**1. Introduction**

In traditional risk assessments, the mortality of seabirds is typically assessed based on a simulated amount of oil combined with a statistical and static (seasonal mean) number of birds within a given grid cell; the size of the cell is typically in the order of 10 by 10 km [1]. It is obvious that cell averaging in a coarse Eulerian grid introduces a high degree of uncertainty with respect to real impact, and due to the patchiness in seabird distribution may result in over-estimation of impacts outside high-density areas and underestimation within high-density patches.

As an alternative to the Eulerian approach risk assessments may be undertaken using the concept of Lagrangian particle tracking. The Lagrangian approach potentially improves the accuracy of risk assessments as the movement of oil particles can be simulated in parallel with a simulation of density and movement of seabirds using the same weather and oceanographical model scenarios. In addition, the predicted impact will have high spatial precision as both oil and seabird particles will be resolved independently from any model grid. With the Langrangian model approach the industry standard risk assessments of oil spills [2, 3] could be further improved. Additionally, the approach would make the results of oil risk assessments in different geographical areas more comparable in the future.

The applicability of this approach in future oil risk assessments is demonstrated for a potential oil spill in the Barents Sea based on the results of the Marine Animal Ranging Assessment Model Barents Sea (MARAMBS) project.

The MARAMBS project (2018–2019) was funded by the Research Council of Norway and aimed for improving the knowledge of the distributional dynamics of seabirds in the Barents Sea. The tentative oil spill scenario was undertaken for an area with a high density of Common Guillemot (*Uria aalge*) during 30 days of the post-breeding period in September 2016.
