R/FISH/EC-103

Description:

OBJECTIVES : The objectives of the proposed research are to develop an approach to determine robust precautionary catch limits that formally include socioeconomic considerations for ecosystem-based fishery management and apply the method to the blue crab fishery in Chesapeake Bay. The approach to be developed and applied will use a method of robust optimization that is data driven, intuitively attractive, and computationally feasible. These methods will be applied to an enhanced version of the model used in the 2011 blue crab stock assessment (Miller et al., in review). The enhanced model will include estimates of economic revenues and costs to the blue crab commercial fishery. The approach can be used as a decision support tool to make policy recommendations for a range of policy objectives including achieving maximum sustainable yield and maximum economic yield. METHODOLOGY: We will develop a decision support model that includes a modified version of the 2011 blue crab stock assessment model and an economic model. The stock assessment model will be modified to estimate confidence intervals for important parameters and then robust optimization will be used to determine precautionary catch limits. Building on recent work by Nilim and El Ghaoui, the precautionary catch limits will be based on the underlying statistical certainty in the fishery. For example, the model will be able to identify a policy recommendation that, based on the available data, has at least a 90% chance of achieving or surpassing the target outcome. We will estimate the economic relationships utilizing a recent individual-based model with economic components and analysis of recent surveys of blue crab commercial fishermen. The integrated socioeconomic model will be used to evaluate performance of a range of options for the blue crab fishery. Early input for the socioeconomic analysis will be obtained from the Socioeconomic Quantitative Ecosystem Team (SEQET) through an online meeting. We will also work with researchers at the University of Maryland to ensure optimal use of the available data and knowledge of the fishery. A capstone workshop will be held at the close of the project a workshop to share project results with decision makers in the fishery and federal agencies involved with fisheries management. RATIONALE: The Chesapeake Bay is a complex multispecies system in which humans play a dominant role. Two central tenets of ecosystem-based fisheries management of systems like this are that humans must be treated as part of the system and that, given uncertainties, a precautionary approach is justified. However, a rigorous foundation for the necessary level of precaution and a formal inclusion of socioeconomic factors are often lacking. This project will develop and implement a way of establishing robust policies that explicitly recognizes the uncertainty in the system. By developing this method for an actual fishery, the project will yield a clear template for the adoption of the approach in other fisheries in the Chesapeake Bay and elsewhere. The economic analysis will add directly to the stock assessment model, providing estimates of economic values into the model's results and thereby allowing analysts to consider economic in addition to biological goals.