A Q&A with Justine Pagnier, a conservation ecologist at University of Gothenburg, EMBRC Sweden

Justine Pagnier is a PhD student focused on advancing omics-based marine biodiversity monitoring in Europe and providing actionable insights for ocean conservation. With more than two years’ experience in the EMO BON network, she is focused on using her expertise and datasets for ecological research that helps marine managers and decision-makers.

As part of EMBRC’s Tech Webinar series, she shared her expertise on the detection and forecasting of non-indigenous species using eDNA metabarcoding and biodiversity modelling. Here are some of the highlights from that session:

The ocean is highly threatened so biodiversity data is critical if we are to understand how natural ecosystems react to human disturbances. This helps us make better decisions for conservation and the sustainable use of marine resources. Plus, environmental health, animal health, and human health are all connected – so it’s important for us too.

The ocean is vast, and many regions—such as the deep sea or the poles—are hard to access and monitor. Marine environments are also highly variable: different areas of the oceans behave differently, so you can’t apply one thing to all kinds of areas.

Historically, monitoring the ocean was costly and labour intensive. You had to send divers out to spot, count and identify species manually. It needed a lot of taxonomic expertise. These challenges led to spatial and temporal gaps in data, and it was also tricky to standardise methods across larger regions.

Today, new technologies (such as research vessels, autonomous robots and remote sensing) are helping to fill these gaps. They complement traditional surveys, rather than replacing them. The result is that we now have access to much more data than before. The new challenge is how to process it efficiently and turn it into actionable information.

The main method is environmental DNA (eDNA), where environmental samples contain traces left behind by an organism in the water, soil, snow or ice. It’s quite sensitive so it allows you to detect rare or cryptic species that are hard to identify, or smaller ones that are hard to see. The biggest limitation is that you must have already sequenced that species to match it. This can mean that some understudied species are being overlooked.

Various sampling methods are used in the EMO BON network. One useful tool to obtain eDNA is Autonomous Reef Monitoring Structures or ARMS. These stacks of nine small PVC plates act like a hotel for species living on the seafloor. Organisms settle and grow on the places over the deployment period (typically 12 months), after which the plates—and their guests—are retrieved for analysis. They can be used to detect a wide variety of taxa, as well as monitoring for alien and endangered species.

We also collect water and sediment samples for eDNA analysis. This combination allows us to detect a broader range of species and to get a more holistic view of marine communities.

Once partners have taken samples, they send them to our centralised sequencing facility in France. The processed FAIR (Findable, Accessible, Interoperable, and Reusable) data can be accessed and used by anyone, whether or not, they are in the EMO BON network.

Alien species are one of the greatest threats to the world’s ocean today, and they have increased drastically in Europe since the 1950s. Species can move to a new place through shipping, deliberate release, or climate change. While some can integrate harmlessly into their new environment, others can damage the ecosystem. When that happens, we call them invasive species, and it’s important to be able to identify and manage them quickly to prevent negative impacts.

Using the ARMS MBON dataset (deployments across 19 observatories in 14 countries from 2018 to 2021), we developed a full analysis pipeline to detect non-indigenous species. This pipeline integrates eDNA metabarcoding data processing, taxonomic assignment, and database cross-checks to identify alien species in the samples. One of the outputs was a set of maps showing which observatories had new or numerous alien species. For example, Plymouth, England, stood out with higher numbers, possibly due to its proximity to ports and shipping channels.

Using modelling, we can identify areas that are more vulnerable to invasions and build an early warning system. If you notice alien species settling, you need to act fast to prevent a negative impact.

The final thing we want to do with alien species is classify them. Some are hitchhikers: they can be transported by ship over a long distance and suddenly arrive far from their native range. Some are range shifters: these slowly move with climate change. Others are more cryptic, and we don’t yet know why or how they move.

Alien Detective is a tool that we’ve been working on for a few months. It allows the classification of species detected in EMO BON data into different categories (native, hitchhiker, range shifter, cryptic) at each sampling site. This will help support management decisions.

It’s still in the testing phase and the code is on GitHub (a development platform), but we are trying to scale it up so that it can be used to process more species. We hope to publish it soon through an official release and a scientific paper.

Emerging monitoring techniques work hand in hand with traditional methods. It’s important to link eDNA with morphology, taxonomy and other disciplines to get the full value from the data. This is important because to reach our goal of protecting 30 percent of the ocean by 2030, we have to act fast and smart. We must protect the most ecologically valuable 30 percent. Integrating different data streams—genetic, imaging, citizen science and remote sensing data—will allow marine managers to make better, real-time decisions, and improve the link between science and policy.