End-to-end modeling as part of an integrated research program in the Bering Sea

• Main Authors: Punt, AE, Ortiz, I, Aydin, KY, Hunt, GL, Wiese, FK
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: eScholarship, University of California 2016
• Subjects: Oceanography; Geochemistry; Ecology; Bering Sea
• Online Access: https://escholarship.org/uc/item/55r435hq

Traditionally, the advice provided to fishery managers has focused on the trade-offs between short- and long-term yields, and between future resource size and expected future catches. The harvest control rules that are used to provide management advice consequently relate catches to stock biomass levels expressed relative to reference biomass levels. There are, however, additional trade-offs. Ecosystem-based fisheries management (EBFM) aims to consider fish and fisheries in their ecological context, taking into account physical, biological, economic, and social factors. However, making EBFM operational remains challenging. It is generally recognized that end-to-end modeling should be a key part of implementing EBFM, along with harvest control rules that use information in addition to estimates of stock biomass to provide recommendations for management actions. Here we outline the process for selecting among alternative management strategies in an ecosystem context and summarize a Field-integrated End-To-End modeling program, or FETE, intended to implement this process as part of the Bering Sea Project. A key aspect of this project was that, from the start, the FETE included a management strategy evaluation component to compare management strategies. Effective use of end-to-end modeling requires that the models developed for a system are indeed integrated across climate drivers, lower trophic levels, fish population dynamics, and fisheries and their management. We summarize the steps taken by the program managers to promote integration of modeling efforts by multiple investigators and highlight the lessons learned during the project that can be used to guide future use and design of end-to-end models.