed R software package was mathematically unable to model all overlaps perfectly. Consequently, the visual figures display slight numerical deviations and completely miss listing two NIMS (Bonnemaisonia hamifera and Oithona davisae) on specific sub-charts.
● Inconclusive Taxonomic Matches: Multiple potential alien species listed in the results (e.g., Ercolania felina, Cauloramphus magnus) remain taxonomically inconclusive due to low sequence variations, single supporting data records, or base pair discrepancies compared against reference databases.