Marine oil spills are globally widespread, posing significant threats to marine wildlife. While the spatial and temporal distribution of oil concentrations in the environment can be modeled with high resolution, the impact of petroleum products on marine biodiversity has remained largely unquantified due to a critical missing component: the species-specific sensitivity of marine organisms to oil pollution, particularly to polycyclic aromatic hydrocarbons (PAHs), the most toxic fraction of crude oil. In this study, we address this knowledge gap by developing a predictive model that estimates the sensitivity of marine species to PAHs exposure based on taxonomic proximity and shared ecological traits. We apply this framework to assess the impact of the February 2021 oil spill on marine biodiversity along the Israeli Mediterranean coastline, integrating our sensitivity model with a high-resolution oil transport model (oil-CMS). Our model predicted PAH sensitivity of 88% of key local species, demonstrating that close to the spill core (i.e., the slick), as many as 75.4% of pelagic species were predicted to experience exposure to PAHs concentrations associated with harmful or lethal effects. This novel approach provides a scalable method for assessing biodiversity risks from oil pollution and emphasizes the urgent need to incorporate species-specific pollutant-sensitivity into marine environmental risk and impact assessments.
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