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The advent of an ecosystem‐based approach dramatically expanded the scope of fisheries management, creating a critical need for new kinds of data and quantitative approaches that could be integrated into the management system. Ecosystem models are needed to codify the relationships among drivers, pressures and resulting states, and to quantify the trade‐offs between conflicting objectives. Incorporating ecosystem considerations requires moving from the single‐species models used in stock assessments, to more complex models that include species interactions, environmental drivers and human consequences. With this increasing model complexity, model fit can improve, but parameter uncertainty increases. At intermediate levels of complexity, there is a ‘sweet spot’ at which the uncertainty in policy indicators is at a minimum. Finding the sweet spot in models requires compromises: for example, to include additional component species, the models of each species have in some cases been simplified from age‐structured to logistic or bioenergetic models. In this paper, we illuminate the characteristics, capabilities and short‐comings of the various modelling approaches being proposed for ecosystem‐based fisheries management. We identify key ecosystem needs in fisheries management and indicate which types of models can meet these needs. Ecosystem models have been playing strategic roles by providing an ecosystem context for single‐species management decisions. However, conventional stock assessments are being increasingly challenged by changing natural mortality rates and environmentally driven changes in productivity that are observed in many fish stocks. Thus, there is a need for more tactical ecosystem models that can respond dynamically to changing ecological and environmental conditions.

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. 2000. Including predation mortality in stock assessments: a case study for Gulf of Alaska walleye pollock. -ICES Journal of Marine Science, 57: 279-293.A separable catch-age stock assessment model that accommodates predation mortality is applied to the Gulf of Alaska walleye pollock (Theragra chalcogramma) assessment. Three predators are incorporated in the model: arrowtooth flounder (Atheresthes stomias), Pacific halibut (Hippoglossus stenolepis), and Steller sea lion (Eumetopias jubatus). The effect of these predators is examined by defining the predation mortality as a type of fishery. The model is used to quantify changes in the relative fit to the survey, fishery, and predator data when the assumption of constant natural mortality is relaxed. Specifically, we examine the effect of assumptions regarding the functional feeding response, residual naturaly mortality, and uncertainty in predator biomass on stock assessment. Total natural mortality rates (including predation) tended to be higher than estimated from life history characteristics of the stock. Models that did not account for uncertainty in natural mortality underestimated uncertainty in current stock biomass by as much as 20%. Our results indicate that independent estimates of survey selectivity, additional food habits data, and estimates of the feeding responses of predators to different prey densities are all needed to improve our ability to develop stock assessment models that address ecosystem concerns. 2000 International Council for the Exploration of the Sea