Much scientific advice for fisheries management is based on results from single species population assessment methods. However, as fisheries management becomes increasingly ecosystem-based, models that consider multispecies and environmental interactions are required, as are effective ecological indicators and reference points. In the Northeast U.S., fisheries managers have recently committed to developing place-based Fishery Ecosystem Plans as part of a broader move towards ecosystem based management. A suite of multispecies and ecosystem models already exist in this region, with several more currently in development. These include Atlantis (a spatially explicit bio-geochemical end-to-end ecosystem model), MS-PROD (a multispecies production model), MSVPA-X (an age structured multispecies model extended to include predators), several static mass-balance food web models, and several single species population dynamics models extended to include predators. Currently in development are a multispecies size structured assessment model (MSSSAM) and a set of linked Ecopath with Ecosim models. While many of these models have an established role in providing strategic advice, the current challenge is to provide tactical management advice for fisheries in a multispecies context that can be readily used within the existing management framework. We outline an interacting system of simulation and assessment models to meet this challenge.
Results/Conclusions
For tactical management, MSSSAM must credibly estimate the status of up to 39 important fish and invertebrate stocks in the Northeast U.S. marine community relative to appropriate reference points. We first focused on estimating status relative to biomass at multispecies maximum sustainable yield (BMMSY) for 10 species on Georges Bank, one of three Northeast U.S. shelf ecoregions. To establish model credibility over a range of plausible system states, Atlantis was used as an operating model to generate input “data” for MSSSAM with known properties for the 10 species, including the impacts of environmental mechanisms not explicitly included in MSSSAM. Comparisons between MSSSAM outputs and the known quantities from Atlantis showed initial mis-specification of the MSSSAM growth model for a subset of species, and identified where environmental covariates were most important to inform recruitment, maturation, and growth. These results were then used to refine the structure of MSSSAM and the process is being repeated. This ongoing work will eventually include comparisons between outputs of MSSSAM and other models for the region to allow multimodel inference in evaluating management options. We ultimately envision a functional ensemble of models incorporating the rich Northeast U.S. data resources to support sustainable fishery management decision making.