Modelling drift patterns to optimize dFAD deployment

A SEARCULAR BIOFAD model being deployed under semi-controlled conditions in the Mediterranean.

Drifting Fish Aggregating Devices (dFADs) are used in tuna purse seine fisheries to attract fish. Once deployed, they drift in the ocean and attract target fish species which are then caught using a purse seine. dFADs are expected to function effectively at sea for around 6 months. Understanding how dFADs move and accumulate in the ocean is an important factor in both their efficiency as fishing equipment and their potential impact if lost at sea. As part of our work in developing a biodegradable dFAD (BIOFAD) using natural materials, we wanted to understand whether the behaviour of BIOFADs differed from traditional plastic-based dFADs and if so, how. In order to do this, we needed to develop a common approach to modelling these drift patterns.

Lagrangian modelling is used to track the movement of individual objects, or particles, over time and through space. The model is often used for predicting dispersal of pollution such as air particles, or oil spills in water. We wanted to apply and adapt this model to better monitor and predict the draft patterns of dFADs in the ocean.

In May 2026, several of our partners convened in Pasaia, Spain to discuss and progress this modelling work. The workshop allowed AZTI, +ATLANTIC and ISSF to align and significantly advance the Lagrangian modelling framework for tracking and predicting dFAD trajectories. A harmonised modelling approach was agreed, including common assumptions, parameterisation and validation procedures based on observed trajectories and historical datasets.

An example model output showing the predicted drift (orange) and the actual, observed drift (black)

From a technical perspective, the work confirmed that dFADs can be reliably represented using Lagrangian particle simulations, capturing large-scale circulation patterns and enabling robust analysis of drift, accumulation and beaching processes. The team also defined a set of standardised diagnostics and simulation scenarios (including deployment strategies, environmental forcing, and FAD lifetimes/designs) to ensure consistent evaluation across partners.

Implications for BIOFADs:

Our framework enables direct, quantitative comparison between biodegradable and conventional dFADs under the same conditions. In particular, it will allow us to assess how BIOFAD design features (e.g. reduced lifetime or modified structure) translate into reduced accumulation and beaching risk, supporting science-based optimisation of designs and deployment strategies.

Wider application of the modelling approach:

Beyond SEARCULAR, the validated Lagrangian framework provides a transferable tool to predict trajectories of drifting objects, identify accumulation hotspots, and support spatial management measures. This is particularly relevant for improving dFAD management, reducing environmental impacts, and informing decision-making at regional and international levels.

The modelling team. Credit: AZTI