Effects of Variability in Ship Traffic and Whale Distributions on the Risk of Ships Striking Whales

Abstract

Assessments of ship-strike risk for large whales typically use a single year of ship traffic data and averaged predictions of species distributions. Consequently, they do not account for variability in ship traffic or species distributions. Variability could reduce the effectiveness of static management measures designed to mitigate ship-strike risk. We explore the consequences of interannual variability on ship-strike risk using multiple years of both ship traffic data and predicted fin, humpback, and blue whale distributions off California. Specifically, risk was estimated in four regions that are important for ship-strike risk management. We estimated risk by multiplying the predicted number of whales by the distance traveled by ships. To overcome the temporal mismatch between the available ship traffic and whale data, we classified the ship traffic data into nearshore and offshore traffic scenarios using the percentage of ship traffic traveling more than 24 nmi from the mainland coast, which was the boundary of a clean fuel rule implemented in 2009 that altered ship traffic patterns. We found that risk for fin and humpback whale populations off California increased as these species recovered from whaling. We also found that broad-scale, northward shifts in blue whale distributions throughout the North Pacific, likely in response to changes in oceanographic conditions, were associated with increased ship-strike risk off northern California. The magnitude of ship-strike risk for fin, humpback, and blue whales was influenced by the ship traffic scenarios. Interannual variability in predicted whale distributions also influenced the magnitude of ship-strike risk, but generally did not change whether the nearshore or offshore traffic scenario had higher risk. The consistency in the highest risk from the traffic scenarios likely occurred because areas containing the highest predicted number of whales were generally the same across years. The consistency in risk from the traffic scenarios suggests that static spatial management measures (e.g., changing shipping lanes, creating areas to be avoided, and seasonal speed reductions) can provide an effective means of mitigating risk resulting from ship traffic variability off California.

Modeling Whale Deaths From Vessel Strikes to Reduce the Risk of Fatality to Endangered Whales

“…By this logic, approximately 3% less mortality occurred in the VSR areas for all three species as a result of the long-term speed decline. On an EEZ-wide basis, these speed declines may have had a significant effect on vessel-strike related mortality, but growth in humpback and fin whale populations and shifts in blue whale distribution may have overshadowed that effect, leading to overall increases in strike risk from 2008 to 2015 (Redfern et al, 2020).…”

Co-occurrence of gray whales and vessel traffic in the North Pacific Ocean

“…These measures, al though not specifically aimed at protecting gray whales, likely have reduced the vessel-strike risk to them. In addition, in 2009, 2014, and 2015, California enacted new low-sulfur fuel standards for ships (Redfern et al 2020); in the same period, the IMO established global and North American low-sulfur standards (https:// www. imo.org/en/OurWork/Environment/ Pages/Sulphuroxides-(SOx)-%E2 %80 %93-Regulation-14.aspx).…”

Using Automatic Identification System (AIS) Data to Estimate Whale Watching Effort

“…Apart from its original goal, the enormous quantity of AIS data available has proved to be a valuable source of information on human use of marine areas. As a consequence, it has been used for different purposes: from monitoring fishing activity and protected area regulation compliance (Natale et al, 2015;de Souza et al, 2016;Rowlands et al, 2019), or evaluating cetacean-vessel collision risks (Greig et al, 2020;Redfern et al, 2020) to specific risk evaluation associated with different kinds of vessels (McWhinnie et al, 2021). Also, recently two projects, MARCET and WAVES have been explored for its potential to evaluate whale watching effort (Canessa, 2019;Universidad de las Palmas de Gran Canaria, 2020).…”