Buffering uncertainty : setting annual catch limits under the Magnuson-Stevens Fishery Conservation and Management Reauthorization Act of 2006

Abstract

The recent Magnuson-Stevens Fishery Conservation and Management Reauthorization Act of 2006 has several new provisions relating to the setting of Annual Catch Limits (ACLs) set by Regional Fishery Management Councils. Specifically, ACLs must ensure no overfishing, and the level at which catch levels are set must not exceed the levels recommended by the Scientific and Statistical Committees (SSC). Due to uncertainty in many aspects of stock assessments, including natural and fishing mortality rates and recruitment, it may be necessary to develop buffers that account for uncertainty and variability, so that the risk of overfishing is minimized. The use of a target and limit framework is useful in this context, allowing for target catch levels (such as ACLs) to be reduced below the overfishing level such that the buffer between the two levels is an adequate distance to account for the uncertainty and variability in the biological and management aspects of a fishery. Age-structured models for the Gulf of Mexico red snapper and red grouper were developed to assess the potential application of an ACL policy under a target/limit framework. Monte Carlo simulations were used to account for recruitment variability and management implementation uncertainty (based on catch overage histories particular to each fishery). After determining the probability of achieving the performance measure of spawning stock size in Year 3 necessary to rebuild to the target stock size in the specified time period, adjustments to catch levels were made. First, catch levels, and the associated fishing mortality rates, were adjusted to account for individual sector's quota overage to address management uncertainty. Then, catch levels were adjusted for an additional buffer of five and ten percent to further improve the probability of reaching the target stock size. In the red snapper fishery, adjusting for quota overages improved the probability of attaining the performance measure to roughly 50%. In addition, certainty levels were improved to around 90% when both management uncertainty and recruitment variability were accounted for under a ten percent buffer. In contrast to the red snapper which is an overfished stock where the objective is to rebuild, the red grouper is above its target stock size, so that the objective is to fish down the stock to the optimum yield level. As such, the red grouper case highlights the importance of specifying an appropriate performance measure. Measuring the probability of the stock falling in a specific range around the target stock size as opposed to the probability of being at or above a target stock size point estimate significantly changes the results. Overall the study's results highlight the necessity of considering, measuring, and accounting for uncertainty, variability, and risk in fisheries assessment and management. Importantly, the results suggest that all sources of uncertainty and variability should be assessed together to determine the appropriate buffer, a contrast to the currently suggested separation of biological and management steps where the SSC handles the biological uncertainty buffer and Councils handle the management uncertainty buffer. Here, it is shown that it may be more prudent and efficient to set buffers by adjusting for quota overages by sector after considering all sources of uncertainty. This improves the probability of success in the performance measure and provides for a solid, equitable basis for setting buffers based on past catch histories specific to each sector. The study provides a basis for risk analysis recommendations, as well as recommendations for clearly defining the objectives and performance criteria of fisheries management. Acceptable risk levels determined a priori, improved monitoring, and continual reassessment all serve to improve the success of fisheries management in ensuring no overfishing, while aiming for optimum yield. Ultimately, this evaluation shows that ACLs, through a limit/target framework, can better inform fisheries policy by accounting for the risk, uncertainty, and variability inherent in fisheries systems, so that the probability of ensuring no overfishing is improved. This study is not meant to provide explicit management advice, rather its purpose is to illustrate the potential process of setting ACLs and highlight the importance of considering risk and uncertainty when making decisions. The model is meant to be a tool that can simulate the effects of a buffer of any size and is meant to be used in the context of a management strategy evaluation to provide pertinent information to decision-makers.