Authors: M. Rafael Ramírez-León, Oscar Sosa-Nishizaki, Paula Pérez-Brunius, Alfonsina E. Romo-Curiel, Zurisaday Ramírez-Mendoza, Arturo Fajardo-Yamamoto, Sharon Z. Herzka and María C. García-Aguilar


Marine mammals are highly vulnerable to oil spills, although the effects at both individual and population levels are not fully understood. A first approximation to evaluate the possible consequences of oil spills on marine life is using ecological risk assessments, which are analytical tools used to assess the likelihood of adverse environmental effects due to exposure to stressors derived from human activities. We developed a semi-quantitative framework to evaluate the risk of oil spill exposure on marine mammals that combines the likelihood of exposure based on species-specific biological and ecological traits, and the feasibility of encounter, which considers not only the overlap between the distribution of the species and the total affected area by a spill but also considers the distribution of spilled oil within this area, thus reducing the uncertainty in the estimate. We applied our framework to assess the risk of exposure of eight cetaceans to scenarios of large heavy oil (API gravity<22) spills originating from three hypothetical deep-water wells in the western Gulf of Mexico. High habitat suitability areas obtained using the maximum entropy (MaxEnt) modeling approach were used as a proxy for the geographic regions where each species is likely to be distributed, and oil spill scenarios were generated using numerical models incorporating transport, dispersion, and oil degradation. The analysis allowed identifying those species for which there is a significant risk of exposure in each spill scenario. However, our results suggest that the risk does not appear to be high for any species under any scenario. The information generated by our risk assessment is key to developing management plans in those areas of the Gulf of Mexico where deep-water activities of the hydrocarbon industry are currently being developed or planned.

Keywords: likelihood of exposure, feasibility of exposure, hydrocarbon industry, ecological traits, geographical distribution, numerical modeling