Risk Analysis of Plausible Incidental Exploitation Rates for the Pacific Sleeper Shark, a Data-Poor Species in the Gulf of Alaska

Monte Carlo simulation was used to investigate the sustainability of incidental exploitation rates (<i>U</i>) for Pacific Sleeper Sharks <i>Somniosus pacificus</i> in the Gulf of Alaska (GOA) under status quo management. Monte Carlo simulations were implemented with a standard, length-based, age-structured model that was evaluated with forward projection. Given the paucity of relevant data, we investigated the sensitivity of simulation results to a range of assumptions about key model parameters by using 24 alternative model configurations, each simulated 1,000 times. The risk analysis results were most sensitive to Pacific Sleeper Shark <i>U</i>-values. The aggregate fraction of simulations ending in an overfished condition increased from 0% under the low-<i>U</i> scenario to 59% under the high-<i>U</i> scenario. Risk analysis results were also sensitive to the assumed shape of the length-based selectivity curve (asymptotic or dome shaped) but were less sensitive to the range of assumptions about other key model parameters, including maximum age and stock productivity. These results indicate that a priority for Pacific Sleeper Shark management is to reduce the uncertainty in <i>U</i>. This major uncertainty will be decreased by an observer program that is now in place to monitor the historically unobserved GOA Pacific Halibut <i>Hippoglossus stenolepis</i> fishery, which incidentally catches Pacific Sleeper Sharks. Received March 19, 2015; accepted December 7, 2015 Published online May 16, 2016