Spatial and Temporal Variability in Shipping Traffic Off San Francisco, California

Shipping traffic poses a worldwide threat to many large whale species. Spatially explicit risk assessments are increasingly being used as a tool to minimize ship-strike risk. These assessments often use static representations of shipping patterns. We used Automatic Identification System data to quantify variability in cargo shipping traffic entering and exiting San Francisco Bay, which contains some of the busiest ports in the United States, at three temporal resolutions: (1) before and after implementation of the California Air Resources Board's Ocean-Going Vessels Fuel Rule, (2) among seasons, and (3) day versus night. We used the nonparametric Mood's Median test to compare median daily distance traveled because the data were not normally distributed and the variance was not homogeneous. Our analyses show that shipping traffic off San Francisco is dynamic at both interannual and daily temporal resolutions, but that traffic was fairly consistent among the seasons considered. Our analyses emphasize the importance of economic and regulatory drivers on interannual shipping traffic patterns. Shipping traffic is expected to continue to change off the U.S. West Coast and to increase globally. These changes in shipping traffic could have implications for the risk of ships striking whales and should be included in risk assessments.