Management strategy evaluation (MSE) is a tool that scientists and managers can use to simulate the workings of a fisheries system and test whether potential harvest strategies can achieve the pre-agreed management objectives. MSE helps to identify the harvest strategy likely to perform best, regardless of uncertainty, and balance trade-offs amid competing management objectives. The MSE in essence is the process of developing and agreeing to a harvest strategy and, unlike traditional assessment-based fisheries science, allows for collaboration between scientists, who do the bulk of the analytical and modeling work on the MSE and managers, with the guidance of stakeholders.
There are numerous ways to structure the MSE framework, but one or more operating models (OM) are at the center of the process. These operating models simulate all relevant aspects of the fisheries system and proposed harvest strategy. The OMs include all plausible hypotheses about the biology of the stock, such as recruitment, and aspects of the fishery, such as the level of illegal fishing activity. Because of the many combinations of assumptions, hundreds of scenarios are often tested.
━━━ a. Generating simulated fishery data (e.g., catch, indices of abundance) from the operating model.
━━━ b. Adding plausible levels of imprecision and bias using the “observation error model” to resemble what happens in a real-world fishery system.
━━━ c. Using the data from the observation error model to estimate stock status, either through a traditional stock assessment model or another approach.
━━━ d. Comparing the estimated stock status with the candidate harvest strategy to determine the management recommendation (e.g., quota, effort limit, size limit or time-area closure).
━━━ e. Subjecting the management recommendation to an analysis of possible implementation error, such as quota overages caused by illegal or unreported catch.
━━━ f. Feeding the output of the implementation error model back into the operating model in step 3A and repeating steps A through E iteratively for many years into the future.